ELE Times

Qualcomm Technologies has used the CMP180 radio communication tester from Rohde & Schwarz to validate advanced multi-antenna capabilities that are designed into its next-generation Wi-Fi 8 platforms, including support for 5×5 MIMO in the 2.4, 5, and 6 GHz bands. Advanced 5×5 MIMO architectures help Wi‑Fi 8 platforms deliver higher capacity and more reliable connectivity across a wider range of real‑world deployment scenarios.

The industry‑leading CMP180 delivers full bandwidth and seamless scalability for testing leading Wi‑Fi 8 chipsets across the entire device lifecycle — from development to production. As a result of this collaboration, Rohde & Schwarz now offers pre‑built test routines and early access to key resources, enabling device manufacturers to accelerate the time‑to‑market of their products.

Wi-Fi 8, based on the IEEE 802.11bn specification, builds on the foundation of Wi-Fi 7 to deliver next-level reliability, efficiency, and seamless mobility. New PHY and MAC layer technologies work together to extend range, improve spectrum utilization, reduce latency, and enable coordinated access across dense environments, setting the stage for ultra-high reliability (UHR) performance. Advanced antenna architectures such as 5×5 MIMO help enhance spatial efficiency and link robustness and provide a more consistent performance in real-world environments.

This new feature set of Wi-Fi 8 will accelerate the wireless LAN performance at home, in offices, venues, and factories, and enable applications like extended reality (XR), AI-assisted applications, real-time cloud gaming, and ultra-high-definition content streaming. To realize these benefits, test equipment must support all bands, full channel bandwidths, multi-antenna operation (MIMO), and deliver best-in-class measurement accuracy at benchmarking test efficiency. Rohde & Schwarz has designed the CMP180 radio communication tester with these capabilities in mind.

The CMP180 enables Qualcomm Technologies to validate essential features of its latest Wi-Fi innovation, including:

• 5×5 MIMO performance to further improve maximum data throughput per link
• Advanced modulation and coding schemes that enable fine‑grained adaptation to real‑time radio conditions.
• Distributed-tone resource units to improve uplink performance under regulatory limits.

Goce Talaganov, Vice President Mobile Radio Testers at Rohde & Schwarz, said: “We are excited to strengthen our long-time collaboration with Qualcomm Technologies to provide a unique testing solution for the next area of Wi-Fi innovations. The CMP180’s advanced features and our close collaboration will empower device manufacturers to bring innovative Wi-Fi 8 products to market quickly and confidently.”

Ganesh Swaminathan, Vice President and General Manager, Wireless Infrastructure and Networking, Qualcomm Technologies, Inc., said: “Qualcomm Technologies’ Wi-Fi 8 portfolio is engineered to deliver next-level performance, reliability, and scalability across a broad range of networking use cases. As part of this portfolio approach, we are advancing innovations such as higher-order MIMO to help increase performance in real-world environments. Our collaboration with Rohde & Schwarz highlights the progress of these capabilities as the Wi-Fi 8 ecosystem builds momentum.”

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Rohde & Schwarz acquired Software Radio Systems (SRS), a specialist in 5G software-defined radio systems. This acquisition further strengthens the position of Rohde & Schwarz in the cellular and wireless communications software market and accelerates development in AI-based test solutions for satellite and next-generation 6G wireless technologies. SRS will continue to operate under its own name as a Rohde & Schwarz group company, maintaining its product roadmap, leadership team and strategic focus. 

The management team at Software Radio Systems, Paul Sutton, Ismael Gomez and Andre Puschmann, will remain. Together with their team at SRS and their new colleagues at Rohde & Schwarz, they will drive innovation in software-defined mobile communications and contribute to the long-term success of the group.

With the acquisition of Software Radio Systems (SRS), Rohde & Schwarz is expanding its software-defined radio (SDR) technology portfolio, strengthening its position in the market for mobile and radiocommunications software, especially in the emerging fields of non-terrestrial networks (NTN) and 6G. The acquisition became effective as of March 5, 2026. Founded in 2012 and headquartered in Ireland, with branches in Barcelona and the USA, SRS has grown from a startup into a globally recognised innovator in mobile and radiocommunications software. The company has established itself as a key player in a highly competitive market through deep technical expertise, product innovation and a strong commitment to open and interoperable network architectures.

By integrating SRS, Rohde & Schwarz decisively expands its capabilities in software-defined radio technology to better serve existing market segments and tap new business opportunities. At the same time, SRS enters a new phase of accelerated growth. With access to deep technical resources from Rohde & Schwarz, global reach and long-term strategic stability, SRS is ideally positioned to scale its technology, expand internationally and execute its long-term mission. The combination of Rohde & Schwarz leadership in test and measurement and RAN expertise from SRS creates powerful synergies that will further advance software-defined mobile network solutions.

Goce Talaganov, Vice President Mobile Radio Testers at Rohde & Schwarz, explains: “I am very pleased that Software Radio Systems is becoming part of the Rohde & Schwarz group. SRS combines extensive telecommunications and wireless expertise with agile software development, making it the ideal complement to our mobile radio testing portfolio, which will benefit the customers of both companies. What SRS and its employees have built up over the past few years is a real success story that you don’t often see. From now on, we will work together to push the boundaries of the technically possible even further, to leverage new synergies and to make an impact on the market.”

Paul Sutton, Chief Executive Officer and co-founder of Software Radio Systems, is ready for the future. “Joining the Rohde & Schwarz group is a proud moment for everyone at SRS. We will continue to operate as SRS with our existing leadership team and a clear commitment to our strategic priorities. What changes is our ability to scale with speed and accelerate the execution of our roadmap, including key initiatives such as the OCUDU project. With Rohde & Schwarz, we gain the strength of a global technology leader whose deep technical expertise, worldwide presence and long-term perspective enable us to grow faster and think bigger. Together, we will expand the impact of our software-defined solutions and deliver innovation that truly makes a difference for our customers.”

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Courtesy: Synopsys

Advances in memory standards are driving faster and more power-efficient mobile and connected devices, from smartphones and tablets to ultra-thin laptops and wearables.

One such standard is Low Power Double Data Rate (LPDDR), which plays a crucial role in balancing high performance with energy efficiency. The latest iteration of the standard, LPDDR6, represents a big step forward in memory management. Comparing LPDDR6 to its predecessors, LPDDR5 and LPDDR5X, reveals just how quickly mobile memory technology is evolving — and what these advances mean for next-generation devices.

The role of LPDDR memory

LPDDR acts as the main system memory inside electronic devices. Working hand-in-hand with device processors and other components to store and access frequently used data, it helps keep applications, media, and multitasking features running smoothly. LPDDR is optimised for low power usage, compact footprint, and fast data transfer, making it ideal for portable, battery-powered devices.

LPDDR can integrate with Inline Memory Encryption (IME) modules to ensure data confidentiality — both in-use and when stored in off-chip memory. This is achieved through standards-compliant independent cryptographic support for read and write operations, providing robust protection against unauthorised access.

LPDDR memory is also available as automotive-grade Synchronous Dynamic Random-Access Memory (SDRAM), making it the preferred DRAM solution for automotive applications that require strict compliance with automotive standards.

LPDDR5 and LPDDR5X: the previous benchmarks

LPDDR5 marked a big step up in mobile memory when it was introduced in 2019. It delivered data rates up to 6.4 Gbps with improved energy efficiency (through features such as Dynamic Voltage Scaling) and smarter data handling. These upgrades led to longer battery life and better support for demanding applications like 5G connectivity, high-resolution media, and the initial wave of artificial intelligence (AI).

LPDDR5 also added new reliability features and smarter error handling, helping stabilise performance under complex workloads. As a result, devices using LPDDR5 delivered noticeable gains in both speed and overall user experience compared to devices using previous generations of LPDDR SDRAMs.

Introduced in 2021, LPDDR5X offered increased performance (up to 10.67 Gbps) and minor enhancements to LPDDR5’s features. LPDDR5X SDRAMs represent the vast majority of LPDDR SDRAMs shipping today.

