Advancements in Massive MIMO Technologies: Comprehensive Literature Survey on Channel Estimation

Massive multiple-input multiple-output (MIMO) technology has become a cornerstone in the development of next-generation wireless communication systems, offering significant improvements in spectral efficiency and energy efficiency. A critical challenge in massive MIMO systems is accurate and efficient channel estimation, essential for coherent signal detection and beamforming. This literature review comprehensively examines channel estimation techniques in massive MIMO systems. We delve into classical methods, such as Least Squares and Minimum Mean Squared Error estimation, advanced algorithms leveraging compressive sensing and machine learning, and innovations addressing practical challenges like pilot contamination and hardware impairments. By analyzing the strengths and limitations of each approach, we highlight the ongoing research efforts and future directions in this vital area.

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Published
2025-05-14
DOI
https://doi.org/10.1109/icpcsn65854.2025.11035307
Primary Topic
Advanced MIMO Systems Optimization
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article
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article

Advancements in Massive MIMO Technologies: Comprehensive Literature Survey on Channel Estimation

K. Vijayakumar, V. Anupriya, M. Saritha, A. Yogeshwaran et al.
Advanced MIMO Systems Optimization
article

Advancements in Massive MIMO Technologies: Comprehensive Literature Survey on Channel Estimation

K. Vijayakumar, V. Anupriya, M. Saritha, A. Yogeshwaran, G.Pavan Kumar, Arnesh Vijay
article en

Abstract

Massive multiple-input multiple-output (MIMO) technology has become a cornerstone in the development of next-generation wireless communication systems, offering significant improvements in spectral efficiency and energy efficiency. A critical challenge in massive MIMO systems is accurate and efficient channel estimation, essential for coherent signal detection and beamforming. This literature review comprehensively examines channel estimation techniques in massive MIMO systems. We delve into classical methods, such as Least Squares and Minimum Mean Squared Error estimation, advanced algorithms leveraging compressive sensing and machine learning, and innovations addressing practical challenges like pilot contamination and hardware impairments. By analyzing the strengths and limitations of each approach, we highlight the ongoing research efforts and future directions in this vital area.

Dhanalakshmi Srinivasan Group of Institutions (IN)
Quality Education
Openalex Percentile: Top 88%
Advanced MIMO Systems Optimization
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Advancements in Massive MIMO Technologies: Comprehensive Literature Survey on Channel Estimation — K. Vijayakumar, V. Anupriya, et al. · (2025) | TGRS Research Map | TGRS