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Нове укриття у 5 корпусі КПІ ім. Ігоря Сікорського! kpi ср, 10/01/2025 - 18:02

Frequent contributor Christopher Paul recently provided us with a painstakingly conservatively error-budget-analyzed Design Idea (DI) for a state-of-the-art pursuit of a 16-bit-perfection PWM DAC.

The DI presented below, while shamelessly kibitzing on Chris’ excellent design process and product, should in no way be construed as criticism or even a suggested modification. It is neither. It’s just a voyage into the strange land of ultimate precision.

Wow the engineering world with your unique design: Design Ideas Submission Guide

In his pursuit of perfect precision, Christopher creatively coped with the limitations of the “art.” Perhaps the most intractable of these limitations in the context of his design was the temperature coefficient of available moderately priced precision voltage references. His choice of the excellent 35xxx family of references, for example, exhibits a temperature coefficient (tempco) of 12 ppm/°C = 0.8 lsb/°C = 55 lsb over 0 to 70°C, reducing this element of conversion precision to only an effective 10.2 bits. 

Since that was more than an order of magnitude worse than other error factors (e.g., DNL, INL, ripple) in Christopher’s simple and elegant (and nice!) design, it got me musing about what possibilities might exist to mediate it. 

Let me candidly admit upfront that my musing was unconstrained by a concern for the practical damage such possibilities might imply towards the simplicity and elegance of the design. This included damage, such as doubling the parts count and vastly increasing the power consumption.

But with those caveats out of the way, here we go.

The obvious possibility that came to mind, of course, was what if we reduced the importance of thermal instability of the reference by the simple (and brute-force) tactic of putting it in a thermostat? Over the years, we’ve seen lots of DIs for using transistors as sensors and heaters (sometimes combining both functions in the same device) for controlling the temperature of single components. Figure 1 illustrates the thermo-mechanics of such a scheme for this application. 

Figure 1 Thermally coupling the transistor sensor/heater to the DAC voltage reference to stabilize its temperature.

A nylon machine screw clamps the heatsink hotspot of a TO-220-packaged transistor (TIP31G) in a cantilever fashion onto the surface of the reference. A foam O-ring provides a modicum of thermal insulation. A dab of thermal grease on the mating surfaces will improve thermal coupling.

Figure 2 shows the electronics of the thermostat. Here’s how that works.

Figure 2 Q1 is a combo heater/sensor for a ±1°C thermostat, nominal setpoint ~70°C. R3 = 37500/(Vref – 0.375).

Q1 is the core of the thermostat. Under the control of gated multivibrator U1, it alternates between a temperature measurement when U1’s “Out” pin is low, and heating when U1’s “Out” pin goes high. Setpoint corresponds to Q1 Vbe = 375 mV as generated by the voltage divider R3/R4, detected by comparator A1, and timed by U1. 

I drew Figure 1 with the R3/R4 divider connected to +5 V, but in practice, this might not be the ideal choice. The thermostat setpoint will change by ~1.6°C per 1% change in Vref, so sub-percentage-point Vref stability is crucial to achieve optimal 16-bit DAC performance. The +5-V supply rail may therefore not be stable enough, and using the thermostatted DAC reference itself would be (much) better.

Any Vref of adequate stability and at least 365 mV may be used by simply setting R3 = 37500/(Vref – 0.375). For the same reason, R3 and R4 should be 1% or better metal film types. The point isn’t setpoint accuracy, which matters little, but stability, which matters much.

Vbe > 375mV indicates Q1 junction temp < setpoint, which gates U1 on. This allows U1 “Out” to transition to +5 V. This turns on driver transistor Q3, supplying ~20 mA to the Q1, Q2 pair. Q2 functions as a basic current regulator, limiting Q1’s heating current to ~0.7 V/1.5 Ω = 470 mA and therefore heating power to 2 W

The feedback loop thus established, Q1 Vbe to A1 to U1 to Q3 to Q1, adjusts the U1 duty cycle from 0 to 95%, and thereby tweaks the heating power to maintain thermostasis. Note that I omitted pinout numbers on A1 to accommodate the possibility that it might be contained in a multifunction chip (e.g., a quad) used elsewhere in the DAC.

