UPDF AI

Closed-Form Model for Analysis of Terahertz Near-Field Sensing-Assisted Mobile Communication Systems in Temporal/Frequency/Spatial Division

Zile Liu,Chuang Yang,Yuanwei Liu,M. Peng

2025 · DOI: 10.1109/TCOMM.2025.3571925
IEEE Transactions on Communications · 1 Citations

Abstract

As one of the key enabler technologies for future networks, terahertz communications (THzComs) are vulnerable to performance degradation and even outage in mobile and near-field scenarios. The emerging integrated sensing and communications (ISAC) technique paves a way to settle the challenges by estimating user position or channel state to achieve beam-alignment, but fails to content the needs of near-field beam-focusing in mobile scenarios. To this end, a closed-form model for terahertz near-field sensing-assisted mobile communications (TNF-SAMC) is provided. Firstly, the TNF-SAMC system models in temporal/frequency/spatial-division schemes are exhibited. Secondly, a near-field four-dimensional sensing framework characterized by Cramér-Rao Bound is put forward. Thirdly, considering the assistance of sensing, the closed-form expressions of Ergodic Shannon Capacity is derived. Next, the theoretical analysis is proceeded to reveal TNF-SAMC performance features in terms of Division Factor, Joint Cramér-Rao Bound, and Critical Point. Especially the simplified closed-form derivations of Critical Points are given, hinting the minimum resources that should be allocated for sensing in TNF-SAMC systems. Then, numerical results verify the conclusion that temporal-division scheme prefers low mobility scenario, spatial-division scheme performs better in beam alignment case, while frequency-division scheme is most superior in TNF-SAMC systems.