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A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G
Mahmoud A Albreem1, Mohammed H Alsharif2, Sunghwan Kim3
1Department of Electronics and Communications Engineering, A'Sharqiyah University, Ibra 400, Oman.
Entropy (Basel, Switzerland)
|December 8, 2020
Summary
Linear detectors in massive multiple-input multiple-output (M-MIMO) systems offer simpler implementation than maximum likelihood detectors. The conjugate-gradient method shows promise, but performance degrades when the antenna ratio approaches one.
Area of Science:
- Wireless Communication
- Signal Processing
- Information Theory
Background:
- Massive multiple-input multiple-output (M-MIMO) is crucial for 5G systems, but optimal detectors have high complexity.
- Linear detectors offer a trade-off between complexity and performance, facing challenges in high-load scenarios and ill-conditioned channels.
- Iterative matrix inversion methods are explored to mitigate noise enhancement and improve detector design.
Purpose of the Study:
- To evaluate the performance of a linear detector using iterative matrix inversion methods in realistic radio channels.
- To assess the conjugate-gradient (CG) method's robustness and efficiency.
- To investigate the impact of antenna ratios on iterative detector performance.
Main Methods:
- Simulation of a linear detector employing iterative matrix inversion techniques.
- Utilized the QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa) package for realistic channel modeling.
- Analyzed the conjugate-gradient (CG) method for its numerical robustness and computational efficiency.
Main Results:
- The conjugate-gradient (CG) method demonstrated numerical robustness and superior performance with fewer multiplications.
- Iterative methods require a large number of iterations (n) for satisfactory performance in the QuaDRiGA environment.
- Performance of iterative matrix inversion methods significantly degrades when the ratio of user to base station antennas (β) approaches 1.
Conclusions:
- The conjugate-gradient (CG) method is a viable and efficient approach for linear detection in M-MIMO systems.
- Iterative methods show potential but necessitate careful parameter tuning (e.g., number of iterations) for optimal results.
- The antenna ratio (β) is a critical factor influencing the effectiveness of iterative linear detectors in M-MIMO systems.
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