A novel beam management strategy using UE trajectory mapping

Date

2024-12

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Publisher

Faculty of Graduate Studies and Research, University of Regina

Abstract

This research presents a novel beam management strategy aimed at optimizing performance in multi-user mobile communication systems, specifically within the framework of 5G mmWave networks. As the demand for reliable and high-speed data transmission increases, traditional beamforming techniques face challenges such as high computational load and inefficiencies in indoor environments. The proposed method leverages user equipment (UE) trajectory information by segmenting user trajectories into equal-length segments, focusing the beam on the centre of each segment to ensure stable and consistent signal coverage. The methodology integrates angular weighting, and dynamic power control to enhance beamforming efficiency. The angular weighting function prioritizes signals aligned closely with the beam direction, further enhancing signal strength while reducing unwanted energy dispersion. Additionally, dynamic power control is employed to adjust transmit power according to the user’s position relative to the segment center, maintaining robust Received Signal Strength (RSS) without unnecessary energy expenditure. Simulation results indicate that the proposed approach significantly reduces beam switching frequency and computational load compared to conventional methods, while maintaining stable RSS and Signal-to-Interference-plus-Noise Ratio (SINR) across multiple users. This study demonstrates the potential of combining trajectory mapping, subarray-based beamforming, and nulling techniques for effective beam management in dynamic indoor environments. Overall, the findings highlight the scalability and efficiency of the proposed strategy in enhancing wireless communication systems, paving the way for future advancements in next generation 5G networks. Key words: Beamforming; Interference Management; Dynamic Indoor Environment; Predefined Segments; Subarray; Nulling Algorithm.

Description

A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Electronic Systems Engineering, University of Regina. ix, 73 p.

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