A Novel Precoding Matrix Quantization Approach for Radio Stripe Architecture of Cell-free Massive MIMO Communication Systems

The radio stripe (RS) is an emerging architecture for cell-free massive multiple-input-multiple-output (CFm-MIMO) communication systems, where access points (APs) are sequentially connected via one optical-fiber link. The traditional precoded signal vector quantization approach is designed for star-topology MIMO architecture with a large demand for fronthaul capacity thereby it is not suitable for RS architecture. To address this challenge, a joint precoding matrix optimization and pruning approach is proposed to reduce the fronthaul traffic in the RS architecture. Central to our strategy is optimizing and pruning the precoding coefficient matrix (PCM), which is decomposed from the stationary point of the weighted sum-rate maximization problem. An iterative algorithm with closed-form iteration expression is developed for the joint optimization and pruning of PCMs. Note that the size of PCM only depends on the number of data streams rather than the antenna number. In contrast to transmitting different precoding matrices to different APs, the required PCMs for different APs are proved to be the same, which illustrates that only one PCM needs to be transmitted in the RS. Simulation results demonstrate that the proposed approach can reduce the fronthaul link traffic by 739% compared to the weighted minimum mean square error (WMMSE) precoding algorithm. When each signal symbol is quantized with 10 bits, the proposed approach can improve the sum-rate by 284% and 544% compared to the zero-forcing and maximum ratio transmission algorithms, respectively.