Symbol Detection in Multiple Antenna Wireless Systems via Ant Colony Optimization

Abstract

Multiple-input multiple-output (MIMO) is a promising technique to realize tremendous rise in the demand for wireless data traffic in future generation of wireless systems. Spatial multiplexing (SM) in MIMO is a key technique through which different information symbols can be transmitted from multiple transmit antennas. However, one of the major issues with the practical implementation of SM-aided MIMO systems is with the detection of different information symbols at the receiver end. Maximum likelihood (ML) detection is a well known technique which achieves optimal bit error rate (BER) performance in MIMO systems but is computationally inefficient due to its exponential increase in computational complexity with increase in the number of antennas. Therefore, low-complexity detectors which can achieve reliable BER performance are of great interest. Recently, there has been an increased attention from wireless research community towards bio-inspired algorithms such as ant colony optimization (ACO) and particle swarm optimization (PSO) which can achieve suboptimal performance with low complexity. In this chapter, we present ACO inspired technique to detect the transmitted symbols in MIMO systems. Further, we also present simulation results to validate the advantages of ACO in MIMO systems. © 2017 Elsevier Inc. All rights reserved.