4.7 Article

Intelligent Reflecting Surface-Aided Joint Processing Coordinated Multipoint Transmission

期刊

IEEE TRANSACTIONS ON COMMUNICATIONS
卷 69, 期 3, 页码 1650-1665

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2020.3042275

关键词

Array signal processing; Optimization; Wireless networks; Transmission line matrix methods; Transforms; Radio frequency; Massive MIMO; Intelligent reflecting surface; coordinated multipoint transmission; phase shift optimization; dual subgradient; majorization-minimization

资金

  1. National Natural Science Foundation of China [61971128, U1936201]
  2. National Key Research and Development Program of China [2020YFB1804901]
  3. Open Research Fund of National Mobile Communications Research Laboratory, Southeast University [2021D15]
  4. UNSW Digital Grid Futures Institute, UNSW, Sydney
  5. Australian Research Council [DP190101363]

向作者/读者索取更多资源

This article investigates intelligent reflecting surface (IRS)-aided multicell wireless networks and proposes a joint optimization scheme to maximize the minimum achievable rate of cell-edge users. By transforming the non-convex max-min problem into an equivalent form using a compromise method, an efficient suboptimal iterative algorithm is designed. The optimization methods for single-user and multiuser scenarios are also discussed, showing significant performance improvement and outperformance compared to conventional designs in terms of max-min rate.
This article investigates intelligent reflecting surface (IRS)-aided multicell wireless networks, where an IRS is deployed to assist the joint processing coordinated multipoint (JP-CoMP) transmission from multiple base stations (BSs) to multiple cell-edge users. By taking into account the fairness among cell-edge users, we aim at maximizing the minimum achievable rate of cell-edge users by jointly optimizing the transmit beamforming at the BSs and the phase shifts at the IRS. As a compromise approach, we transform the non-convex max-min problem into an equivalent form based on the mean-square error method, which facilities the design of an efficient suboptimal iterative algorithm. In addition, we investigate two scenarios, namely the single-user system and the multiuser system. For the former scenario, the optimal transmit beamforming is obtained based on the dual subgradient method, while the phase shift matrix is optimized based on the Majorization-Minimization method. For the latter scenario, the transmit beamforming matrix and phase shift matrix are obtained by the second-order cone programming and semidefinite relaxation techniques, respectively. Numerical results demonstrate the significant performance improvement achieved by deploying an IRS. Furthermore, the proposed JP-CoMP design significantly outperforms the conventional coordinated scheduling/coordinated beamforming coordinated multipoint (CS/CB-CoMP) design in terms of max-min rate.

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