LPDDR6: the next generation

Published in July 2025, the new LPDDR6 specification and compliant SDRAMs deliver even more performance, efficiency, and features — all designed to meet the growing demands of next-generation mobile and connected devices. LPDDR6 offers:

• Faster data rates. LPDDR6 is expected to reach up to 14.4 Gbps, a significant increase from LPDDR5X. This extra speed is essential for power-hungry applications like augmented reality, ultra-high-definition video streaming, advanced AI, and automotive electronics, all of which depend on rapid data processing.
• Wider bandwidth. Using 24-bit channels (up to 96 bits per package with 4 channels total), LPDDR6 effectively doubles LPDDR5X’s bandwidth per package. In addition, two 12-bit sub-channels in each channel help improve latency and access.
• Enhanced power management. LPDDR6 introduces more precise control over voltage and power states. This upgrade helps devices run more efficiently and extends their battery life as a result.
• Improved reliability and error correction. As the speed and footprint of LPDDR rise, so too does the risk of data errors — especially in data centres. LPDDR6 addresses this challenge with enhanced RAS (Reliability, Availability, and Serviceability) capabilities, providing robust error correction via Metadata, Advanced ECC, and Link ECC features. These improvements help minimise system glitches and stabilise device performance.

While LPDDR6 builds on LPDDR5 and LPDDR5X’s foundations, some legacy mechanisms were streamlined or replaced to support higher speeds and tighter power control. For example, earlier voltage scaling and command encoding schemes have been reworked to enable more granular power states and improved signal integrity. These changes mean LPDDR6 prioritises advanced efficiency and reliability features over older approaches that were optimised for lower data rates.

The implications for memory design and mobile devices

The improved performance, efficiency, and features of LPDDR6 will have wide-ranging impacts. From a technical perspective, LPDDR6 introduces a variety of upgrades to memory architecture:

• Signal integrity and bank management. Smarter signalling and improved memory bank management reduce latency and maximise data throughput.
• Ultra-low power modes. New power-saving states allow devices to conserve energy when idle, a big advantage for wearables and Internet of Things (IoT) products that run on small batteries.
• The new specification is engineered for seamless integration with the latest processors and chipsets, making it easier for manufacturers to integrate LPDDR6 into their next-generation devices.

These upgrades will enable the creation of mobile devices that offer:

• Faster, smoother performance. Higher data rates mean apps open quicker, multitasking is more efficient, and device operation is smoother.
• Better battery life. Improved power management reduces energy consumption, allowing devices to run longer between charges.
• Greater system stability. Stronger error correction improves reliability and reduces the risk of crashes and data loss.
• Future-proofing. LPDDR6 enables devices to support future advances in mobile computing, connectivity, and multimedia.

The Impact of LPDDR6 on smartphones, laptops, and wearables

LPDDR6 represents a significant step forward in mobile memory technology, delivering faster speeds, increased capacity, improved reliability, and better energy efficiency.

Leveraging silicon-proven interface IP and verification IP solutions — which have also been successfully validated at 10.667 Gb/s for SDRAM — device manufacturers are already upgrading their flagship smartphones, high-end laptops, and innovative wearables with LPDDR6-based memory.

But the transition from LPDDR5X/5 to LPDDR6 is more than just a technical upgrade — it enables new possibilities in mobile computing. As manufacturers adopt the new standard, users can expect devices that are faster, more reliable, and ready to support the next wave of on-device and cloud-connected experiences.

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Arrow Electronics and Infineon Technologies AG have announced REF_ARIF240GaN, a 240W USB Power Delivery (PD) 3.2 reference design for battery-powered motor control applications that require high performance and power efficiency in a compact form factor. This design complements the existing portfolio of joint reference design solutions from Arrow and Infineon, supporting the ongoing migration of customer designs to USB-C technology.

REF_ARIF240GaN is specifically designed to support the launch of EZ-PD PMG1-B2, Infineon’s newest USB PD 3.2 controller, featuring up to 240W USB sink capability and integrated buck-boost functionality in a compact single package. It provides developers with a ready-to-use platform for implementing high-power USB-C charging alongside efficient motor drive control features. It brings fast charging capabilities for 2- to 12-cell Li-ion battery packs, simplifying the overall design and reducing components count.

Motor control functionality is delivered using Infineon’s PSOC C3, a 180MHz Arm Cortex-M33 microcontroller, and highly efficient 100V CoolGaN G5 transistors. By combining a fully interoperable USB-C PD stack with high-performance sensor and sensorless GaN motor control on a single platform, the reference design enables compact, high-efficiency battery-powered systems while shortening development time, reducing bill of materials cost and space required.

Target applications include light electric vehicles (e-bikes, e-scooters and personal mobility devices), along with power tools, vacuum cleaners, kitchen appliances, garden equipment and robotics.

The reference design can be obtained upon request. Advanced technical support and customisation services are available from Arrow’s engineering solutions centre (ESC).

Visitors to embedded world 2026 can see the joint Arrow and Infineon solutions for motor control and battery-powered applications at Arrow’s stand 4A-342.

About Arrow Electronics
Arrow Electronics (NYSE:ARW) sources and engineers technology solutions for thousands of leading manufacturers and service providers. With 2025 sales of $31 billion, Arrow’s portfolio enables technology across major industries and markets. Learn more at arrow.com.

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Factories today operate as dense mechanical ecosystems, whether in automotive assembly lines or semiconductor fabrication units. Traditionally, each robotic and mechanical element performed predefined, deterministic functions within isolated automation cells. However, as shop floors become increasingly machine-intensive and interconnected, operational complexity rises proportionally. Managing these environments now requires more than mechanical precision—it demands architectural coordination across layers of control and intelligence.

In this context, the convergence of Information Technology (IT) and Operational Technology (OT) is fundamentally reshaping robotics engineering. Data processing layers—analytics engines, business logic systems, and enterprise platforms—are no longer separated from operational control systems. At the same time, the physical layer, comprising sensors, actuators, servo drives, and Programmable Logic Controllers (PLCs), is becoming increasingly tightly integrated with edge compute and network infrastructure. Robotics systems are no longer designed as standalone motion units; they are engineered as nodes within a larger, connected control ecosystem.

“Traditional automation tools were built for a high-volume, low-variability environment. But today’s market demands agility,” says Ujjwal Kumar, Former Group President of Teradyne Robotics.

This architectural integration is shifting robotics engineering from a purely mechanical discipline toward system-level design—where communication protocols, deterministic networking, cybersecurity, and software orchestration are as critical as torque curves, kinematics, and payload specifications.

Adaptive Systems

At the core of this transformation lies the emergence of adaptive robotic systems. In practical terms, adaptability on the shop floor means the ability to reconfigure, scale, and modify operational behavior through software-defined control and network orchestration, rather than through mechanical redesign. Modern robots are no longer confined to fixed, pre-programmed routines. Equipped with AI models, IIoT connectivity, and high-resolution sensor feedback, they can interpret environmental inputs, process real-time data streams, and dynamically adjust execution parameters.

“The big difference is that traditional automation was a custom-made, perfect solution for one application. The new age of AI-integrated robotics has standard products serving multiple applications. You go into multiple applications through software and some end-of-arm tooling differences,” says Ujjwal Kumar, Former Group President of Teradyne Robotics.

As manufacturers pursue higher efficiency alongside greater product diversity, such adaptability becomes essential. Integrated control and data layers allow robots to transition between production tasks or product variants with minimal downtime, supporting high-mix manufacturing environments. Simultaneously, context-aware operations enable robotic systems to respond to signals from enterprise platforms such as ERP and MES, aligning execution with demand fluctuations, material availability, and downstream constraints.

The Build Architecture: Sensors, Control, and Communication Layers

To understand the engineering behind IT–OT convergence, it is useful to examine the architectural layers that define modern shop-floor robotics. Traditionally, industrial systems followed hierarchical models such as ISA-95, where field devices, control systems, and enterprise platforms operated in structured tiers with limited cross-layer interaction. Today’s robotic systems, however, are increasingly designed around a more unified Industrial Internet of Things (IIoT) architecture—where sensing, control, computation, and enterprise integration operate within a tightly interconnected framework.

“The groundbreaking automation innovations of the future won’t come from one single company but from close cross-technology ecosystem collaborations,” says Ujjwal Kumar, Former Group President of Teradyne Robotics.

At the foundation lies the physical and sensing layer. Modern robots are embedded with dense networks of encoders, force–torque sensors, high-resolution vision systems, vibration monitors, and environmental sensors—particularly critical in semiconductor manufacturing. Unlike earlier generations, where sensors primarily supported local closed-loop motion control, today’s sensing infrastructure generates continuous, time-synchronised data streams. These data flows serve a dual purpose: ensuring precision motion control while simultaneously feeding analytics and optimisation engines upstream.

