Open AccessResource allocation for multiple input multiple output‐orthogonal frequency division multiplexing ‐based space division multiple access systems
Author(s) -
Pao WeiChen,
Lou WenTing,
Chen YungFang,
Chang DahChung
Publication year - 2014
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2014.0104
Subject(s) - mathematical optimization , orthogonal frequency division multiple access , computer science , telecommunications link , transmitter power output , multiplexing , resource allocation , orthogonal frequency division multiplexing , selection (genetic algorithm) , mathematics , telecommunications , computer network , channel (broadcasting) , transmitter , artificial intelligence
The problem of the system throughput maximisation and the fairness issue among users is considered for the downlink multiuser multiple input multiple output‐orthogonal frequency division multiplexing system with MMSE precoding. Since finding the optimal solution by using the exhaustive search has very high computational burden, the authors propose a low‐complexity user selection strategy plus the optimal power allocation in this study. With resorting to the mathematical simplification process, the proposed user selection scheme is designed to compare the related value of SINR. The power allocation is performed after the user selection. However, the power allocation is not in interference‐free environment but in the presence of crosstalk, which is a nonlinear non‐convex optimisation problem. In this study, the authors use an optimisation technique to obtain the optimal solution of the constrained non‐convex nonlinear problem by replacing the objective function with a difference of two convex functions. A bisection‐based strategy to solve this problem with interference‐awareness to find local optimal solutions is presented in this study. Simulation results show that the performance of the proposed algorithm is close to that of the optimal solution. The trade‐off between the system throughput and the fairness among users is also considered.