Project description
Preparing for the 6G-Era Vehicle-to-Everything Communications
Advanced wireless communication beyond 5G and 6G comes with critical challenges. With reconfigurable intelligent surfaces (RIS), cell-free massive multiple-input multiple-output (mMIMO), and vehicle-to-everything (V2X) technologies, it is necessary to revolutionise connectivity. With the support of the Marie Skłodowska-Curie Actions programme, the VeXaRIS project will use RIS and cell-free mMIMO to optimise spectral/energy efficiency for V2X communications, eliminating handover issues and reducing power consumption. Active RIS enhances signal quality but demands careful power management. VeXaRIS will pioneer closed-form solutions for efficient V2X-enabled mMIMO, balancing signal quality and energy consumption. Additionally, a federated learning approach will combat channel ageing effects, ensuring sustained performance in dynamic environments. VeXaRIS stands at the frontier of future wireless innovation.
Objective
The reconfigurable intelligent surfaces (RIS), cell-free (CF) massive multiple-input multiple-output (mMIMO), and vehicle-to-everything (V2X) are key technologies for next-generation wireless communication, i.e. beyond 5G and 6G. The CF mMIMO involves deploying many APs in a large geographical area to jointly serve all users. V2X allows vehicle user equipment (VUEs) to communicate with base stations, pedestrians, and other vehicles. The high mobility of VUEs leads to frequent handovers and channel ageing. This makes the CF mMIMO ideal for V2X since handovers are eliminated. To reduce the impact of channel ageing, more APs must be deployed which increases the power consumption. The RIS comprises many passive reflecting elements (REs), which can independently induce phase and amplitude change, with marginal power needs. Thus, the RIS can improve the spectral/energy efficiency (SE/EE). However, the passive RIS suffers from double-fading attenuation which may be detrimental for VUEs.
This proposal seeks to analyze the SE/EE of the active RIS (aRIS)-aided CF mMIMO enabled for V2X. Each AP serves VUEs with the aid of multiple aRISs. We will derive closed-form solutions for the uplink/downlink SE by assuming imperfect channel state information, spatially correlated Rician channels, and channel ageing. For the aRIS, while increasing the reflected signal amplitude improves the desired signal, it also enhances the noise. Also, the aRIS requires extra power to amplify the signal which grows the network power consumption. The tradeoff between the SE and EE will be analyzed to identify the best operating regions. Increasing the APs (or VUEs) transmit power may increase the SE but saturates at a point due to interference. Therefore, we seek to jointly optimize the power, aRIS amplitude and phase with the objectives of (1) maximizing the sum SE (2) maximizing the EE. Finally, we propose a federated learning algorithm for CSI forecasting to mitigate channel ageing effects.
Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
91120 Palaiseau
France