Efficient V2I Communication via IRS-Enhanced MIMO Backscatter with Non-Linear Detection

This paper investigates an Intelligent Reflecting Surface (IRS)-enhanced vehicle-to-infrastructure (V2I) multiple input multiple output (MIMO) backscatter communication network. In this network, multiple IRSs send roadside information to a multi-antenna reader using the backscatter technique, while the inevitable self-interference at the reader is taken into account. To maximize the introduced system’s weighted sum rate, we propose an optimization scheme based on minimum mean square error with successive interference cancellation (MMSE-SIC). This scheme jointly optimizes the reader’s detection matrix, beamforming vector, and IRS reflection coefficients. The formulated non-convex problem is tackled using a block coordinate descent (BCD) algorithm combined with successive convex approximation (SCA) and semi-definite relaxation (SDR) methods. The proposed framework is compared with other schemes including the linear detection technique, highlighting the trade-off between performance and computational complexity. The study provides insights into the impact of key parameters, such as the reader’s transmit power and the number of IRS elements, on system performance. Furthermore, our findings lay the groundwork for future exploration of more effective transmission approaches in IRS-enhanced V2I backscatter communication networks.