Above this sits the control and communication layer, where deterministic execution remains paramount. PLCs, motion controllers, industrial PCs, and real-time operating systems govern microsecond-level synchronisation of servo drives and actuators. However, this layer has evolved from rigid, ladder-logic-driven hierarchies to hybrid architectures that combine deterministic control with networked intelligence. Industrial Ethernet, fieldbus systems, and increasingly Time-Sensitive Networking (TSN) ensure that motion commands and data packets coexist without compromising latency or jitter requirements. Control systems are no longer isolated—they are communicative nodes within a broader industrial network.

The next shift occurs at the edge. Edge computing nodes now preprocess high-frequency sensor data, execute AI inference models, and filter operational information before it propagates upward. Event-driven architectures and publish–subscribe communication patterns allow machines to update a shared operational state across the plant continuously. Rather than relying solely on hierarchical polling mechanisms, modern factories operate through near real-time data dissemination, enabling contextual awareness across production assets.

James Davidson, Chief Artificial Intelligence Officer, Teradyne Robotics, says, ” AI is transforming robots from tools into intelligent collaborators that can perceive, learn, and adapt.” 

At the enterprise integration level, robotics systems increasingly interact with MES and ERP platforms, digital twin environments, and predictive maintenance engines. Data flow is no longer unidirectional. Demand signals, material constraints, and quality metrics can influence robotic execution parameters in near real time. This bidirectional exchange is the practical manifestation of IT–OT convergence—where business logic and machine logic intersect.

Underpinning all these layers is a security and infrastructure framework that ensures resilience. As robots become connected assets, cybersecurity, network segmentation, device authentication, and secure firmware management become integral engineering considerations rather than afterthoughts. Connectivity without security would undermine determinism and operational continuity.

Redefining the Core of Robotics Engineering 

For decades, robotics engineering on shop floors was largely centred on mechanical excellence. Engineers focused on motion accuracy, payload capacity, repeatability, structural rigidity, and cycle-time optimisation. The primary goal was to design a robot that could execute a defined task with precision and reliability within a controlled cell.

That foundation still matters—but it is no longer enough. As IT–OT convergence reshapes shop floors, robotics engineering now extends far beyond mechanical design. Engineers must integrate advanced sensors, real-time communication networks, edge computing systems, AI-driven analytics, and enterprise software interfaces into the robot’s architecture. A robot is no longer just a mechanical arm with a controller; it is a connected, data-producing, and data-consuming system embedded within a larger digital ecosystem.

This means engineering decisions are no longer confined to gears, motors, and control loops. Network latency can influence motion stability. Data accuracy affects predictive maintenance outcomes. Software updates can modify operational behaviour. Cybersecurity vulnerabilities can interrupt production. Mechanical performance is now intertwined with software reliability and network integrity.

Physical AI equips robots with the capacity to perceive and respond to the real world, providing the versatility and problem-solving capabilities that are often required by complex use cases that have been out of scope until now,” says James Davidson, Chief AI Officer, Teradyne Robotics. 

In practical terms, robotics engineers are moving from designing machines to designing intelligent systems. They must think about interoperability, data structures, communication protocols, and secure integration—alongside torque curves and kinematics. The robot is no longer an isolated automation asset; it is part of a coordinated production architecture that responds to real-time information from across the enterprise.

The shift is clear: robotics engineering is evolving from a purely mechanical discipline into a multidisciplinary field where mechanics, electronics, networking, and software operate as a unified whole.

Conclusion 

As factories continue to evolve into connected, data-driven environments, robotics can no longer be engineered as standalone mechanical systems. The convergence of IT and OT is embedding intelligence, connectivity, and responsiveness directly into the core of robotic architecture. What was once a discipline defined by mechanical precision is now defined by system integration. 

“Taking a modern Industry 5.0 approach requires prioritisation of adaptability, empowering line workers with robots that can be reprogrammed and redeployed as demand shifts, which is the biggest benefit of having these very flexible systems coming online quickly,”  says Ujjwal Kumar, Former Group President of Teradyne Robotics.

The competitive edge will not belong merely to the fastest or strongest robots, but to those designed as intelligent, interoperable components of a unified production ecosystem. In this new industrial reality, robotics engineering is no longer just about motion—it is about orchestration.

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As enterprises accelerate toward cloud-native infrastructure, edge computing, and virtualised network functions, data volumes and traffic patterns have become increasingly dynamic and unpredictable. This shift has significantly complicated network management, making traditional monitoring and testing approaches insufficient for modern workloads.

Software-Defined Networking (SDN) emerged as a response to this complexity. By decoupling the control plane from the data plane and centralising network intelligence in software-based controllers, SDN introduced programmability, agility, and fine-grained policy enforcement into network architecture. Networks were no longer static hardware constructs — they became programmable systems capable of real-time configuration and orchestration.

However, this programmability has introduced a new challenge: protocol behaviour is no longer deterministic. Dynamic flow rules, frequent controller updates, real-time policy changes, and multi-controller orchestration have made protocol validation exponentially more complex. Traditional pre-defined test scripts and static regression libraries struggle to keep pace with continuously evolving network states.

“AI applications are driving an entirely new set of requirements in our customers’ network equipment and in their network architectures,” says  Joel Conover, senior director at Keysight Technologies

In programmable environments, protocols must be validated not just for correctness, but for adaptive behaviour across changing topologies and traffic conditions. This is precisely where Artificial Intelligence is beginning to redefine network protocol testing — shifting it from rule-based verification to intelligent, adaptive validation.

Traditional Protocol Testing Failing with SDNs

With legacy traditional networks, the protocol behaviour remains largely uniform and predictable. Routing tables were static, firmware updates were infrequent, and network state changes followed predictable patterns. Testing technologies evolved accordingly – with pre-defined test cases, fixed traffic simulations, and rule-based regression suites. But with Software Defined Network, that isn’t the case. 

SDN disrupts this very uniformity and predictability. As with SDN, the control plane is abstracted into centralised controllers, and the network remains largely flexible- not hardcoded into individual devices. Flow rules are dynamically installed, modified, or withdrawn based on application demands, policy engines, and real-time telemetry. As a result, network state becomes fluid rather than fixed. This also puts forth tremendous testing challanges including: 

• Dynamic Flow Table Updates: In SDN environments, flow entries can change in milliseconds. Traditional test scripts, designed for static configurations, cannot continuously validate transient states or short-lived rule conflicts.
• Controller-Driven Logic Complexity: Unlike legacy networks, where protocols like Open Shortest Path First (OSPF) or Border Gateway Protocol (BGP) operate autonomously within devices, SDN controllers introduce centralized decision-making logic. Testing must now validate not only protocol compliance, but also controller algorithms, northbound applications, and southbound API interactions.
• Multi-Controller and Multi-Domain Orchestration: Large deployments often rely on distributed controller clusters for scalability and redundancy. Synchronisation delays, inconsistent state propagation, or split-brain scenarios introduce validation complexity beyond conventional test frameworks.
• CI/CD-Driven Network Updates: Modern SDN deployments increasingly follow DevOps models, where network policies and configurations are updated frequently. Regression cycles that once ran quarterly may now need to be executed daily or continuously.
• Emergent Behavior in Programmable Networks: When multiple applications interact through a controller — security policies, load balancers, traffic optimizers — unintended rule interactions can produce emergent protocol behavior. Static test matrices cannot anticipate such combinations.

In this evolving environment, traditional test automation tools operate reactively. They verify what has been explicitly defined, but struggle to discover what has not been anticipated. As SDN architectures scale in complexity, protocol testing must evolve from deterministic validation — capable of learning network behaviour rather than merely executing predefined scenarios.

The Limits of Automation in Modern SDN Testing

As SDN environments grew in complexity, testing frameworks also adopted automation. Continuous integration pipelines began validating controller updates, traffic replay tools simulated workloads, and orchestration layers executed regression suites at scale. Usually, the traditional automated testing systems operate on predefined logic. They execute scripted scenarios, compare outputs against expected results, and flag deviations. While this approach accelerates validation cycles, it remains fundamentally reactive. It can only test what engineers anticipate. In programmable networks, however, not all behaviours are foreseeable.

With SDNs, Flow rules interact dynamically, policies overlap, and controllers adapt in real time to the telemetry inputs. Under such conditions, failure modes are often emergent rather than explicit. They arise from complex interactions between components rather than from isolated configuration errors.

This is where the limitations of deterministic automation become evident:

• Static rule engines cannot adapt to evolving topology states.
• Regression libraries cannot scale combinatorially with policy variations.
• Manual definition of edge cases becomes impractical in large-scale SDN fabrics.

As networks increasingly resemble distributed software systems, testing must adopt characteristics of software intelligence — the ability to learn patterns, detect deviations autonomously, and anticipate risk scenarios. It is within this context that Artificial Intelligence begins to move from experimental concept to architectural necessity.

