Beamforming based algorithm for 5G applications

Abohamra, Yousef Ali; Solymani, R.; Shayan, Yousef R.; Srar, Jala A.

doi:10.1007/s11235-022-00973-4

Cited by 2 publications

(2 citation statements)

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“…However, the study lacks details regarding the specific findings or limitations of the study, such as practical implementation challenges, real-world performance, or comparisons between these algorithms in diverse scenarios. The paper introduces a new algorithm -"Direction Finding for Beamforming and Synthesizing" -that combines Direction of Arrival (DOA) estimation, adaptive beamforming, and radiation pattern synthesis to achieve better results for 5G applications [5]. The algorithm's fast convergence, reliable tracking, and low side lobe levels are highlighted, but limitations such as real-world implementation challenges or comparisons with existing methods are not discussed.…”

Section: Related Workmentioning

confidence: 99%

“…The need for seamless data communication has led to the exploration of innovative techniques, among which "Dynamic Beamforming" has emerged as a promising solution. Dynamic beamforming is a crucial technique in the field of array signal processing, which improves the performance of sensor arrays in applications like wireless communication, radar, and sonar systems [5]. The primary aim of Dynamic beamforming is to optimize the array's directionality by adjusting the weights of individual sensors.…”

Section: Introductionmentioning

confidence: 99%

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Traffic Aware Dynamic Beamforming Antenna Design For 5G Communication

Imon,

Rahman,

Reza

et al. 2024

Preprint

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Dynamic beamforming is a wireless communication technique that enhances signal transmission and reception using multiple antennas to focus radio frequency energy towards specific directions or devices. Dynamic beamforming faces several challenges as mobility, signal interference, beam misalignment, beam training overhead, and signal traffic management. In this research work, an Advanced Optimized Algorithm (AOA) for beam-forming is proposed after a comprehensive analysis of the performance exhibited by the least mean square (LMS) and the Adaptive gradient algorithm. The weights of the antenna array are initiated and updated by the Advanced optimized algorithm, which involves moving in the direction of the negative gradient of the error signal. This optimization method significantly improves the array factor and the weighted value compared to the LMS and Ada-Grad algorithm, which reduce the processor burden and power consumption during the beamforming process. The outcomes of the experiments and analysis reveal that the proposed Advanced Optimized Algorithm is effective in enhancing the overall performance of beamforming patterns in the desired direction and can be used to resolve the issues of signal interference by employing complex weights for 5G antenna design. The proposed method demonstrates the suitability for high-speed, reliable real-time data communication, along with superiority for signal strength over the LMS and Ada-Grad algorithms.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%