Keysight Technologies (United Kingdom)

<div class="section abstract"><div class="htmlview paragraph">The Automotive industry widely uses cast iron due to its better mechanical performance and cost-effectiveness. However, repair welding or assembly of cast iron components remain highly challenging due to the material’s high carbon content, inherent brittleness, rapid thermal conductivity, and complex microstructural transformations. Multi-pass welding exacerbates these challenges by subjecting materials to repeated thermal cycling, accumulating residual stress, and inducing distortion – all of which potentially degrade the integrity of welded joints. A comprehensive understanding of welded joint behavior is essential to effectively mitigate these effects. Finite element analysis (FEA) serves as a powerful tool, enabling accurate prediction of thermal profiles, phase transformations, residual stress development, and resulting deformations. These valuable insights are critical for optimizing welding processes and enhancing overall joint quality.</div><div class="htmlview paragraph">This study investigates and validates the use of FEA-based simulation tools for multi-pass MIG welding of ductile cast iron plates, highlighting the effectiveness of virtual modeling in complex welding scenarios. A numerical simulation of 20 mm thick cast iron plates welded with Ni-Fe filler wire was conducted using SYSWELD software. The distortion, temperature distribution, microstructure, hardness, and residual stresses of the weld coupon were predicted using a thermo-metallurgical-mechanical model. The simulation incorporated a double-elliptical heat source for welding and an imposed thermal cycle model for pre- and post-weld heat treatments. Metallurgical analysis was performed utilizing a phase transformation model and Continuous Cooling Transformation diagram to estimate microstructural phase fractions and hardness. The mechanical analysis, based on the thermo-metallurgical profile and boundary conditions, evaluated weld distortion and residual stresses on weld coupon. Predicted results, including thermal cycles, fusion zone, distortion, hardness, and residual stresses, were validated against experimental data showed strong coherence.</div><div class="htmlview paragraph">This study demonstrates the efficacy of FEA tools in accurately predicting dissimilar weld properties, reinforcing their reliability for welding and repairing cast iron components in industrial applications.</div></div>

We demonstrate 200 GBaud OOK, transmitter using a 1064 nm lithium niobate Mach-Zehnder modulator (MZM). We achieve performance below 6.25 % overhead HDFEC threshold and study different equalization configurations.

The emergence of cloud-native architectures and Open RAN (O-RAN) principles has revolutionized the deployment and scalability of mobile network infrastructure. However, the energy efficiency of Virtualized Network Functions (VNFs) operating in such environments remains a critical concern, particularly as 5G and 6G networks scale in complexity and resource demands. This study introduces a modular and reproducible testbed for high-fidelity energy profiling of containerized monolithic srsRAN-based gNB implementations running on Commercial Off-The-Shelf (COTS) server-class hardware. The testbed integrates a commercial-grade Power Analyzer (PA) and a full-stack network emulation framework to measure the impact of key parameters, including CPU frequency and core allocation, on the power consumption of a virtualized gNB. A comprehensive configuration dataset is collected across both high-load and low-load scenarios. The results reveal that CPU frequency throttling consistently reduces energy consumption beyond specific performance thresholds, while core limitation is effective only in low-load scenarios; however, it enables VNF co-location, which contributes to reducing overall infrastructure-level energy consumption. These findings validate the applicability of dynamic energy optimization strategies and provide actionable insights for orchestration frameworks aiming to balance energy efficiency with Quality of Service (QoS) requirements. The emergence of cloud-native architectures and Open RAN (O-RAN) principles has revolutionized the deployment and scalability of mobile network infrastructure. However, the energy efficiency of Virtualized Network Functions (VNFs) operating in such environments remains a critical concern, particularly as 5G and 6G networks scale in complexity and resource demands. This study introduces a modular and reproducible testbed for high-fidelity energy profiling of containerized monolithic srsRAN-based gNB implementations running on Commercial Off-The-Shelf (COTS) server-class hardware. The testbed integrates a commercial-grade Power Analyzer (PA) and a full-stack network emulation framework to measure the impact of key parameters, including CPU frequency and core allocation, on the power consumption of a virtualized gNB. A comprehensive configuration dataset is collected across both high-load and low-load scenarios. The results reveal that CPU frequency throttling consistently reduces energy consumption beyond specific performance thresholds, while core limitation is effective only in low-load scenarios; however, it enables VNF co-location, which contributes to reducing overall infrastructure-level energy consumption. These findings validate the applicability of dynamic energy optimization strategies and provide actionable insights for orchestration frameworks aiming to balance energy efficiency with Quality of Service (QoS) requirements.

This paper introduces activities of AI and Digital Twin working group (AI-DT WG) in XGMF 6G Radio Technology Project. Especially in the fiscal year 2024, AI-DT WG has been engaged in activities for getting the beyond 5G white paper "AI/ML and Digital Twin Technologies" ready for the world. The AI-DT WG also launched the discussion for establishing a shared dataset for AI training. This paper provides an overview of the white paper and the status of the discussion for shared dataset establishment.

