A low-complexity hybrid algorithm based on particle swarm and ant colony optimization for large-MIMO detection

作者：

Highlights：

• A low-complexity hybrid algorithm for large-MIMO detection is proposed.

• Hybridization of ant colony and particle swarm optimization algorithms.

• Superior performance over existing ant colony optimization algorithms.

• The hybrid algorithm achieves near optimal bit error rate performance.

摘要

•A low-complexity hybrid algorithm for large-MIMO detection is proposed.•Hybridization of ant colony and particle swarm optimization algorithms.•Superior performance over existing ant colony optimization algorithms.•The hybrid algorithm achieves near optimal bit error rate performance.

论文关键词：Particle swarm optimization,Ant colony optimization,Zero forcing,Minimum mean squared error,Multiple-input multiple-output,Maximum likelihood,Bit error rate

论文评审过程：Received 15 January 2015, Revised 9 December 2015, Accepted 10 December 2015, Available online 29 December 2015, Version of Record 14 January 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.12.008