Journal
IET COMMUNICATIONS
Volume 11, Issue 10, Pages 1619-1625Publisher
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-com.2016.1487
Keywords
MIMO communication; relay networks (telecommunication); telecommunication scheduling; array signal processing; antenna arrays; computational complexity; search problems; amplify and forward communication; protocols; approximation theory; multipair massive MIMO relay networks; power scaling laws; user scheduling strategy; multiple-input multiple-output relaying network; single relay station; amplify-and-forward protocol; antennas; zero-forcing beamforming; rate performance; power efficiency; scaling factors; transmit powers; closed-form expressions; optimal user scheduling; ergodic sum-rate maximimization; optimal use pair search; complexity reduction; Monte-Carlo simulation; analytical approximations
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Funding
- Jiangsu Provincial Colleges and Universities Project [16KJB510026]
- NUPTSF [NY213062, NY214035]
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This study studies a multi-pair massive multiple-input multiple-output (MIMO) relaying network, where multiple pairs of users are served by a single relay station with a large number of antennas, and the amplify-and-forward protocol and zero-forcing (ZF) beamforming are used at the relay. The authors investigate the ergodic achievable rates for the users and obtain tight approximations in closed form for finite number of antennas. The rate performance and power efficiency are studied based on the analytical results for asymptotic scenarios, and the effect of scaling factors of transmit powers for users and relay are discussed. The closed-form expressions enable us to determine the optimal user scheduling which maximizes the ergodic sum-rate for the selected pairs. A simplified user scheduling algorithm is proposed which greatly reduces the average complexity of the optimal use pair search without any rate loss. Moreover, the complexity reduction for the proposed algorithm increases nonlinearly with the increase of the number of user pairs, which indicates that the simplified scheduling algorithm has notable advantages when the number of users is increased. The tightness for the analytical approximations and the superiority of the proposed algorithm are verified by Monte-Carlo simulation results.
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