Challenges and opportunities for enhanced channel capacity in near-field wireless communication

Bing Tian

doi:10.1117/12.3027110

1 April 2024 Challenges and opportunities for enhanced channel capacity in near-field wireless communication

Bing Tian

Proceedings Volume 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024); 1307704 (2024) https://doi.org/10.1117/12.3027110
Event: 4th International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 2024, Chicago, IL, United States

Abstract

This paper explores the application and challenges of Multiple Input, Multiple Output (MIMO) systems in the near-field range of wireless communication. With the shortening of the wavelength of electromagnetic wave, wireless communication gradually changes from far-field communication to near-field communication. In near-field communication, the spherical wave property of electromagnetic wave dominates, rather than the plane wave property in far-field communication. Therefore, it is necessary to reevaluate the existing far-field theories. The study investigates the use of MIMO to enhance channel capacity in the near-field range, considering the effective transmission distance of electromagnetic waves and the transition from plane to spherical waves. The complexities of utilizing millimeter waves and the potential of other frequency bands are examined. An in-depth analysis is provided on the practical implementation of near-field MIMO systems, including their applicability in current 4G and emerging 5G technologies. The manuscript offers a comprehensive understanding of the innovative approach to improve information transmission in wireless communication, paving the way for future research and development.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bing Tian "Challenges and opportunities for enhanced channel capacity in near-field wireless communication", Proc. SPIE 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 1307704 (1 April 2024); https://doi.org/10.1117/12.3027110

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