Q.E.D. But wait! What are C2 and R2 for? Their reason for being, in general terms, is to be found in “Fixing a fundamental flaw of self-sensing transistor thermostats.”

As “Fixing…” explains, a fundamental limitation on the accuracy of thermostats like Figure 1 is as follows. The junction temperature (Tj) that we can actually measure is only an imperfect approximation of what we’re really interested in: controlling the package temperature (Tc). Figure 3 shows why.

Figure 3 The fatal flaw of Figure 1: the junction temperature is an imperfect approximation of the package temperature.

Because of the nonzero thermal impedance (Rjc) between the transistor junction and the surface of its case, an error term is introduced that’s proportional to that impedance and the heating power:

Terr = Tj – Tc = Rjc*Pj

In the TIP31 datasheet, Rjc is specified in the “Thermal Characteristics” section as 3.125 °C/W. Therefore, as Pj goes from 0 to 2 W, Terr would go from 0 to 6.25 °C. Recalling that the REF35 has a 12 ppm/°C tempco, that would leave us with 12 x 6.25 = 75 ppm = 5 lsb DAC drift. 

That’s 11x better than the 55-lsb tempco error we started with, but it’s still quite a way from true 16-bit accuracy. Can we do even better?

Just like the R11, R12, C2 network in Figure 2 of “Fixing a fundamental flaw of self-sensing transistor thermostats” that adds a Pj proportional Terr correction to the thermostat setpoint, that’s what R2 and C2 do here in this DI. C2 accumulates a ~23 ms average of 0 to 100% heating duty cycle = 0 to 700 mV, and adds through R2 a proportional 0 to 14 mV = 0 to 6.25°C Terr correction to the setpoint for net ±1°C stable thermostasis and < 1 lsb reference instability.

Now Q.E.D!

Stephen Woodward’s relationship with EDN’s DI column goes back quite a long way. Over 100 submissions have been accepted since his first contribution back in 1974.

 Related Content

• Fixing a fundamental flaw of self-sensing transistor thermostats
• A nice, simple, and reasonably accurate PWM-driven 16-bit DAC
• Double up on and ease the filtering requirements for PWMs
• Inherently DC accurate 16-bit PWM TBH DAC
• Self-heated ∆Vbe transistor thermostat needs no calibration
• Take-back-half thermostat uses ∆Vbe transistor sensor
• 1kHz per Kelvin temperature sensor
• Measure junction temperature using the MOSFET body diode on a PG pin

The post A transistor thermostat for DAC voltage references appeared first on EDN.

Molecular beam epitaxy (MBE) system maker Riber S.A. of Bezons, France has confirmed a 22% drop in revenue from €13.7m in first-half 2024 to €10.7m for first-half 2025, reflecting a delivery schedule that is concentrated into second-half 2025. The firm says that, in a complex international environment, it recorded solid commercial activity, despite particularly pronounced seasonality...

Photonic integration firm Photon Bridge of Eindhoven, The Netherlands is collaborating with transceiver maker PICadvanced of Ílhavo Portugal to showcase prototype transceivers built using its multi-material integrated photonics platform...

Участь представників ФБТ у Літній академії в Німеччині: обмін досвідом та розвиток міжнародних відносин Інформація КП ср, 10/01/2025 - 14:10

The world of manufacturing is changing very fast with digital intelligence merging with the conventional industrial processes. Physical AI lies at the heart of this revolution, bringing together sophisticated algorithms and machinery such as robotic arms, autonomous guided vehicles (AGVs), and CNC machinery. For these systems based on AI to function optimally, they depend on real-time information from industrial sensors. Serving as the “eyes and ears” of machines, sensors today do much more than make measurements they allow AI systems to learn, adapt, and optimize processes to enhance productivity, safety, and efficiency.