How is AI replacing the Automation Debate in Testing? 

As Software-Defined Networks evolve into highly dynamic, programmable infrastructures, testing frameworks must move beyond deterministic execution models. AI-driven protocol testing becomes the obvious and most promising strategy as it is enhanced with contextual learning, predictive analysis, and adaptive decision-making. An effective AI-enabled SDN testing architecture operates across multiple functional layers.

“AI is being infused into many aspects of communications technology – it shows particular promise in predicting channel conditions, essentially creating new forms of ‘smart radios’ that can achieve higher throughput and/or longer distances by incorporating machine learning in the radio itself,” says  Mr Conover. 

At the foundation lies a telemetry intelligence layer. SDN environments generate vast volumes of real-time data — including flow table updates, controller logs, latency metrics, packet drops, topology transitions, and API interactions across northbound and southbound interfaces. Rather than relying solely on post-event log analysis, AI models ingest and process this telemetry continuously. By establishing behavioural baselines, the system distinguishes between acceptable adaptive changes and genuine protocol anomalies.

Built upon this is the Behavioral Modeling Layer. In programmable networks, protocol validation must account for interactions between controllers, applications, and dynamic policies. Machine learning models analyse how control-plane decisions influence data-plane outcomes under varying traffic loads, topology shifts, and failover scenarios. Through supervised and unsupervised learning techniques, the system identifies normal operational patterns and detects deviations that static scripts might overlook — such as cascading latency effects, unstable rule propagation, or intermittent synchronization gaps.

The next layer introduces Intelligent Test Case Generation and Prioritisation. Traditional regression testing treats all scenarios uniformly, often leading to inefficiencies. AI-enhanced systems instead evaluate historical defect data, configuration change patterns, and policy dependency graphs to calculate risk scores. Testing resources are then dynamically allocated to high-risk areas. Reinforcement learning techniques can further simulate targeted disruptions, enabling adversarial-style validation that exposes weaknesses before deployment.

Finally, Predictive Validation capabilities elevate protocol testing from reactive detection to proactive assurance. By analysing patterns across multiple test cycles, AI systems can forecast potential congestion points, controller overload risks, and policy conflicts at scale. This predictive insight is particularly valuable in CI/CD-driven SDN environments, where frequent updates demand continuous and reliable validation.

Together, these layers transform protocol testing from a script-driven verification exercise into an adaptive, intelligence-led framework. As networks become software-defined, testing infrastructures are becoming learning-defined — capable not only of validating correctness, but of anticipating instability before it manifests in production environments.

Conclusion

Software-Defined Networking transformed networks into programmable, software-driven systems — but in doing so, it also made protocol validation far more complex. Static test scripts and deterministic regression cycles are no longer sufficient for environments defined by dynamic flows, controller logic, and continuous updates.

“The use case for network testing is emulating the unique properties of that environment, and delivering it at a scale we’ve never seen before,”  says  Mr Conover. 

Artificial Intelligence is emerging as the natural evolution of network testing. By learning behavioural patterns, detecting anomalies in real time, and prioritising risk intelligently, AI shifts protocol validation from reactive verification to predictive assurance.

The future of SDN will not depend solely on how programmable networks become, but on how intelligently they are tested. As infrastructure grows more dynamic, validation must become equally adaptive — combining automation, intelligence, and human oversight to ensure resilient, scalable network operations.

The post How AI Is Transforming Network Protocol Testing in Software-Defined Networks? appeared first on ELE Times.

Courtesy: Murata Electronics

What is fashion tech? – diverse technologies and methods evolving the industry

“Fashion tech” is a term that combines fashion and technology. It refers to the use of big data, artificial intelligence (AI), augmented reality/virtual reality (AR/VR), and IT in customer services; the development of products incorporating functional materials and wearable devices; and the application of electronics and digital technologies in manufacturing, processing, and distribution processes.

Fashion tech is expected to garner even more attention as a means to invigorate future consumption activities, products, industries, and markets as technology progresses and new products and services are introduced. As mentioned earlier, fashion tech is a broad term, but it can be classified into two categories based on its nature. One is the evolution of services and customer experiences (CX), and the other is the evolution of product functionality and manufacturing processes. We explain these two aspects of fashion tech in the following sections.

Fashion tech evolving the customer experience (CX)

IT and digital transformation (DX) are currently driving fashion tech. There have been many challenges in enhancing sales CX in stores and on e-commerce sites, but many of these have been addressed through IT and DX initiatives.

For example, when selling clothing, shoes, jewellery, watches, eyewear, bags, etc., online, a longstanding issue has been the high hurdle for purchase decisions due to the difficulty for individual consumers to imagine how the actual products would look on them. However, in recent years, virtual fitting via AR (augmented reality), which can be easily used with smartphones and tablets, has become widely adopted. Even without 3D data for products, the technology to enable three-dimensional representation in AR using artificial intelligence (AI), if multiple 2D images of the product are prepared, has lowered the barrier to service introduction.

In parallel with virtual fitting, services are now emerging whereby AI assesses how well eyewear and accessories suit a consumer based on the individual’s facial features and the item’s shape and size. These technological advances are driving improvements in CX through the introduction of fashion tech.

Furthermore, the adoption of radio frequency identification (RFID) technology, including RFID tags and readers, is also advancing, and its applications are moving beyond rationalising inventory management. RFID is being used to reduce checkout lines and payment hassles by simplifying self-checkout and protecting brands, such as by authenticating genuine products.

Additionally, AI is being used to analyse customer and consumption trends across physical stores and e-commerce sites using RFID data. This enables a swift response to customer needs through appropriate inventory adjustments. These are just some of the ways technology is being used.

Fashion tech is evolving product value and manufacturing processes through technology

The DX and CX-oriented fashion tech mentioned above is expected to develop further. In addition, fashion tech that provides new added value to consumers through new characteristics and functions of materials and products is likely to garner more attention in the future due to advancements in materials, wearable devices, engineering, and manufacturing processes.

Here, we introduce technologies such as digital fabrication, smart textiles, smart fabrics, and wearables, which are said to be key to the future development of fashion tech.

Digital fabrication

Digital fabrication is a general term for technologies that make or process products based on digital data. In fashion product manufacturing, it refers to using 3D scanners and 3D CAD to digitise product ideas and patterns and then importing the digitised data into digital manufacturing machines such as 3D printers and laser cutters to shape or process the ideas and patterns.

Digital fabrication has attracted attention in recent years due to the diversification of needs and the development of digital technologies. By streamlining the design and manufacturing processes, digital fabrication has made it possible to accommodate high-mix, low-volume production and the manufacturing of personalised products. It is also gaining attention as a technology for providing new added value to products, such as the manufacturing and processing of materials with structures, functions, and properties that were not previously available.

Smart fabrics (smart textiles)

Expectations are rising for smart fabrics or smart textiles (hereinafter, smart fabrics), technologies that create new added value by imparting functionality to fashion products’ materials themselves. The digital fabrication mentioned earlier is also a means to realise these technologies.

Smart fabrics generally refer to imparting functionality to fibres by integrating electronic technology. The functions are diverse. For example, the clothing itself may function as a sensor to monitor the wearer’s health condition, use electricity for sterilisation, or regulate temperature. Various R&D and commercialisation efforts are underway to realise these functions.

Many of these technologies are attracting attention for a wide range of purposes, such as health and medical care, sports and fitness, and safety improvement. The introduction of such technologies into everyday clothing is being plotted to provide new added value through fashion products with advanced functionality.

Wearable and flexible electronics

The integration of wearable devices into fashion items and the IoT-ization of fashion items themselves are also anticipated as a technology closely related to smart fabrics. For instance, by using wearable devices to process, communicate, display, manipulate, and control data sensed by smart fabrics, products could be endowed with a variety of functions and performance.

Many wearable devices, such as smartwatches, have rigid mounting boards and housings, which is fine for wristwatches. However, these rigid components can interfere with body movement and risk device damage when implemented in wearable items such as clothing.

One promising solution to such challenges is flexible electronics. Flexible electronics refer to pliable electronic circuits and components that can bend. This high compatibility with smart fabrics and wearables raises expectations for their application to future fashion tech and the sophistication of functions it will bring.

Fashion trends cyclically go through revivals. It is hard to imagine that futuristic designs like something out of a sci-fi movie will suddenly become mainstream. This is likely because established designs are rational and fit most people’s sensibilities. On the other hand, while the outward appearance of items may follow traditional lines, the purchasing experience, product functionality, and added value will continue to evolve through fashion tech.

