Ant Colony Optimization-based Signal Detection for Multiple-Input Multiple-Output System

• Main Authors: Jyun-Yu Chen, 陳俊宇
• Other Authors: Jenn-Kaie Lain
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/44905912927321913061

碩士 === 雲林科技大學 === 電子與資訊工程研究所 === 97 === Multiple-input multiple-output (MIMO) systems have shown significant increase in spectral efficiency using arrays of transmit and receive antennas with spatial processing. The performance improvements resulting from MIMO systems come at the cost of increasing the computational complexity in the receiver for signal detection. It is well known that maximum likelihood (ML) detection is considered the optimum method. However, ML detection is an NP-hard problem and is thus regarded as unfeasible especially for large number of transmit antennas and high-order modulation. Therefore, computational complexity in signal detection is the most critical issue for practical MIMO applications. In this thesis, we present a reduced-complexity MIMO signal detection scheme based on ant colony optimization (ACO) and proposed a modified ant colony optimization (MACO) with an emphasis on its near-ML performance with a low computational complexity.