Reducing Successive Interference Cancellation Iterations in Hybrid Beamforming Multiuser Massive Multiple Input Multiple Output Systems Through Grouping Users with Symmetry Channels

This paper presents a comprehensive exploration of advanced beamforming techniques tailored for millimeter-wave (mm-Wave) communication systems. In response to the burgeoning demand for higher data rates, coupled with the constraints of power consumption and hardware complexity, this study focuses o...

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Bibliographic Details
Published in:Symmetry (Basel) 2024-11, Vol.16 (11), p.1437
Main Authors: Rehab, Hashem Khaled, Rogozhnikov, Eugeniy, Savenko, Kirill, Mukhamadiev, Semen, Kryukov, Yakov, Pokamestov, Dmitriy
Format: Article
Language:English
Subjects:
Algorithms
Antennas
Beamforming
Channels
Communications systems
Complexity
Design
Efficiency
hybrid beamforming
Mean square errors
Millimeter waves
MIMO
MIMO communications
mm-Wave
Performance evaluation
SIC
Simulation methods
spectral efficiency
Symmetry
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Summary:This paper presents a comprehensive exploration of advanced beamforming techniques tailored for millimeter-wave (mm-Wave) communication systems. In response to the burgeoning demand for higher data rates, coupled with the constraints of power consumption and hardware complexity, this study focuses on developing a hybrid beamforming framework optimized for downlink scenarios, specifically targeting groups of users based on the approximate symmetry of their channels. The primary innovation of this research lies in leveraging the symmetry of channels among near users to develop a group-based successive interference cancellation (SIC) algorithm. Unlike traditional approaches that address interference on a per-user basis, this algorithm utilizes channel symmetry within clusters of users to reduce computational complexity and improve the efficiency of SIC. By grouping users with symmetrical channel characteristics, the algorithm simplifies the interference management process while maintaining system performance. The proposed system demonstrates notable advantages over existing non-linear algorithms through extensive simulations and performance evaluations, particularly in terms of spectral efficiency and computational complexity. In this study, we further emphasize the importance of balancing spectral efficiency improvements with reduced computational demands, offering a nuanced trade-off that accommodates various operational requirements. The flexible optimization framework provided showcases the system’s adaptability to diverse deployment scenarios and network configurations.
ISSN:2073-8994
2073-8994
DOI:10.3390/sym16111437