The two-part series addresses how industrial sensors enable physical AI applications. The first part discusses sensor types and functions in smart factories, while the second part will discuss innovations and trends that will dominate next-generation physical AI-powered industrial systems.

How Industrial Sensors Enable Physical AI

Industrial sensors measure physical parameters like motion, distance, pressure, temperature, or flow into electrical signals that undergo parameterization. These signals find their way into PLCs, CNC machines, and edge AI devices that carry out real-time decision making.

A typical sensor has some or all of these components: sensing element, operational amplifier OpAmp, ADC, processor, interface, and power management. All these or some of them constitute the sensor acting as a bridge between AI algorithms and the physical world, much like the nervous system transmitting information to the brain.

With a modern smart factory, there is an increase in the deployment of AI at the edge, embedding algorithms in sensors, robots, and controllers themselves. This obviates decision making in real-time being made on cloud-based IT systems alone.

Key Industrial Sensor Types

Vision (Image) Sensors: Cameras used to capture product images for machine vision, inspection, and quality control. They recognize orientation, defects, and positioning in real time. Next-generation short-wave infrared (SWIR) and low-power image sensors provide high dynamic range and low-light capabilities in demanding industrial settings.

Position & Torque Sensors: Hall-effect, optical, and inductive sensors are used to detect motor position and torque. Latest inductive PCB-based sensors combine analog front-ends and controllers to make mechanical design easier while providing improved temperature tolerance and contamination resistance.

Ultrasonic Sensors: Detect distance by emitting ultrasonic waves. Suitable for detecting transparent objects, ultrasonic sensors are widely applied in autonomous robots for navigation and obstacle detection and in process automation for flow and level measurement.

Photoelectric Sensors: Capture objects using light-based technologies infrared or laser and come in through-beam, retroreflective, and diffuse-reflective configurations. They are non-contact, flexible, and accommodate long detection ranges.

Proximity Sensors: Sense metallic objects using electromagnetic induction without contact. They are durable in harsh environments and can be used in conjunction with ultrasonic or photoelectric sensors to detect non-metallic objects.

Pressure Sensors: Condition clean-room environments and pneumatic or hydraulic systems. They deliver accurate voltage readings that represent system pressure using strain gauges or force resistors.

Temperature Sensors: Monitor and control temperature in various industries. Thermocouples, RTDs, and semiconductor temperature sensors protect machinery and stabilize processes.

Environmental Sensors: Add gas, chemical, rain, and light sensors to measure environmental conditions and workplace safety. For example, electrochemical sensors can measure chemical currents at low power consumption, providing constant monitoring.

Selecting the Correct Sensors for Intelligent Manufacturing

When designing industrial systems with AI, engineers should keep in mind:

1. Application Response Speed & Accuracy: Response speed and accuracy should be suited to the job, from control of robots to quality inspection in real time.
2. Data Reliability: Sensors need to deliver high-quality data reliably to enable AI learning and analytics.
3. Integration & Interoperability: Sensors need to integrate seamlessly with PLCs, field buses, and other industrial automation.
4. Data Privacy & Cybersecurity: Preserving sensitive operating data is essential, particularly as sensors communicate data through networks.
5. Energy Efficiency: Sensors with low power consumption allow widespread deployment without exceeding power budgets.

Conclusion:

Industrial sensors are critical to enable physical AI in the smart factory spaces. By sensing the physical world accurately and interpreting it, these sensors enable AI systems to make quicker, wiser, and more secure decisions. With advancements in sensor technologies, they will further propel more intelligent, adaptive, and more sustainable industrial activities, leading the way to Industry 5.0.

With its extensive sensor portfolio and application know-how, Onsemi continues to be the leader in intelligent sensing, assisting manufacturers to unlock the full value of physical AI.

