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DE/PSO-aided Hybrid Linear Detectors for MIMO-OFDM Systems under Correlated Arrays

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Rafael Masashi Fukuda, David William Marques Guerra, Ricardo Tadashi Kobayashi, Taufik Abrao

Signal Processing · Submitted 3 Oct 2018

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Numerical results demonstrated the applicability of hybrid detection approach, which can improve considerably the performance of minimum mean-square error (MMSE) and matched filter (MF) detectors.

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arXiv ID1810.01600 (version 1)
Pith IDQUTGUL35, Pith's permanent record of this paper and its review
CitationDavid William Marques Guerra, Rafael Masashi Fukuda, Ricardo Tadashi Kobayashi, Taufik Abrao. "DE/PSO-aided Hybrid Linear Detectors for MIMO-OFDM Systems under Correlated Arrays." arXiv:1810.01600 (2018). https://pith.science/paper/QUTGUL35
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What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.14 · human participants 0.01 · controlled comparison 0.78 · randomized assignment 0.01 · states quantitative result 0.06 · compares with prior results 0.87 · mentions code or data availability 0.02.

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arXiv listing abstract v1. Results and the main claim are underlined; .

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 (DE) and particle swarm optimization (PSO). Numerical results demonstrated the applicability of hybrid detection approach, which can improve considerably the performance of minimum mean-square error (MMSE) and matched filter (MF) 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.

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#sentencerolethe authors' own workstates the main conclusionstrength
s0 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. contribution 0.98 0.77 0.05 asserted 0.69
s1 Hybrid linear-heuristic detectors under different initial solutions provided by linear detectors are considered, namely differential evolution (DE) and particle swarm optimization (PSO). method 0.79 0.52 0.04 asserted 0.79
s2 Numerical results demonstrated the applicability of hybrid detection approach, which can improve considerably the performance of minimum mean-square error (MMSE) and matched filter (MF) detectors. result 0.97 0.94 0.72 asserted 1.00
s3 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. contribution 0.94 0.91 0.07 asserted 0.88
s4 The influence of the initial point in the performance improvement and complexity reduction is evaluated numerically. contribution 0.68 0.93 0.09 asserted 0.90

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

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 (DE) and particle swarm optimization (PSO). Numerical results demonstrated the applicability of hybrid detection approach, which can improve considerably the performance of minimum mean-square error (MMSE) and matched filter (MF) 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.

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