The post What is Fashion Tech? Providing New Product Value and Customer Experiences with Technology appeared first on ELE Times.

Courtesy: Renesas

Detecting human screams for help is important in disaster relief, security, and healthcare applications. Imagine being stuck in an elevator when the usual means of communication failed. An emergency screaming detection system can recognise the distress signal and immediately activate emergency protocols, such as alerting security personnel or triggering an alarm, to efficiently get help and save lives.

Renesas’ Reality AI Emergency Scream Detection is a machine learning (ML) model designed to identify human screams. This model isn’t just about recognising any loud noise; it’s finely tuned to discern distress calls (as a scream) from background sounds. This system will enable immediate dispatch for help, especially important in enclosed or isolated environments where safety is critical.

How does Emergency Screaming Detection work?

The emergency scream detection system is trained to differentiate different audio sounds based on the data collected. The steps involved in developing this machine learning model are as follows:

• Data Collection and Training: The model’s training begins with comprehensive data collection. A public dataset including a variety of audio samples is used. The “Scream” class, featuring intense nonverbal screaming sounds and screaming with words, is used to train the emergency scream detection system. To ensure the model distinguishes what isn’t a scream, a diverse range of sounds such as wind, ambient noise, normal conversation, singing, music, and clapping is also used from the same dataset.
• Feature Extraction: The next step is to extract meaningful features from the audio files that help the model recognise scream-specific patterns amidst various noises.
• Model Training: After selecting the best feature, a machine learning classifier is trained to distinguish between “scream” and “non-scream” audios. The training process involves adjusting the model parameters to minimise errors and enhance its performance.

By using these methods, the emergency scream detection system can be built to ensure emergency responses are swift, providing a vital safeguard in various environments.

Application Example

Audio signals are collected from the real-world environment to create the Renesas VOICE-RA6E1 Voice User Demonstration Kit. These audio signals are then processed by Renesas’ Reality AI-trained classifier model, which helps in distinguishing between “scream” and “non-scream” audio sounds.

The live testing of Renesas’ Emergency Scream Detection model is benchmarked with ≥90% accuracy for screams at a maximum distance of 2 meters from the testing board. The testing conditions also included background noises such as wind, elevator music, human conversations, baby cries, and ringing phones to determine distress signals while maintaining accuracy.

Easily Build the Application Example

Users can collect audio signals with Renesas’ e² studio IDE and integrate any AI model generated from Renesas’ Reality AI software. After collecting data from a public dataset*, deploy the Reality AI software’s tools to perform feature extraction, model training, and deployment of the model to C code.

The deployed model can be integrated for live testing using the e² studio IDE. After integration, the model can be extensively tested in a live setting using the VOICE-RA6E1 board, and the live results can be visualised using the AI live monitor.

Experience the seamless and fast integration capabilities of Renesas’ Reality AI software and e² studio IDE in model training, deployment, and testing of an application.

Conclusion

The Reality AI Emergency Scream Detection application exemplifies the potential of machine learning in enhancing safety measures in various settings and demonstrates how users can employ Renesas’ technology to integrate advanced feature extraction, model training, and deployment with real-time response capabilities. The scalable Reality AI Tools can generate ML models for a wide range of Renesas MCU and MPU devices.

The post Emergency Screaming Detection: How AI Recognizes Human Screams and Saves Lives appeared first on ELE Times.

India’s electronics story has entered a decisive phase. The policy announcements of February 2026 — combined with export milestones and strategic partnerships — suggest that the country is attempting something far larger than incremental industrial growth. It is trying to reposition itself in the global technology hierarchy. But ambition alone will not secure that position. Execution will.

The Union Budget 2026–27 allocated ₹40,000 crore to strengthen domestic component manufacturing under the Electronics Components Manufacturing Scheme. This is a necessary correction. For years, India has excelled at assembling finished goods while importing critical components.

Simultaneously, India Semiconductor Mission 2.0 signalled a deeper commitment to building semiconductor capability across fabrication, assembly, and materials. The intent is clear: India does not want to remain at the lower end of the value chain.

The export data reinforces this shift. Smartphone exports have touched roughly $30 billion, with global leaders such as Apple and Samsung Electronics scaling manufacturing operations in India. This is not a small achievement. In less than a decade, India has moved from a peripheral manufacturing base to a meaningful node in global electronics supply chains.

Yet, the central question remains: Is India building depth — or scale without control?

Assembly success does not automatically translate into technological sovereignty. True leverage lies in advanced semiconductor fabrication, high-end equipment manufacturing, precision materials, and ownership of intellectual property. On these fronts, India still trails global leaders by a wide margin.

The partnership between Qualcomm and Tata Electronics in automotive electronics demonstrates progress in value-added manufacturing. But automotive modules, while strategically important, are not the same as owning leading-edge fabrication technology.

There is also a structural reality policymakers must confront: semiconductor ecosystems take decades to mature. They require uninterrupted capital flow, stable policy frameworks, reliable power, water security, efficient logistics, and depth in engineering. Any inconsistency could stall momentum.

The global semiconductor race is no longer an economic contest. It is a geopolitical war — one fought with export controls, subsidy regimes, technology blockades, and supply chain realignments. The United States has weaponised semiconductor policy through export controls and industrial subsidies. China has doubled down on domestic chip independence. Europe is pouring billions into sovereign fabrication capacity. Taiwan remains indispensable. South Korea protects its giants as strategic assets.

Semiconductors have become the oil of the digital century — and nations are securing supply at any cost.

What India is attempting is bold — and necessary. Electronics today underpin defence systems, AI infrastructure, mobility platforms, and digital economies. Countries that control semiconductor depth control strategic autonomy.

The danger is complacency born from export success. Hitting $30 billion in smartphone exports is impressive. But if core chips, advanced lithography systems, and high-value IP remain imported, strategic vulnerability persists.

India’s electronics sector is at a crossroads. The past month shows strong policy intent and rising industrial confidence. The next five years will test whether this momentum can be translated into irreversible capability.

The world is reorganising supply chains. India has an opportunity to claim a durable position. But the window will not remain open indefinitely. Ambition has been declared. Now comes the harder task — building capability that the world cannot bypass.

The next ten years will determine whether India becomes: a swing state in the global tech war, a protected assembly corridor or a sovereign semiconductor power. The chip war is not theoretical. It is unfolding in export controls, trade negotiations, and defence alliances.

The question now is whether it is prepared to fight at the highest technological tier — or remain a strategic subcontractor in someone else’s supply chain.

History will not remember the announcements. It will remember who controlled the chips.

Devendra Kumar
Editor

The post India’s Electronics Push: Ambition Is Clear. Execution Will Decide the Outcome appeared first on ELE Times.

India to welcome three more semiconductor plants after PM Modi inaugurated Micron’s plant last week, on February 28.

Since the commencement of the India Semiconductor Mission in 2021, India has developed its semiconductor ecosystem exponentially, with four out of ten plants already approved and three more to be inaugurated in 2026 itself. The government further accelerated this by introducing catalyst initiatives like the PLI scheme.

With semiconductors being the core of any modern technology, the demand has grown multifold, and India is pioneering to become a competitive manufacturer for semiconductor to meet the global demand.

India has given approval to ten semiconductor plants in six states with an investment of about Rs 1.60 lakh crore.

As per government records, the approved list of semiconductor plants other than the recently inaugurated Micron plant is as follows:-

1. Tata Electronics (Dholera, Gujarat): Semiconductor fab in partnership with PSMC, Taiwan.
2. CG Power (Sanand, Gujarat): OSAT facility in partnership with Renesas & Stars.
3. Tata Semiconductor Assembly and Test (TSAT) (Morigaon, Assam): Semiconductor packaging facility.
4. Kaynes Semicon Pvt Ltd (Sanand, Gujarat): OSAT facility.
5. HCL-Foxconn JV (Location TBD): Semiconductor packaging and testing.
6. SiCSem Private Limited: Compound semiconductor manufacturing.
7. 3D Glass Solutions Inc.: Advanced substrate manufacturing.
8. Advanced System in Package (ASIP) Technologies: Assembly and testing.
9. Continental Device India Private Limited (CDIL): Discrete semiconductor fab.

The evolving semiconductor landscape in India is expected to generate over two lakh jobs, secure supply chains, as well as strengthen the AI, EV, and defence sectors.