(This article has been adapted and modified from content on Onsemi.)

The post How Industrial Sensors are Powering the Age of Physical AI in Smart Manufacturing appeared first on ELE Times.

The US Department of Energy’s (DOE) Office of Fossil Energy and Carbon Management (FECM) has announced up to $6m in federal funding available for R&D projects to help establish a secure domestic supply chain for gallium...

Делегація кафедри МАтаТЙ ФМФ в Університеті Мелардален (Швеція) kpi ср, 10/01/2025 - 11:55

Photonic integration firm Photon Bridge of Eindhoven, The Netherlands has debuted its integrated tunable laser photonic integrated circuit (PIC), powered by its patented cantilever waveguide coupling technology (which combines III-V speed with silicon scale)...

A breakthrough in wearable technology is redefining what smart glasses can do: generative AI running entirely on the device, without the need for a phone or cloud connection. Powered by the new Snapdragon AR1+ Gen 1 platform, the glasses allow an AI to interact seamlessly in every day scenarios-from shopping or any home tasks.

AI Fitting Inside Glasses

In a live demonstration, a generative AI assistant operated directly on smart glasses using a compact language model (SLM). During a simulated grocery trip, the assistant helped with a recipe, delivering audio guidance and text directly on the lenses all without any external device. This is a strong demonstration of what is going on with smart glasses from mere accessories to full-blown, standalone AI tools.

Snapdragon AR1+ Gen 1

The Snapdragon AR1+ Gen 1 processor, 26% smaller than previous generations, brings enhanced power efficiency, improved image quality, and the ability to run small language models directly on the glasses. These improvements are crucial for thinner, lighter frames that don’t compromise performance or functionality.

Flexible XR Ecosystem

Next-generation smart glasses will be available in various form factors. Some will be standalone, and others will be linked to nearby devices like smartphones, tablets, or portable computing “pucks.” This modular system provides flexible, high-performance experiences across various configurations while keeping AI interactions speedy, private, and responsive.

Improved Vision and Multimodal Inputs

Sophisticated camera features enable glasses to record and perceive the world in rich detail, enabling proactive suggestion and context-sensitive help. Even when not connected to other devices, these glasses can be paired with other wearables like smartwatches or rings, enabling new forms of interaction and input.

Conclusion

This demonstration represents the beginning of a new era in wearable AI, in which intelligent glasses have the capability to provide tailored, real-time support on the move. Powered by the Snapdragon AR1+ platform, Qualcomm is making some of the thinnest, cleverest, and most powerful glasses possible that might change the way we engage with technology in our everyday lives.

(This article has been adapted and modified from content on Qualcomm Technologies.)

The post On-Glass Generative AI: The Next Era of Standalone Smart Glasses appeared first on ELE Times.

The hardware, software and  Intelligent Factory concept presented by market and technology leader ASMPT drew strong interest from trade visitors at this year’s productronica India.

At the joint booth with long-standing distribution partner Maxim SMT, the spotlight was on the fast, precise, and process-stable DEK TQ solder paste printer platform and the SIPLACE TX high-speed placement solution. The SIPLACE CP20 and SIPLACE CPP placement heads on display also proved particularly well suited to the high-volume production that characterizes the Indian market, offering manufacturers maximum flexibility and productivity in demanding high-volume production.

Integrative concepts for high-volume production

Many visitors took the opportunity to gain a detailed understanding of a complete ASMPT production line in personal technical discussions. Of particular interest was the integrated concept of the intelligent factory, where standardized interfaces across all ASMPT machines continuously collect and process data, making it available where it can be used to enhance quality, prevent errors, and eliminate production bottlenecks.

Comprehensive software portfolio

ASMPT’s extensive software portfolio attracted strong interest from the expert audience. At the core is the WORKS Software Suite, which supports all line-related processes, complemented by the Factory Solutions for holistic optimization across the entire manufacturing environment – including critical areas such as material intralogistics. Live demonstrations featured WORKS Optimization, the intelligent inline expert system for end-to-end process improvement; the Factory Equipment Center, an integrated asset and maintenance management system; the Material Flow Optimizer, ensuring efficient intralogistics and smooth material supply; and SMT Analytics, providing in-depth analysis of the entire SMT production process across all lines.

