Near-optimal Reconfigurable Intelligent Surface Configuration: Blind Beamforming with Sensing

Blind beamforming has emerged as a promising approach to configure reconfigurable intelligent surfaces (RISs) without relying on channel state information (CSI) or geometric models, making it directly compatible with commodity hardware. In this paper, we propose a new blind beamforming algorithm, so-called Blind Optimal RIS Beamforming with Sensing (\textsc{BORN}), that operates using only received signal strength (RSS). In contrast to existing methods that rely on majority-voting mechanisms, \textsc{BORN} exploits the intrinsic quadratic structure of the received signal-to-noise ratio (SNR). The algorithm proceeds in two stages: \emph{sensing}, where a quadratic model is estimated from RSS measurements, and \emph{optimization}, where the RIS configuration is obtained using the estimated quadratic model. Our novelties are twofold. Firstly, we show for the first time, that \textsc{BORN} can achieve provable near-optimal performance using only $O(N \log_2(N))$ samples, where $N$ is the number of RIS elements. As a by-product of our analysis, we show that quadratic models are learnable under Rademacher feature distributions when the second-order coefficient matrix is low-rank. This result, to our knowledge, has not been established in prior matrix sensing literature. Secondly, extensive simulations and real-world field tests demonstrate that \textsc{BORN} achieves near-optimal performance, substantially outperforming state-of-the-art blind beamforming algorithms, particularly in scenarios with a weak background channel such as non-line-of-sight (NLOS).

Optimising Communication Control Factors for Energy Consumption in Rural LOS V2X

Connected braking can reduce fatal collisions in connected and autonomous vehicles (CAVs) by using reliable, low-latency 5G New Radio (NR) links, especially NR Sidelink Vehicle-to-Everything (V2X). In rural areas, road side units are sparse and power-constrained or off-grid, so energy efficiency must be considered alongside safety. This paper studies how three communication control factors including subcarrier spacing ($\mathrm{SCS}$), modulation and coding scheme ($\mathrm{MCS}$), and transmit power ($P_{\mathrm{t}}$) should be configured to balance safety and energy consumption in rural line-of-sight (LOS) scenarios in light and heavy traffic scenarios. Safety is quantified by the packet receive ratio ($\mathrm{PRR}$) against the minimum communication distance $D_{\mathrm{comm}}$, defined as the distance that the vehicle travels during the transmission of the safety message. Results show that, under heavy traffic, increasing $P_{\mathrm{t}}$ and selecting a low-rate $\mathrm{MCS}$ at $\mathrm{SCS} = 30$ kHz sustains high $\mathrm{PRR}$ at $D_{\mathrm{comm}}$, albeit with higher energy cost. In light traffic, maintaining lower $P_\mathrm{t}$ with low $\mathrm{MCS}$ levels achieves a favorable reliability-energy trade-off while preserving acceptable $\mathrm{PRR}$ at $D_{\mathrm{comm}}$. These findings demonstrate the necessity of adaptive, energy-aware strategy to guarantee both safety and energy efficiency in rural V2X systems.