By: Shreya Bansal, Sub-Editor

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Union Minister for Electronics and Information Technology Ashwini Vaishnaw on Sunday encouraged Gujarat to develop itself as a global hub for data-centres to capture data-hosting opportunities from across the world while speaking at the Gujarat SemiConnect Conference 2026 in Gandhinagar.

The Minister highlighted the growing importance of the AI, Semiconductors, and Electronics Manufacturing trio in the coming years. With the world surging in the production of advanced electronics, the above three are beginning to take centre stage, and India must grasp this opportunity to leverage its advantage of skilled population, clubbed with the fertile ecosystem for growth.

Gujarat has great potential to grow as a data centre for the world with its surplus power and availability of clean energy, presenting a bright opportunity for the establishment of such facilities in the state.

The event was attended by other prominent dignitaries like Chief Minister of Gujarat, Shri Bhupendra Patel and Deputy Chief Minister Shri Harsh Sanghvi. The three leaders unveiled the new ‘Science, Technology and Innovation (STI) 2026–31’ Policy at the event.

Organised by the state government’s Department of Science and Technology, and inspired by the Prime Minister’s vision, the conference carried the theme “Gujarat: India’s Silicon Gateway”, aimed at fostering strategic collaboration between high-tech chip manufacturers and local industry.

The Chief Minister described the conference as the “right job at the right time,” highlighting how Prime Minister Modi’s inauguration of the Micron plant at Sanand has ignited a technological revolution for the country. He added that the conference, which was launched immediately after that historic milestone, will demonstrate the state’s readiness to build a semiconductor ecosystem, attract global partners, and fulfil the vision of an Aatmanirbhar Bharat through research, innovation, and supply chain localisation.

India is developing its semiconductor atmosphere, with Dholera Special Investment Region (SIR) in Gujarat being developed as India’s premier ‘Semicon City’ and a global hub for electronics manufacturing. Located near Ahmedabad, it is the site of India’s first commercial semiconductor fabrication unit by Tata Electronics. 

By: Shreya Bansal, Sub-Editor

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Rohde & Schwarz and Qualcomm Technologies, Inc. have reached another pivotal milestone in 6G research and ecosystem readiness, successfully demonstrating carrier aggregation across FR1 and FR3 frequency ranges. The joint achievement is showcased live at MWC Barcelona 2026.

At MWC Barcelona, Rohde & Schwarz and Qualcomm Technologies present a live demonstration at the Rohde & Schwarz booth (5A80) that aggregates a mid-band channel around 2.5 GHz (FR1) with an upper mid-band channel around 7 GHz (FR3), using 4×4 MIMO on both bands and higher-order modulation. With this setup, the two companies validate end-to-end device behaviour across the aggregated spectrum.

At the heart of the test setup is the CMX500 one-box signalling tester from Rohde & Schwarz, extended with the new RFU18 board to provide coverage up to 18 GHz. RFU18 is a modular hardware upgrade for the CMX500 platform, giving customers a straightforward, cost-effective path to extend existing testers towards 6G. As the device under test (DUT), Qualcomm Technologies provided a Mobile Test Platform (MTP) powered by the Qualcomm® Modem-RF System, enabling comprehensive validation of RF performance and protocol behaviour across the aggregated FR1 and FR3 bands.

The FR3 frequency range (7.125 to 24.25 GHz) has been identified by industry and research as a “sweet spot” for combining wide-area coverage with high capacity. FR3 in terrestrial networks (TN) and non-terrestrial networks (NTN) is expected to support demanding applications such as eXtended Reality (XR), connected and autonomous vehicles and industrial automation. By validating FR3 as an additional frequency range for future networks, the partners are helping accelerate 6G development and ecosystem readiness.

Goce Talaganov, Vice President Mobile Radio Testers at Rohde & Schwarz, said: “Through our ongoing collaboration with Qualcomm Technologies, we continue to push the boundaries of wireless communications. As the ecosystem moves toward 6G, we’re showing how easy innovation can be with our test equipment. In response to customer demand, we are extending the CMX500 platform to 18 GHz – so that our customers gain headroom for FR3 evolution and higher-frequency emissions and harmonic testing.”

Tingfang Ji, Vice President of Engineering and Head of 6G Research at Qualcomm Technologies, Inc., said: “Our collaboration with Rohde & Schwarz highlights the importance of aggregating existing spectrum bands with new 6G spectrum in FR3 to establish 6G as the high-efficiency digital infrastructure for the 2030s. By validating new spectrum layers and advanced RF capabilities using our MTP powered by Qualcomm Modem-RF System, we are accelerating innovation across the ecosystem and helping prepare devices and networks for the next-generation of services.”

Future-ready CMX500 platform for 6G:

The CMX500 is a modular, powerful and future-proof one-box signalling tester enabling comprehensive multi-technology testing – from RF to protocol – across all relevant frequency ranges (FR1, FR2 and FR3). All existing CMX500 platforms can be enhanced with the new RFU18 board to extend frequency coverage and capabilities without replacing the entire system, offering users a simple upgrade path.

Engineered for data rates up to 20 Gbps, the CMX500 is one of the most versatile mobile device test platforms, supporting wide dynamic range, 4096QAM and up to 16 device antenna ports for advanced spatial multiplexing. With its multi-band capabilities, it covers LTE and NR in SA/NSA modes, NR-NTN, NB-NTN, Direct-to-Cell (D2C/DTC) testing, and WLAN, including Wi‑Fi 7 and future Wi‑Fi 8.

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ROHM and Suchi Semicon have announced the establishment of a strategic semiconductor manufacturing partnership in India.

This collaboration reflects a shared commitment to strengthening semiconductor manufacturing capabilities in India while supporting the requirements of both domestic and global markets. By combining ROHM’s device technology expertise and global semiconductor leadership with Suchi Semicon’s manufacturing capabilities and operational execution, the companies aim to build a reliable and scalable manufacturing framework aligned with evolving industry needs.

This partnership supports the expansion of semiconductor manufacturing capabilities in India (aligned with the “Make in India” objective) while maintaining global standards of manufacturing excellence. The collaboration aims to enhance supply chain resilience and provide customers with trusted manufacturing solutions.

Specifically, ROHM is considering the outsourcing of back-end processes for power devices and IC products to Suchi Semicon and has begun technical evaluations toward potential mass production shipments starting in 2026. Through these efforts, ROHM aims to build, in collaboration with Suchi Semicon, an early-stage manufacturing framework in India that aligns with the expected industry ramp-up in the coming years.

Furthermore, ROHM and Suchi Semicon will share a roadmap to expand the range of locally manufactured packages, thereby broadening the scope of collaboration between the two companies.

The partnership between ROHM and Suchi Semicon will extend beyond semiconductor manufacturing. Both companies recognise the growing expectations from customers across diverse sectors for locally manufactured semiconductors for the Indian market and will jointly pursue new business development opportunities to meet this demand. In addition, the collaboration will leverage Suchi Semicon’s strong local marketing expertise to conduct joint marketing initiatives that enhance visibility and customer engagement. Importantly, the alliance is not limited to these areas alone; ROHM and Suchi Semicon are committed to exploring further avenues of cooperation, ensuring that the partnership evolves into a comprehensive and long-term alliance that supports the sustainable growth of India’s semiconductor industry over time.

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Batteries have quietly become the limiting factor of modern technology. They define how far an electric vehicle can go, how safely energy can be stored in a city, how fast systems can charge, and how reliably power can be delivered over years of use. In transport, grids, and electronics alike, progress is no longer constrained by motors or software—it is constrained by electrochemical trade-offs embedded deep inside the cell.

At the heart of those trade-offs sits a deceptively simple question: what are you optimising for? Every battery design balances five variables—energy density, safety, lifetime, cost, and scalability—and no chemistry can maximise all five at once. Push harder on one axis, and something else gives way. This is not a materials problem waiting for a perfect solution; it is an engineering problem that demands choice.

That choice, today, largely resolves into two dominant lithium-ion chemistries: LFP and NMC. They are not incremental variations of the same idea. They represent two fundamentally different engineering philosophies. LFP embeds stability, durability, and cost control into the chemistry itself. NMC extracts higher performance by operating closer to material limits, shifting risk and complexity to system-level design.

For companies such as Amara Raja Advanced Cell Technologies, this divergence is not theoretical. It directly shapes manufacturing strategy, product architecture, and long-term capacity planning. The future is not converging toward one universal battery. It is segmenting.

Every battery discussion eventually sounds like a chemistry debate—but the real argument is architectural.