“We were very pleased with the strong interest shown in our insights and the solutions we showcased for state-of-the-art electronics manufacturing,” summarized Neeraj Bhardwaj, General Manager for India at ASMPT SMT Solutions. “The lively response confirms that we are on the right track in this important growth market.”

The post ASMPT at productronica India: Transform your SMT production with ASMPT appeared first on ELE Times.

New digital micromirror device with real-time correction enables equipment manufacturers to achieve high-resolution printing at scale, maximizing throughput and yield

What’s new

Texas Instruments is enhancing the next generation of digital lithography with the introduction of the DLP991UUV digital micromirror device (DMD), the company’s highest resolution direct imaging solution to date. With 8.9 million pixels, sub-micron resolution capabilities and a data rate of 110 gigapixels per second, the device eliminates the need for expensive mask technology while delivering the scalability, cost-effectiveness and precision needed for increasingly complex packaging.

Why it matters

Maskless digital lithography machines – which project light for etching circuit designs on materials without a photomask or high-end stencil – are becoming increasingly popular for the manufacturing of advanced packaging. Advanced packaging combines multiple chips and technologies into a single package, enabling high-computing applications, such as data centers and 5G, to have systems that are smaller, faster, and more power-efficient.

With TI DLP technology, system assembly equipment manufacturers can leverage maskless digital lithography to achieve the high-resolution printing at scale necessary for advanced packaging. The new DLP991UUV acts as a programmable photomask, offering precise pixel control with reliable high-speed performance.

“Just as we redefined cinema by enabling the transition from film to digital projection, TI’s DLP technology is once again at the forefront of a major industry shift,” said Jeff Marsh, vice president and general manager of DLP technology at TI. “We’re enabling the creation of maskless digital lithography systems that empower engineers around the world to breakthrough the current limits of advanced packaging and bring powerful computing solutions to market.”

The post TI DLP technology delivers high-precision digital lithography for advanced packaging appeared first on ELE Times.

Synopsys recently announced expanded generative AI capabilities through offerings such as Ansys Engineering Copilot and AgentEngineer technology.

Nuburu Inc of Centennial, CO, USA — which was founded in 2015 and developed and previously manufactured high-power industrial blue lasers — has announced a quarterly update on its business performance, strategic initiatives, and outlook for the upcoming period...

КПІ ім. Ігоря Сікорського та ФРУ Дефенс готуватимуть менеджерів для оборонно-промислового комплексу України kpi вт, 09/30/2025 - 22:09

I was inspired by the recent post from u/MaxwellHoot regarding a local parts inventory system. I did indeed end up using one of my old Palm devices, the SPT1800 to be exact. It has a built in laser/barcode scanner just for this purpose. While it can't do QR codes, the barcodes work just fine. Using abandonware - the "CatScan" Palm app, "J-Pilot" Linux app, and a custom script to turn the database into an HTML file, I now can scan all my mouser bags and inventory items rather quickly. The webserver is read-only, but still useful. It might be fun to develop everything into a kiosk, but I don't have time right now. submitted by /u/vtfrotex [link] [comments]

Today, the FPGA company revealed an array of new announcements at its annual Altera Innovators Day developer conference.

One of my electronics interests is building radios, particularly those featured in older UK electronics magazines such as Practical Wireless, Everyday Electronics, Radio Constructor, and The Maplin Magazine. Most of those radios are designed to run on a 9-V disposable PP3 battery.

Wow the engineering world with your unique design: Design Ideas Submission Guide

Using 9 V instead of the 3 V found in many domestic radios allows the transistors in these often-simple circuits to operate with a higher gain. PP3 batteries are, at a minimum, expensive in circuits consuming tens of mA and are—I suspect—hard to recycle. A more environmentally friendly solution was needed.

