Channel Estimation and Signal Detection for Massive MIMO under 5G Communication

In this article, the space-time transmit technique (STTT) is examined in a massive MIMO environment with Rayleigh fading. The article characterizes the instantaneous signal-to-noise ratio (SNR) for statistical analysis after channel estimation. Singular value decomposition (SVD) is used to get SNR. It provides a closed-form expression for the moment-generating function (MGF) and uses the incomplete moment-generating function (IMGF) to construct the moment's closed-form expression. Key concepts in the fundamentals of communication theory, such as the probability density function (PDF) and cumulative distribution function (CDF), are explored. PDF and CDF plots are obtained for a range of degrees of freedom. Simulation results show that as the degree of freedom increases, a properly normalized sum of the channel information tends toward a normal distribution in STTT which follows central limit theorem.

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Publication Details

Journal
Computer Networks and Communications
Published
2024-11-07
DOI
https://doi.org/10.37256/cnc.2220245390
Citations
3
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.63
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article

Channel Estimation and Signal Detection for Massive MIMO under 5G Communication

M. K. Arti, Pratibha Rani, Pradeep Kumar Dimri
3 citations
Computer Networks and Communications
Advanced MIMO Systems Optimization
0.63
article

Channel Estimation and Signal Detection for Massive MIMO under 5G Communication

M. K. Arti, Pratibha Rani, Pradeep Kumar Dimri
article en
3 citations

Abstract

In this article, the space-time transmit technique (STTT) is examined in a massive MIMO environment with Rayleigh fading. The article characterizes the instantaneous signal-to-noise ratio (SNR) for statistical analysis after channel estimation. Singular value decomposition (SVD) is used to get SNR. It provides a closed-form expression for the moment-generating function (MGF) and uses the incomplete moment-generating function (IMGF) to construct the moment's closed-form expression. Key concepts in the fundamentals of communication theory, such as the probability density function (PDF) and cumulative distribution function (CDF), are explored. PDF and CDF plots are obtained for a range of degrees of freedom. Simulation results show that as the degree of freedom increases, a properly normalized sum of the channel information tends toward a normal distribution in STTT which follows central limit theorem.

Computer Networks and Communications
Netaji Subhas University of Technology (IN), J.C. Bose University of Science & Technology, YMCA (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 31%
Advanced MIMO Systems Optimization
0.63
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