This letter studies a joint design of transmit beamforming and fronthaul compression for the uplink cloud radio access network (C-RAN) with intelligent reflecting surface (IRS) aided wireless fronthauling. In C-RAN, a number of users communicate with baseband unit (BBU) pool through multiple remote radio heads (RRH), wherein RRHs compress the received signals by Wyner-Ziv (WZ) coding and forward the quantization bits to BBU pool through wireless fronthaul link. With the goal of maximizing the uplink sum rate, an alternating algorithm is proposed for jointly optimizing the fronthaul quantization noise covariance matrices, the passive beamformer of IRS and the transmit beamformers of users and RRHs. Via numerical results, the effectiveness of the proposed joint design is verified.

中文翻译：

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具有智能反射表面增强无线前传的上行 C-RAN 前传压缩和波束成形优化

这封信研究了具有智能反射面 (IRS) 辅助无线前传的上行链路云无线接入网 (C-RAN) 的传输波束成形和前传压缩的联合设计。在 C-RAN 中，多个用户通过多个远程射频头 (RRH) 与基带单元 (BBU) 池通信，其中 RRH 通过 Wyner-Ziv (WZ) 编码压缩接收到的信号，并通过无线将量化比特转发到 BBU 池前传链路。以最大化上行总速率为目标，提出了一种交替算法，用于联合优化前传量化噪声协方差矩阵、IRS的无源波束形成器以及用户和RRH的发射波束形成器。通过数值结果，验证了所提出的联合设计的有效性。