Engineers do not choose LFP or NMC because of crystal diagrams; they choose them based on how each chemistry behaves across five non-negotiable constraints:

• Energy density
• Safety under abuse or fault
• Cycle life and ageing behaviour
• Cost stability and manufacturability
• Scalability across millions of cells

From a manufacturer’s standpoint, these trade-offs extend beyond lab performance. When thermal management, battery management system (BMS) complexity, and warranty risk are considered, the hidden advantages of LFP become system-level advantages.

According to Yi Seop Ahn, Associate Vice President – Centre of Excellence at Amara Raja Advanced Cell Technologies, customers today largely understand LFP’s strengths over NMC:

• Less heat generation, reducing thermal management burden
• Lower degradation at high temperatures
• Reduced BMS complexity due to smaller variation in cell ageing
• Lower warranty risk because of longer intrinsic cycle life

One often underestimated advantage, however, lies in cell sizing. Because LFP carries a lower risk of rupture or explosion compared to NMC, manufacturers can scale cell capacity significantly higher. Larger-format LFP cells reduce the proportion of inactive components within a pack, partially offsetting LFP’s lower gravimetric energy density. In other words, system-level design can compensate for chemistry-level limitations.

At the material level, LFP and NMC reflect opposing design philosophies.

LFP: Structurally Conservative
Its iron–phosphate framework is chemically and mechanically stable. The lattice resists deformation during cycling, tolerates elevated temperatures, and does not readily release oxygen under stress. Stability is intrinsic, not engineered on top.

NMC: Structurally Aggressive
Its layered oxide structure enables higher voltage and energy density, but expands and contracts during cycling. At high states of charge or temperature, structural instability increases. The chemistry delivers more—but demands tighter control.

This difference cascades into real-world outcomes: thermal behaviour, ageing, fast-charging margins, and pack architecture.

In India, the expansion of LFP is not accidental—it is contextual.

Yi Seop Ahn notes that most Indian vehicle usage consists of daily commuting and urban mobility rather than sustained high acceleration or long-distance highway driving. In a price-sensitive market, these usage patterns favour a chemistry optimised for durability, cost stability, and safety rather than peak energy density.

Temperature is an even stronger driver. Intrinsically, LFP performs weaker at low temperatures compared to NMC. However, India’s predominantly hot climate turns this limitation into an advantage. LFP cells exhibit lower degradation at high temperatures and require less aggressive cooling strategies. In such environments, LFP becomes a natural fit.

The result is not merely economic preference — but climatic alignment.

Energy density, thermal behaviour, and lifetime are not separate attributes. They stem from how aggressively a material system is pushed.

NMC achieves higher energy density through higher operating voltage and electrochemically active nickel content. But that gain comes with tighter stability margins and increased reliance on cooling, sensing, and control algorithms.

LFP sacrifices some voltage and gravimetric energy density but maintains wider thermal margins. Ageing remains slower and more predictable due to minimal structural strain during cycling.

From a system-design perspective, LFP reduces the engineering burden outside the cell. NMC shifts complexity upward—into pack design, software controls, and thermal infrastructure.

While LFP is often described as “mature,” its evolution continues across three parallel layers: chemistry, cell design, and system integration.

Chemistry
Over the past decade, LFP active materials have undergone incremental but meaningful improvements. Manufacturing costs have declined significantly, enabling price competitiveness over NMC. Compaction density has steadily increased through sintering process refinements, with further improvements expected. New chemistries such as LMFP are entering the market, targeting improved cycle life alongside electrolyte advancements.

Cell Architecture
Capacity per cell has expanded dramatically. LFP cells have moved into the 300 Ah range and are advancing toward 400–500 Ah formats. Larger cells reduce inactive material proportion and improve effective pack-level energy density.

System Integration
Innovation is accelerating at the integration layer—moving from module-based packs to cell-to-pack and cell-to-chassis architectures. As integration tightens, chemistry choice increasingly influences vehicle platform design.

All three vectors—chemistry, cell scaling, and system integration—are advancing in parallel rather than sequentially.

NMC’s performance advantages remain real and strategically important.

Despite requiring more robust and complex pack management, NMC offers:

• Better low-temperature performance
• Higher power output
• Longer-range capability
• Stronger suitability in weight- and space-constrained applications

These characteristics ensure NMC’s continued relevance in premium and performance-oriented platforms.

Moreover, innovation in electrolyte systems—including semi-solid and solid-state approaches—aims to mitigate thermal risks. Pairing high-nickel cathodes and silicon-dominant anodes with safer electrolyte systems and improved thermal insulation could extend high-energy-density solutions into domains currently dominated by LFP.

In that sense, NMC is not static. It is evolving along a different axis.

Looking five to seven years ahead, battery chemistries are unlikely to remain interchangeable components.

Different nominal voltages and operating profiles between LFP and NMC inherently drive platform divergence. NMC’s need for more robust management systems further reinforces chemistry-specific architectures.

While experimental “dual-pack” or “two-heart” systems exist—combining different chemistries in one vehicle—they require discrete BMS systems and add architectural complexity. The broader trend points toward OEMs standardising around chemistry-specific platforms rather than designing neutral battery bays.

This is not convergence. It is structural segmentation.

LFP and NMC are not competitors in a zero-sum contest. They are solutions optimised for different definitions of performance. LFP embeds safety, longevity, and cost predictability into the chemistry itself—reducing system-level burden and aligning naturally with India’s climate and usage patterns. NMC maximises energy density and performance, accepting tighter operating margins and higher management complexity.

For manufacturers such as Amara Raja Advanced Cell Technologies. 

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Viasat and Rohde & Schwarz are set to collaborate to boost testing for Narrowband Non-terrestrial Networks (NB-NTN) IoT devices connecting via satellite. By thoroughly validating devices and confirming interoperability with Viasat’s network, the collaboration aims to help ensure uninterrupted connectivity for a wide range of satellite-based Internet of Things (IoT) applications. Visitors to MWC Barcelona 2026 can experience the test plan in action.

The collaboration aims to ensure that chipsets, modules and devices interoperate seamlessly with Viasat’s satellite network and comply with 3GPP Release 17 standards.

Deploying advanced testing methodologies upholds the highest standards of quality, performance and reliability for Viasat’s connectivity services: delivering ubiquitous IoT applications in areas without terrestrial network coverage.

The certification test plan with Viasat entails protocol, performance and RF test scenarios. It is based on the CMX500 one-box signalling tester from Rohde & Schwarz, a versatile solution designed for testing various NTN technologies, including New Radio (NR-NTN) and NB-NTN. In a single instrument, the CMX500 covers R&D through certification and carrier acceptance tests, guaranteeing reliable and repeatable results. It empowers engineers to accelerate development, ensure quality and confidently deploy reliable NTN services, safeguarding that the whole ecosystem can achieve the highest levels of performance.

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Keysight Technologies, Inc. will demonstrate lab-based validation of new radio non-terrestrial networks (NR-NTN) devices at Mobile World Congress 2026 in collaboration with Samsung Electronics’ System LSI Business. The demo will showcase testing capabilities aligned with planned Low Earth Orbit (LEO) satellite deployments, including Starlink Direct to Cell.

As satellite connectivity becomes integral to 5G evolution and future 6G networks, chipset and device vendors must validate NR-NTN performance well in advance of large-scale deployment. Satellite systems in LEO introduce new challenges, including rapid motion, frequent handovers, dynamic link conditions, and stringent positioning requirements. Without access to live satellite networks during early development, organisations need accurate laboratory-based methods to assess mobility, service continuity, and throughput performance under realistic operating conditions in a laboratory.

Keysight’s NTN Network Emulator Solutions recreate LEO satellite characteristics in a controlled laboratory environment. The MWC demonstration integrates Keysight’s 5G Network Emulator with a Samsung NR-NTN modem to validate satellite and device mobility, service continuity, and higher-throughput Multiple-Input, Multiple-Output (MIMO) configurations under parameters aligned with Starlink deployment scenarios.

The demonstration also showcases Keysight’s positioning emulation capabilities, enhanced through its recent Spirent acquisition. PNT Xe enables accurate global navigation satellite system-based positioning as part of an end-to-end validation workflow.

Jungwon Lee, Executive Vice President of System LSI Modem Development Team at Samsung Electronics, said: “NR-NTN introduces new technical challenges for modem design, particularly around mobility, handover, and link adaptation in LEO environments. This demonstration with Keysight allows us to validate NR-NTN modem performance under representative satellite conditions, helping ensure readiness for future satellite-based 5G services.”

