An Ant Colony Optimization Approach to the Probabilistic Traveling Salesman Problem
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Ant Colony Optimization
Fundamentals of wireless communication
Fundamentals of wireless communication
Introducing a binary ant colony optimization
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Receive antenna selection for MIMO spatial multiplexing: theory and algorithms
IEEE Transactions on Signal Processing
Capacity of MIMO systems with antenna selection
IEEE Transactions on Wireless Communications
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Capacity of MIMO Channels With Antenna Selection
IEEE Transactions on Information Theory
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In this paper, we present a real-time low-complexity joint transmit and receive antenna selection algorithm for MIMO systems. We apply Ant Colony Optimization (ACO) to the joint antenna selection problem. The computational complexity of exhaustive search in this problem grows exponentially with the number of transmit and receive antennas. The proposed ACO for joint antenna selection has a low computational complexity, and its effectiveness is verified through simulation results.