Paper: Feb 25,2021
eess.SP
ID:2102.12817
Fronthaul Compression and Passive Beamforming Design for Intelligent Reflecting Surface-aided Cloud Radio Access Networks
This letter studies a cloud radio access network (C-RAN) with multiple
intelligent reflecting surfaces (IRS) deployed between users and remote radio
heads (RRH). Specifically, we consider the uplink transmission where each RRH
quantizes the received signals from the users by either point-to-point
compression or Wyner-Ziv compression and then transmits the quantization bits
to the BBU pool through capacity limited fronthhual links. To maximize the
uplink sum rate, we jointly optimize the passive beamformers of IRSs and the
quantization noise covariance matrices of fronthoul compression. An joint
fronthaul compression and passive beamforming design is proposed by exploiting
the Arimoto-Blahut algorithm and semidefinte relaxation (SDR). Numerical
results show the performance gain achieved by the proposed algorithm.
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Paper Author: Yu Zhang,Xuelu Wu,Hong Peng,Caijun Zhong,Xiaoming Chen
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