Joint interference mitigation and data recovery in C-RAN with distributed fronthaul compression

Abstract

We consider joint interference mitigation and data recovery in the uplink of cloud radio access networks (C-RANs). Specifically, the remote radio headers (RRHs) first employ a distributed fronthaul compression scheme to compress the received signal before transmitting it to the baseband processing units (BBUs) so that the limited fronthaul capacity constraint can be satisfied. Then BBUs recover the desired data based on the compressed received signals collected from the RRHs using an alternating optimization (AO) based CS recovery algorithm. By exploiting the individual sparse structure of the information and interference, the AO algorithm is able to achieve enhanced interference mitigation and data recovery performance even with compressed received signals. For performance analysis, we introduce a new restricted isometry property (RIP) called the ISLs-RIP and show that the normalized C-RAN measurement matrix satisfies the ISLs-RIP. Based on the ISLs-RIP, we establish the convergence conditions for the AO algorithm. Finally, we analyze the MSE satisfaction probability for the C-RAN.