智能反射面辅助OFDMA云接入网的资源分配方法

Resource Allocation for Intelligent Reflecting Surface Assisted OFDMA C-RAN

本文研究了智能反射面(IRS)辅助OFDMA(Orthogonal Frequency Division Multiple Access,正交频分多址接入)云无线接入网(C-RAN)的下行链路传输系统,其中基带处理单元(BBU)池通过多个远端射频头(RRH)与多个用户进行通信.RRH到用户的接入链路采用OFDMA接入技术.对于BBU池到RRH,采用无线前传链路,并且部署多个IRS以增强链路传输能力.在BBU池和每个RRH发射功率约束下,本文提出通过联合优化前传链路和接入链路资源配置使下行用户和速率最大化.由于该资源配置问题是非凸的,首先采用连续凸逼近(SCA)对目标以及约束条件进行转换.其次,将转换后的问题拆分成三个子问题来交替性求解.最后,计算机仿真结果显示了所提出的联合资源分配方法与其他基准方案相比具有显著的传输性能增益.

This paper studies the downlink transmission system of intelligent reflecting surface(IRS)assisted OFDMA(Orthogonal Frequency Division Multiple Access)cloud radio access network(C-RAN),where the baseband unit(BBU)pool communicates with multi-user via multiple remote radio heads(RRHs).The access link from the RRH to the user adopts OFDMA technology.Wireless fronthaul link is used between the BBU pool and the RRH,and multiple IRSs are deployed to enhance the link transmission.Under the transmit power constraints of the BBU pool and per-RRH,this paper proposes to maximize the sum rate of downlink users by jointly optimizing the fronthaul link and the access link resource allocation.Since the resource allocation problem is non-convex,successive convex approximation(SCA)is first used to transform the objective and constraints.Then,the transformed problem is decomposed into three sub-problems which are solved alternatingly.Finally,the computer simulation results show that the proposed joint resource allocation approach can achieve significant transmission performance gain compared with other benchmark schemes.