MIMO antenna subset selection with space-time coding
IEEE Transactions on Signal Processing
Receive antenna selection for MIMO spatial multiplexing: theory and algorithms
IEEE Transactions on Signal Processing
Adaptive transmit antenna selection with pragmatic space-time trellis codes
IEEE Transactions on Wireless Communications
Receive antenna selection in MIMO systems using convex optimization
IEEE Transactions on Wireless Communications
Antenna selection in MIMO systems
IEEE Communications Magazine
Low-Complexity Throughput-Based Antenna Selection Method
Wireless Personal Communications: An International Journal
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This paper investigates the receive antenna selection problem to maximize capacity in wireless MIMO communication system, which can be formulated as an integer programming optimization problem and can not be directly solved because of its non-convex characteristics caused by the discrete binary antenna selection factor. To deal with this challenge, a computationally efficient approach, particle swarm optimization(PSO) algorithm is introduced, in which the particle is defined as the discrete binary antenna selection factor and the objective function is associated with the capacity corresponding to the specified antenna subsection represented by the particle. Furthermore, in order to meet the condition that the number of selected antennas should keep fixed, the particle elements are relaxed to change between [0 1] and the position of the higher elements are taken as the index of the antenna subsection to be activated. Then the best antenna subset can be found by seeking the global optimal particle in PSO. Numerical results reveal that PSO algorithm exhibits a promising performance when applied to both the classical benchmark function and our antenna selection scenario.