New Coding Method Slashes Data Overhead for Smart Wireless Mirrors

<p>Reconfigurable intelligent surfaces (RISs) can greatly improve the signal quality of future communication systems by reflecting transmitted signals toward the receiver. However, even when the base station (BS) has perfect channel knowledge and can compute the optimal RIS phase-shift configuration, implementing this configuration requires feedback signaling over a control channel from the BS to the RIS. This feedback must be kept minimal, as it is transmitted wirelessly every time the channel changes. In this paper, we examine how the feedback load, measured in bits, affects the performance of an RIS-aided system. Specifically, we investigate the trade-offs between codebook-based and element-wise feedback schemes, and how these influence the achievable signal-to-noise ratio (SNR). We propose a novel quantization codebook, tailored for line-of-sight scenarios, that guarantees minimal SNR loss while reducing feedback overhead from linear to logarithmic scaling with the number of RIS elements. We demonstrate the codebook’s usefulness over Rician fading channels and extend it to 3D channel geometries with a uniform planar array through joint quantization of elevation and azimuth angles, including scenarios with a non-zero static path. Furthermore, we also analyze the SNR impact of discrete phase shifts and implement an efficient differential feedback scheme that leverages temporal correlation for mobility scenarios. Numerical simulations and analytical analysis are performed to quantify the performance degradation caused by reduced feedback load, shedding light on how efficiently RIS configurations can be fed back in practical systems.</p>