In the past, I’ve used single 3.6-V lithium-ion (Li-ion) cells from discarded e-cigarettes [1] with cheap combined charger and DC-DC converter modules found on eBay. They provide a nice, neat solution when housed in a small plastic box, but unfortunately generate a lot of electromagnetic interference (EMI), which falls within the shortwave band of frequencies (3 to 30 MHz) where a lot of the radios I build operate. I needed another solution that was EMI-free and environmentally friendly.

Solution

One solution is to eliminate the DC-DC converter and string together three or more Li-ion cells in a battery pack (B1) with a variable linear regulator (IC1) to generate the required 9 V (V1) as shown in Figure 1. Li-ion cells, like all electronic components, have tolerances. The two most important parameters are cell capacity and open circuit voltage. Differences in these parameters between cells in series lead to uneven charging and ultimately stressing of some cells, leading to their eventual degradation [2]. To even out these differences, Li-ion battery packs often contain a battery management system (BMS) to ensure that cells charge evenly.

Figure 1 Li-ion battery pack, with 3 or more Li-ion cells, and a variable linear regulator to generate the required 9 V.

As luck would have it, on the local buy-nothing group in Ottawa, Canada, where I live, someone was giving away a Mastercraft 18-V Li-ion battery with charger as shown in Figure 2. The person offering it had misplaced the drill, so there was little expense for me. Upon opening the battery pack, it was indeed found to contain a battery management system (BMS). This seemed like an ideal solution.

Figure 2 The Mastercraft 18-V Li-ion battery and charger obtained locally.

Circuit

The next step was to make a linear voltage regulator to drop 18 V to 9 V. This, in itself, is not particularly environmentally friendly, as it is only 50% efficient, and any dropped battery voltage will be dissipating as heat. However, assuming renewable power generation is used as the source, this would prove a more environmentally friendly solution compared to using disposable batteries.

In one of my boxes of old projects, I found a constant current nickel-cadmium (NiCad) battery charger. It was based around an LM317 linear voltage regulator in a nice black plastic enclosure sold by Maplin Electronics as a “power supply” box. The NiCad battery hadn’t been used for over 20 years, so this project would be a repurpose. A schematic of the rewired power supply is shown in Figure 3.

Figure 3 The power supply schematic with four selectable output voltages—6, 9, 12, and 13.8 V.

In Figure 3, switch S1 functions as both the power switch and selects the output voltage. Four different output voltages are selectable based on current needs: 6 V, 9 V, 12 V, and 13.8 V can be chosen by adjusting the ratio of R2 and R3-R6 as shown in the LM317 datasheet [3]. R2 is usually 220 Ω and develops 1.23 V across it, the remaining output voltage is developed across R3-R6. To get the exact values, parallel combinations are used as shown in Table 1.

Resistor #	Resistors (Ω)	Combined Value (Ω)
3	910, 18k, 15k	819
4	1.5k, 22k, 33k	1.35k
5	2.2k, 15k	1.92k
6	2.2k	2.2k

Table 1 Different values of paralleled R3 to R6 resistors and their combined value.

A photograph of the finished power supply with a Li-ion battery attached is shown in Figure 4.

Figure 4 A photograph of the finished power supply with four selectable output voltages that can be adjusted via a knob.

Results

Crimp-type spade connectors were fitted to the two input wires, which mated well with the terminals of the Li-ion battery. Maybe at some point, I will 3D-print a full connector for the battery. With the resistor values shown in Figure 3, the actual output voltages produced are: 5.96 V, 9.03 V, 12.15 V and 13.8 V. While these are not the actual designed values due to the use of preferred resistor values, it is of little consequence as the output voltage of disposable batteries varies over their operating time and there is of course a voltage drop due to cables. With this power supply, though, the output voltage of the power supply will remain constant during this time, even as the output voltage of the Li-ion drops due to its discharging.

