Greenerwave (France)

Wireless local area networks (WLAN) and recent Wi-Fi standards, are used since a few decades for a large variety of network applications. Since a few years, the $5^{\text {th }}$ generation wireless cellular networks (5 G) are being deployed and used, most of the time for similar applications. Both technologies and their evolution, are expected to be deployed within the wireless ecosystem by 2030 and for decades beyond. The Wi-FIP project invokes these two wireless networking solutions and their evolution, to further enhance the wireless data networks regarding sustainable and scalable quality of hybrid network services. This paper presents the visions and objectives of the Wi-FIP project, targeting to enhance synergies and integration of Wi-Fi in 5G/beyond 5G networks, through the convergent B2B/B2C usage model concept, sustainable multi-connectivity, hierarchical Software Defined Networking (SDN) and orchestration. The paper analyzes the functionalities to develop for sustainable, secure and hybrid WLAN/cellular networking.

Recently, a new working item has been identified in pre-standardization activities (at ETSI) on reconfigurable intelligent surfaces (RIS) as a preparation for the the 3GPP 6G standardization. Among other topics, over-the-air (OTA) measurements are a common tool used to characterize the RIS. In this paper, we therefore propose OTA measurement techniques to evaluate RIS performance metrics and its compliance with 3GPP specifications through test and measurement (T&M) setups and equipments. These measurements are confirmed through extensive simulation results. The findings presented in this paper highlight the importance of OTA RIS measurements and show the impact of RIS technology on signal quality and network coverage, paving the way for the integration of this technology into next-generation wireless communication systems.

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The design of a dual-band dual-polarized chokering horn antenna for Low Earth Orbit (LEO) Telemetry, Tracking and Control (TT&C) satellite applications in Ka-band is reported here. The antenna comprises an input circular waveguide as the primary feed where two topologies are explored with quad- and hexa-ridged cross-sections. The optimization has been performed using commercially available software. The obtained simulation results of the latter solution indicate a significant improvement on the RF performance. A preliminary design of the proposed dual-band dual-polarized excitation network is also presented and discussed. The detailed design of the complete antenna is on-going in the frame of an ESA funded activity and preliminary results will be presented during the conference.

This publisher's note contains corrections to Opt. Lett.48, 3275 (2023)10.1364/OL.491711.

Massive access for the Internet of Things (IoT) is a hot research topic for current and future systems, such as 6G. The main contribution of this paper is the design and evaluation of a novel set of waveforms, called Golden Modulation (GM), which departs conceptually from linear frequency modulated signals, e.g., as used in LoRa, and allows a huge increase in the number of parallel channels, compared to the state of the art mentioned above. The basic modulation principles relying on spectrum spreading via direct Zadoff-Chu sequence modulation are presented. The multiuser interference level is evaluated and shown to be small, even under uncoordinated conditions. Overall, GM paves the way for the deployment of Low Power Wide Area Networks with truly massive capacity, or for the upgrade of existing ones.

This paper presents an example of antenna diagnosis using a measurement device based on infrared thermography. Infrared thermography measurements allow to obtain, in less than one minute, a high resolution near field mapping of the electric field radiated by the antenna under test. In this study, such measurements are performed on an X-band telemetry antenna and allow to quickly identify manufacturing defects by comparing the measurements with numerical results.

The rise of small satellites constellations, the multiplication of radiofrequency (RF) links for payloads and platforms and the generalization of electric propulsion involve new antenna positioning and radiofrequency compatibility (RFC) issues for satellite manufacturers. We propose in this paper to focus on methodologies for assessing satellite structure and plasma plume impact on antenna radiation patterns, and also radiofrequency decoupling at satellite level.

Plasma-based microwave power limitation in a suspended microstrip transmission line integrating a micro hollow cathode discharge (MHCD) in its centre is experimentally and numerically studied. Transient and steady state microwave power measurements exhibit a limitation threshold of 28 dBm and time responses of 25 microseconds. Intensified charge-coupled device imaging shows that microwave breakdown occurs at the top of the MHCD. The plasma then extends towards the microwave source within the suspended microstrip transmission line. Besides, a self-consistent model is proposed to simulate the non-linear interaction between microwave and plasma. It gives numerical results in agreement with the measurements, and show that the plasma expansion during the transient response is related to a shift between the ionization source term and the electron density maximum. The propagation speed, under the tested conditions, depends mainly on the stepwise ionization from the excited states.

The Internet-of-Things (IoT) requires endnodes with ultra-low-power always-on capability for a long battery lifetime, as well as high performance, energy efficiency, and extreme flexibility to deal with complex and fast-evolving near-sensor analytics algorithms (NSAAs). We present Vega, an IoT endnode system on chip (SoC) capable of scaling from a 1.7- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> fully retentive cognitive sleep mode up to 32.2-GOPS (at 49.4 mW) peak performance on NSAAs, including mobile deep neural network (DNN) inference, exploiting 1.6 MB of state-retentive SRAM, and 4 MB of non-volatile magnetoresistive random access memory (MRAM). To meet the performance and flexibility requirements of NSAAs, the SoC features ten RISC-V cores: one core for SoC and IO management and a nine-core cluster supporting multi-precision single instruction multiple data (SIMD) integer and floating-point (FP) computation. Vega achieves the state-of-the-art (SoA)-leading efficiency of 615 GOPS/W on 8-bit INT computation (boosted to 1.3 TOPS/W for 8-bit DNN inference with hardware acceleration). On FP computation, it achieves the SoA-leading efficiency of 79 and 129 GFLOPS/W on 32- and 16-bit FP, respectively. Two programmable machine learning (ML) accelerators boost energy efficiency in cognitive sleep and active states.