Publication: Optimization of spectral efficiency for 5g networks of beamforming using modified weighted vector of mmse algorithm
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Date
2024-09-01
Authors
Mohammed Sadoon Khalaf, Alhuraishawy
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Abstract
The 5G cellular network, developed in 2020s, offers benefits like increased throughput and beam management. However, rapid global subscriber growth has affected network performance and spectral efficiency, causing lower data transfer rates and communication traffic congestion. Despite machine-learning algorithms for optimizing SE, they are not capable of optimizing overall 5G network parameters. The PhD dissertation aims to optimize the 5G mobile network by improving network quality, capacity, and user capacity while maintaining speed, durability, resilience, and performance. A case study of the general 5G cellular system was used to analyze a realistic dataset. The Minimum Mean Square Error (MMSE) algorithm was modified using a weight vector to enhance the spectral efficiency (SE) and compared with other state-of-the-art models. The results showed that the modified MMSE algorithm provided upgraded enhancements and significant amendments correlated to SE in the investigated 5G network, resulting in increased potential and robustness levels, fostered data receiving and sending potential, augmented bandwidth speed, and expandable user numbers. The modified MMSE algorithm outperformed other models in performing sufficient user communication requirements, making it the best candidate for managing efficient communication operations. For 10 channels, MMSE SE varies from 4.76 to 10.87 bps/Hz. Increasing users under a certain number of channels lowers SE, while adding channels boosts SE as user numbers rise. Overall, the modified MMSE algorithm helps serve users in far areas, saving data transfer costs, and improving spectral efficiency by 0.37-2.62%.