Portable power

Although the power supply was intended for powering radio projects, it has other uses where portable power is needed and a DC-DC converter is too noisy, like sensitive instrumentation or some audiophile preamplifier [4]. 

Gavin Watkins is the founder of GapRF, a producer of online EDA tools focusing on the RF supply chain. When not doing that, he is happiest noodling around in his lab, working on audio electronics and RF projects, and restoring vintage equipment.

Related Content

• Drive any electronic clock with a high-precision 10-MHz reference
• Analogue charge pump produces high-frequency, high-voltage pulses
• Investigating a vape device
• Double Lithium-Ion/Lithium-Polymer USB Type-C Charger
• Low Cost Universal Battery Charger Schematic

References

1. Reusing e-cigarette batteries in a e-bike, https://globalnews.ca/news/10883760/powering-e-bike-disposable-vapes/
2. BU-808: How to Prolong Lithium-based Batteries, https://batteryuniversity.com/article/bu-808-how-to-prolong-lithium-based-batteries
3. LM317 regulator datasheet, https://www.ti.com/lit/ds/symlink/lm317.pdf
4. Battery powered hifi preamp, https://10audio.com/dodd_battery_pre/

The post An off-line power supply appeared first on EDN.

Welcome to the first All About Circuits Summit Day of 2025! This guide will introduce the features of our first Wednesday schedule and help you plan your month-long participation.

Anritsu Corporation will participate in the upcoming India Mobile Congress (IMC) 2025, taking place in New Delhi, India, from October 8 to October 11, to showcase its latest innovations in communications test and measurement solutions.

As the mobile and connectivity industry continues to expand with the rapid adoption of 5G, IoT, and emerging technologies such as AI-driven services, cloud computing, and immersive XR applications, the demand for robust, reliable, and efficient test solutions has never been greater. At IMC 2025, Anritsu will highlight its comprehensive portfolio designed to meet these evolving needs, supporting operators, device manufacturers, and ecosystem partners in accelerating their technology development and deployments.

Virtual Signalling Tester

5G Network Simulator, a software-based solution for 5G IoT chipset and device testing. It enables virtual 5G network simulation on a PC, supporting RedCap tests and efficient device verification.

Radio Communication Test Station MT8000A

All-in-One Support for RF Measurements, Protocol Tests and Applications Tests in FR1 (to 7.125 GHz) and FR2 (Millimeter-Wave) Bands. MT8000A is used by Mobile Chipset, Mobile Handset, IoT Device, 5G base Station R&D and manufacturing companies.

Field Master Pro MS2090A

Handheld Spectrum Analyzer delivers the highest continuous frequency coverage up to 54 GHz and real-time spectrum analysis bandwidth up to 150 MHz to address current and emerging applications such as 5G &LTE Base Station Measurement, Satellite System Monitoring, Interference Hunting, EMF measurement and much more.

Anritsu Collaborates with Altair to Demonstrate Integration of Anritsu Monitoring Systems with Spectrum Management Software WRAP.

Altair WRAP integrates georeferenced data from Anritsu spectrum analyzers to validate coverage, interference, and spectrum compliance with field reality.

VectorStar Broadband VNA ME7838

The VectorStar ME7838 Series broadband VNA offers the widest available 2-port single frequency sweep from 70 kHz to 110, 125, 145, and 220 GHz with mmWave bands up to 1.1 THz. Vector Star is a cost-effective solution for OnWafer Measurements, RIS, Novel Channel Sounding applications along with active and passive devices measurement supporting 5G and 6G technology.

Optical Spectrum Analyzer MS9740B

MS9740B offers Single mode and Multimode Fiber application and high-speed optical devices such as optical transceivers, VCSEL, and DFB light sources testing R&D and production.

The post Anritsu Showcases 6G and NTN Test Solutions at IMC 2025 appeared first on ELE Times.