Improved LAS detector for MIMO systems with imperfect channel state information

Issa, Chihaoui; Ammari, Mohamed Lassaad; Fortier, Paul

doi:10.1049/iet-com.2018.5783

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…Altamirano et al in Reference 37 have evaluated the BER performance of linear detectors in M‐MIMO systems under ICSI. Performance analysis of ZF has been carried out under ICSI with different likelihood ascent search (LAS) detectors for M‐ary quadrature amplitude modulation (4‐QAM) and pulse amplitude modulation (4‐PAM) over

10\times 40

MIMO systems 38 . It is observed in Reference 38 that the proposed LAS detector gives good BER performance with ICSI, however, at the cost of high computational complexity.…”

Section: Introductionmentioning

confidence: 99%

“…Performance analysis of ZF has been carried out under ICSI with different likelihood ascent search (LAS) detectors for M‐ary quadrature amplitude modulation (4‐QAM) and pulse amplitude modulation (4‐PAM) over

10\times 40

MIMO systems 38 . It is observed in Reference 38 that the proposed LAS detector gives good BER performance with ICSI, however, at the cost of high computational complexity. Minimum Error Probability (MEP) is proposed in Reference 39 for a given length of pilot symbols with ICSI; however, the complexity of the proposed detector is equivalent to the MMSE detector.…”

Section: Introductionmentioning

confidence: 99%

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Performance analysis and comparison of approximate detectors with linear detectors in massive MIMO systems under imperfect channel state information

Khurshid

Imran

Wakeel

2023

Trans Emerging Tel Tech

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SummaryMassive MIMO systems are a key technology for enhancing the capacity and reliability of wireless communication systems. However, to unlock the full potential of massive MIMO systems, accurate channel state information is crucial at the receivers. In practice, channel estimation errors are inevitable, leading to significant performance degradation in traditional massive MIMO equalizers that assume perfect channel state information. In this work, we investigate the performance of approximate massive MIMO detectors, specifically the Gauss‐Seidel and Neumann series, over a time‐invariant channel with imperfect channel state information. We derive the expressions of signal‐to‐interference‐plus‐noise ratio and average bit error rate for approximate massive MIMO detectors in a unicellular environment using M‐ary quadrature amplitude modulation. Additionally, we compare the performance of linear detectors, including zero‐forcing, minimum‐mean‐squared‐error, and maximal‐ratio combining, with that of the approximate detectors. Through extensive Monte Carlo numerical simulations and various system configurations, we demonstrate that the Gauss‐Seidel detector, under imperfect channel state information, achieves comparable bit error rate performance to the zero‐forcing and minimum‐mean‐squared‐error detectors while requiring less computational complexity. Our study suggests that the Gauss‐Seidel detector has the potential to be used in massive MIMO systems in the presence of imperfect channel state information, highlighting its practical relevance in real‐world scenarios.

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10\times 40

MIMO systems 38 . It is observed in Reference 38 that the proposed LAS detector gives good BER performance with ICSI, however, at the cost of high computational complexity.…”

Section: Introductionmentioning

confidence: 99%

10\times 40

Section: Introductionmentioning

confidence: 99%

Performance analysis and comparison of approximate detectors with linear detectors in massive MIMO systems under imperfect channel state information

Khurshid

Imran

Wakeel

2023

Trans Emerging Tel Tech

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“…Approximate expectation propagation (EP) is proposed in [ 23 ]. In [ 24 ], a detector based on likelihood ascent search (LAS) was proposed for M-MIMO. Although they achieve a good performance, the complexity is still high.…”

Section: Introductionmentioning

confidence: 99%

A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G Communication Systems

Albreem

Alsharif

Kim

2020

Entropy

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Massive multiple-input multiple-output (M-MIMO) is a substantial pillar in fifth generation (5G) mobile communication systems. Although the maximum likelihood (ML) detector attains the optimum performance, it has an exponential complexity. Linear detectors are one of the substitutions and they are comparatively simple to implement. Unfortunately, they sustain a considerable performance loss in high loaded systems. They also include a matrix inversion which is not hardware-friendly. In addition, if the channel matrix is singular or nearly singular, the system will be classified as an ill-conditioned and hence, the signal cannot be equalized. To defeat the inherent noise enhancement, iterative matrix inversion methods are used in the detectors’ design where approximate matrix inversion is replacing the exact computation. In this paper, we study a linear detector based on iterative matrix inversion methods in realistic radio channels called QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa) package. Numerical results illustrate that the conjugate-gradient (CG) method is numerically robust and obtains the best performance with lowest number of multiplications. In the QuaDRiGA environment, iterative methods crave large n to obtain a pleasurable performance. This paper also shows that when the ratio between the user antennas and base station (BS) antennas ( β ) is close to 1, iterative matrix inversion methods are not attaining a good detector’s performance.

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Performance Analysis of LAS Algorithm in Massive MIMO with Imperfect CSI

Solanki

Gupta

2022

Proceedings of First International Conference on Computational Electronics for Wireless Communications

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Improved LAS detector for MIMO systems with imperfect channel state information

Cited by 5 publications

References 28 publications

Performance analysis and comparison of approximate detectors with linear detectors in massive MIMO systems under imperfect channel state information

Performance analysis and comparison of approximate detectors with linear detectors in massive MIMO systems under imperfect channel state information

A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G Communication Systems

Performance Analysis of LAS Algorithm in Massive MIMO with Imperfect CSI

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