DE/PSO‐aided hybrid linear detectors for MIMO‐OFDM systems under correlated arrays

• Published in: Transactions on emerging telecommunications technologies 2018-12, Vol.29 (12), p.n/a
• Main Authors: Fukuda, Rafael Masashi, Guerra, David William Marques, Kobayashi, Ricardo Tadashi, Abrão, Taufik
• Format: Article
• Language: English
• ISSN: 2161-3915; 2161-3915
• DOI: 10.1002/ett.3495

In this paper, we analyze the performance of evolutionary heuristic‐aided linear detectors deployed in multiple‐input–multiple‐output (MIMO) orthogonal frequency‐division multiplexing (OFDM) systems, considering realistic operating scenarios. Hybrid linear‐heuristic detectors under different initial solutions provided by linear detectors are considered, namely, differential evolution and particle swarm optimization. Numerical results demonstrated the applicability of hybrid detection approach, which can improve considerably the performance of minimum mean‐square error and matched filter detectors. Furthermore, we discuss how the complexity of the presented algorithms scales with the number of antennas, besides of verifying the spatial correlation effects on MIMO‐OFDM performance assisted by linear, heuristic, and hybrid detection schemes. The influence of the initial point in the performance improvement and complexity reduction is evaluated numerically. Hybrid linear‐heuristic detector for MIMO‐OFDM systems is proposed and evaluated under the realistic channel and system scenarios, including a wide range of spatial antennas correlation. The proposed hybrid evolutionary MIMO‐OFDM detectors provided much better BER performance compared to linear and conventional heuristic approaches with reduced computational complexity regarding FLOPs. Parallelization, possibility to deal with nondifferentiable functions while speeding up convergence (iterations truncation), allows achieving suitable performance‐complexity tradeoffs and viable strategies for hardware implementation in real applications.