ABSTRACTThe artificial neural networks (ANN) models have been proven to accurately describe the device's electrical behaviors. However, considering the importance of device physics, the physical‐based SPICE models are still the golden standard in the industry. This paper investigates two directions of ANN‐assisted SPICE modeling solutions. A scalable inductor model demonstrates the use of ANN to extract the scaling equation, and the hybrid model showcases the ANN enhancement on top of the physical SPICE model. The results show the potential feasibility and practicality of the ANN modeling approach to improve the SPICE model extraction process in speed and accuracy.

ABSTRACT This letter presents a novel stripline resonator (SR) that can be used for high‐frequency characterization of dielectric substrates, which is excited at the center of the upper and lower metal grounds by using coaxial probes. The proposed resonator is studied using simulation software as well as experiments. The main advantages of the improved stripline resonator are that it makes coupling tuning more efficient and easier, allows fast and accurate testing of different materials without prior consideration of impedance or size matching, and reduces the influence of edge effects of conventional coupling structures. This resonator is used to measure two well‐known commercial substrates in the frequency range from 2 to 27 GHz, and the results are in good agreement with the reference data, suggesting that the proposed methods can perform broadband and high‐accuracy measurements of the complex permittivity for the substrates.

This paper presents a comparative analysis of onwafer noise figure (NF) measurements at D-band <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(110-170 \text{GHz})$</tex> and G -band <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(140-220 \text{GHz})$</tex> frequencies using cold-source and Y-factor methods. A broadband distributed amplifier fabricated in an advanced BiCMOS process is used as the device under test. The measurement setups employ automated source tuners, bandspecific calibration components, and vector network analyzerbased gain extraction to improve accuracy. Results highlight notable discrepancies in NF and gain measurements across bands, attributed primarily to variations in calibration and gain estimation. The study provides insight into the sensitivity of sub-THz NF metrology to hardware non-idealities, and proposes techniques to mitigate these challenges, with implications for the design and evaluation of future 6 G systems.

The flexibility inherent to the 6G space through its use of virtualized/Service Based Architecture (SBA) networks means that generated performance results can be more difficult to contextualize than previous generations. In this space, experimentation, either with the purpose of evaluating the appropriate integration of a new network device, system or software or targeting the assurance of application-demanding performance service levels, needs to be done in such a way to ensure that the assessment is performed uninfluenced by the actual dimensioning constraints of the underlying beyond 5G (B5G)/6G experimentation platform. This paper explores the development of an Adaptive Calibration methodology, which can be used to provide context to results in the 6G space so that to ensure platform agnosticism. Exemplary results of its application in the 6G-SANDBOX project, exploiting four (4) different and geographically dispersed experimentation platforms, are presented hereby. The methodology involves the establishment of a baseline environment which can be measured before the introduction of a device/system/software under test (SUT). The results of the baseline measurement can be compared to the results including the SUT to produce deltas in multiple KPIs. These deltas can then be used to provide context to results generated within a single platform or be used to compare multiple platforms. The use of this methodology within 6G-SANDBOX uncovered significant performance disparities between the partaking platforms related to virtualization methods, and it is currently being used to drive the platforms closer to parity, investigate the virtualization issues and quantify the performance of various components within each individual platform. In this regard, the application of the proposed methodology is proven substantial to increase confidence in the SUT assessment results performed over B5G/6G experimentation platforms.

With the rapid development and commercialization of fifth-generation (5G) technology, calibration and RF testing using over-the-air (OTA) is becoming increasingly important. Due to the large size of the massive multiple-input and multiple-output (MIMO) base station (BS), it is very challenging to fulfill direct far-field (DFF) conditions in OTA tests. Conventional near-field (NF) testing methods suffer from long measurement times due to the stringent sampling requirements (e.g., NF to far-field (FF) transformation) or the requirement for expensive test equipment [e.g., compact antenna test range (CATR)]. In this article, we propose a simplified extrapolation technique (ET) strategy to reconstruct the FF radiation pattern based on mid-field (MF) phaseless measurements, with high measurement efficiency. The traditional ET uses polynomials with many terms to fit the radiated power of an arbitrary antenna at the radial direction, while the simplified ET only uses a few terms to fit the power variation in the MF, taking into account the structure and element excitation characteristics of common arrays such as BSs. The relationship between the element excitation mode and the coefficients of each fitted term is determined by detailed theoretical derivations. Then, the best-fitting polynomials are determined for different excitation modes. The antenna pattern of the BS is successfully reconstructed in an anechoic chamber by power measurements at two or three different distances of less than one-fourth of the FF distance. The robustness and effectiveness of the proposed method are experimentally verified by comparing the accuracy of the antenna pattern reconstruction with different fitting polynomials in the anechoic chamber for a practical BS antenna.