Weighted-Sum-Rate Maximization for an Reconfigurable Intelligent Surface Aided Vehicular Network

Abstract

Recently, reconfigurable intelligent surfaces (RISs) have been identified as one potential solution to avoid performance degradation of using millimeter wave (mmWave) frequencies in vehicular communications. In this paper, we investigate the use of an RIS in a mmWave vehicular communication network. The problem of weighted sum-rate maximization in the uplink is considered, where an RIS is used to assist the communication. We focus on both single-user and multi-user cases. Single user case is solved using successive refinement algorithm, where two phase-optimization schemes that help reducing the channel estimation overhead are considered. In multi-user case, fractional programming technique is used to reformulate the original problem into a more convenient form, and an algorithm based on alternating optimization is proposed. The validity of the proposed methods is confirmed by numerical simulations. A significant performance increase is seen when utilizing an RIS in both cases. Considered phase optimization schemes are shown to result in a significant reduction in channel estimation at a cost of small performance degradation compared to the full channel state information beamforming scenario. We perform simulations to investigate the effects of mobility, and the results demonstrate the ability of an RIS to mitigate the effects of mobility to some extent. Furthermore, to get practical insights into vehicular communications aided by an RIS, we use a commercial ray-tracing tool to evaluate the performance.

Keywords

• Alternating optimization
• fractional programming
• mmWave communications
• passive beamforming
• ray tracing
• reconfigurable intelligent surfaces