Peng Cao, Vice President and General Manager, Keysight’s Wireless Test Group, said: “Direct-to-device satellite connectivity is moving from concept to deployment, making early end-to-end NR-NTN validation essential. Our lab-based, live-application testing gives the ecosystem a repeatable way to prove interoperability and performance, cutting risk and time-to-market while keeping users connected beyond terrestrial coverage.”

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Combining TSMC’s Process Technology to Build an End-to-End, In-Group Production System

ROHM has decided to integrate its own development and manufacturing technologies for GaN power devices with the process technology of TSMC, with which ROHM has an ongoing partnership, to establish an end-to-end production system within the ROHM Group. By licensing TSMC GaN technology, ROHM will strengthen its supply capability to meet growing demand for GaN in applications such as AI servers and electric vehicles.

GaN power devices offer excellent high-voltage and high-frequency performance, helping to improve efficiency and reduce size in a wide range of applications, and are already used in consumer products such as AC adapters. Adoption is also expanding in high-voltage applications such as power units for AI servers and on-board chargers for electric vehicles (EVs), and demand is expected to continue growing.

ROHM began developing GaN power devices at an early stage and established a mass-production system for 150V GaN at ROHM Hamamatsu in March 2022. In the mid-power range, ROHM has built its supply structure while advancing external collaborations. One of the key partners in this effort has been TSMC: ROHM has adopted a 650V GaN process since 2023, and in December 2024, the two companies entered into a partnership related to automotive GaN, further deepening their collaboration.

This latest integration represents an evolution of that partnership. Under a newly concluded license agreement, TSMC’s process technology will be transferred to ROHM Hamamatsu. ROHM aims to establish the production system in 2027 to meet expanding demand in applications such as AI servers.

Upon completion of the technology transfer, ROHM and TSMC will amicably conclude their automotive GaN partnership. At the same time, the two companies will continue to strengthen collaboration for higher efficiency and more compact power supply systems.

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element14, an Avnet Community, in collaboration with ADI, has launched a new design challenge inviting engineers and makers to develop advanced security and surveillance prototypes.

Participants are tasked with designing a prototype or test rig utilising ADI’s MAX32630FTHR, a versatile development platform, and Würth Elektronik’s SMD LEDs with an integrated WL-ICLED controller. The challenge encourages creative applications of these components to deliver innovative security features.

Selected challengers will receive a free kit of components, with ADI’s MAX32630FTHR as the core element, to assist in building their prototypes. Each participant will document the build process and final outcome through blogs on the element14 Community platform.

Examples of potential applications include facial recognition door entry systems, voice and face detection, environmental monitoring, crowd sentiment analysis, break-in detection and remote security sentry solutions.

“Through this challenge, we’re inviting our global community to showcase creativity and problem-solving in the field of security and surveillance,” said Andreea Teodorescu, Global Director of Product Marketing & element14 Community. “It’s an opportunity for participants to learn, share ideas, and demonstrate how innovative thinking can address real-world safety challenges.”

“We’re excited to collaborate with the element14 Community on a challenge that inspires creativity and problem-solving,” said Stephane Di Vito, ADI Distinguished Engineer, Product Security. “This initiative brings together passionate designers and engineers to explore new ideas and develop solutions that can make security smarter and more effective.”

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Rohde & Schwarz and LITEON collaborate to showcase a production-optimised test setup for high-throughput multi-device testing at MWC Barcelona 2026. The demonstration will feature the high-performance PVT360A vector performance tester from Rohde & Schwarz characterising in parallel four new LITEON FlexFi 5G femtocells as devices under test (DUT). The setup highlights the adaptability of the test platform to various production and validation environments, all within a compact form factor.

Rohde & Schwarz has designed the PVT360A performance vector tester with a minimal footprint for maximum performance. It is a comprehensive solution for non-signalling 5G NR FR1 and LTE small cell testing in the design verification stage and in production. LITEON has selected the test platform for the manufacturing lines of their new FlexFi 5G femtocell, boosting the overall testing speed by 50%. At MWC 2026, the two companies will showcase a femtocell production testing setup characterising four DUTs using a single PVT360A.

The single‑box vector signal generator (VSG) and vector signal analyser (VSA) solution delivers efficient, high‑performance RF testing and pairs seamlessly with the R&S VSE Vector Signal Explorer software for reliable timing verification as well as comprehensive 5G NR downlink and uplink signal analysis. Engineered to significantly accelerate 5G production testing and streamline design validation workflows, the PVT360A features an innovative 2×8 port architecture, coupled with a unique Smart Channel feature that dynamically optimises resource allocation. This dramatically increases test throughput and enables manufacturers to test more devices in less time.

Beyond core testing efficiency, the PVT360A supports advanced 5G scenarios, including multi-component carrier testing and highly accurate MIMO measurements with optional dual signal generators and analysers. This combination of speed, versatility and support for complex 5G technologies makes the PVT360A a critical tool for manufacturers looking to rapidly scale 5G device production and deliver cutting-edge performance.

To enhance both the production efficiency and quality of its 5G femtocell products, LITEON has successfully integrated the PVT360A performance vector tester into its manufacturing lines, enabling fully automated calibration and verification processes. Leveraging its proprietary Smart Channel technology, a single unit can now simultaneously test four 5G femtocells. This enhancement has delivered a 50% increase in overall testing speed, significantly boosting production throughput while maintaining superior product consistency.

Richard Chiang, General Manager of LITEON Smart Life Application SBU, said: “To enhance our manufacturing excellence, we are embarking on a long-term partnership with Rohde & Schwarz. By adopting their PVT360A platform, we aim to achieve higher levels of automation and precision in our testing processes, ensuring that our products consistently meet the highest market standards.”

Goce Talaganov, Vice President Mobile Radio Testers at Rohde & Schwarz, said: “We are proud to support LITEON in advancing its smart manufacturing strategy with our PVT360A platform. Their ability to achieve higher throughput and consistent quality demonstrates how our scalable multiport architecture and smart channel technology can transform production efficiency. We look forward to deepening our collaboration and enabling even greater innovation in 5G small cell manufacturing.”

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Next-generation embedded systems are essential for applications in the rapidly evolving connected world. They range from high-performance sensors for capturing critical data to advanced microcontrollers (MCUs) that process and analyse this data. At Embedded World 2026, taking place from March 10 to 12, 2026, in Nuremberg, Germany, Infineon Technologies AG will demonstrate how its innovative semiconductor solutions enable green and efficient energy, clean and safe mobility, and an intelligent and secure IoT. True to the motto “Driving decarbonization and digitalisation. Together,” the Infineon booth in Hall 4A, booth 138, will present highlights for applications ranging from AI and IoT to automotive and robotics that contribute to a more sustainable future.

Infineon’s highlight topics at embedded world 2026

Microcontrollers – the core of embedded intelligence: MCUs are the central processing units of modern embedded systems, coordinating control, computation, and connectivity in countless applications. In Nuremberg, Infineon will demonstrate its comprehensive MCU portfolio through live demos that illustrate real-world use cases, such as:

• Edge AI and robotics demonstrations, where Infineon PSOC and AURIX MCUs enable deterministic real-time processing, adaptive control, advanced safety, and secured connectivity
• Demos targeting software-defined vehicles, including the TRAVEO SDV Zonal Demo, highlighting how automotive MCUs support zonal E/E architectures, OTA updates, and software-driven innovation
• Industrial and IoT applications, showing how energy-efficient MCUs combine performance, safety, and cybersecurity to enable smart devices and enable manufacturers to comply with the upcoming European Cyberresilience Act (CRA)

XENSIV sensors – bridging the physical and digital worlds:

Sensors act as the interface between the real world and digital processing, enabling precise data acquisition for control, monitoring, and decision-making processes. At Embedded World 2026, Infineon will present its XENSIV sensor portfolio, demonstrating how sensor data powers advanced systems across automotive, industrial, and consumer electronics. The demos include:

• Robotics and Edge AI demos in which Infineon XENSIV sensors enable robots to see, hear, and feel, providing the environmental and contextual awareness required for safe interaction and autonomous behaviour
• Automotive and SDV-related use cases, showcasing how radar, magnetic, and current sensors support perception, monitoring, and zonal architectures in modern vehicles
• IoT and industrial demonstrations,s including the next generation XENSIV CMOS 60 GHz radar for IoT. These illustrate how MEMS microphones and other XENSIV sensors deliver reliable, high-fidelity data for connected and energy-efficient devices

In addition, Infineon experts will be giving in-depth presentations demonstrating how the company’s MCU and sensor solutions enable efficient, secure, and rapid innovations in areas such as AI, robotics, IoT, and software-defined vehicles.

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