Resource Allocation and Beamforming Optimization for IRS-Assisted OFDMA Uplink in C-RAN

This letter studies the resource allocation and passive beamforming for the cloud radio access network (C-RAN) with orthogonal frequency division multiple access (OFDMA) assisted by intelligent reflecting surface (IRS). Specifically, we consider the uplink transmission where remote radio heads (RRHs) quantize the received signals from the users by independent point-to-point compression and transmit the quantization bits to the baseband unit (BBU) pool through capacity-limited fronthaul links. We jointly optimize the resource allocation and passive beamforming to maximize the uplink sum-rate, using alternating approach and successive convex approximation (SCA) technique. Numerical results verify the performance gain brought by IRS and validate the effectiveness of the proposed algorithm.