Tensor decomposition-based 3D positioning with a single-antenna receiver in 5G millimetre wave systems

• Published in: IET communications Vol. 14; no. 20; pp. 3619 - 3630
• Main Authors: Dan, Zesheng, Lian, Baowang, Tang, Chengkai, Xu, Haowei
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 15.12.2020
• Subjects: 5G base station; 5G millimetre wave systems; 5G mmWave systems; 5G mobile communication; array signal processing; CAMDECOMP/PARAFAC decomposition; channel estimation; compressed sensing; compressed sensing‐based algorithm; Cramér–Rao bound; fifth‐generation base stations; high‐precision positioning; massive antenna arrays; matrix decomposition; mean square error methods; millimetre wave antenna arrays; millimetre wave receivers; millimetre‐wave system; mmWave channel; radio receivers; Research Article; single antenna; single‐antenna receiver; tensor decomposition‐based 3D positioning; third‐order low‐rank tensor structure; three‐dimensional positioning; time of arrival; time‐of‐arrival estimation; wireless channels; CAMDECOMP/PARAFAC decomposition; time-of-arrival estimation; compressed sensing; millimetre-wave system; matrix decomposition; third-order low-rank tensor structure; 5G mmWave systems; mmWave channel; Cramér–Rao bound; three-dimensional positioning; single-antenna receiver; wireless channels; 5G base station; mean square error methods; array signal processing; high-precision positioning; 5G mobile communication; millimetre wave receivers; fifth-generation base stations; radio receivers; tensor decomposition-based 3D positioning; massive antenna arrays; channel estimation; compressed sensing-based algorithm; 5G millimetre wave systems; single antenna; millimetre wave antenna arrays; time of arrival
• ISSN: 1751-8628; 1751-8636; 1751-8636
• DOI: 10.1049/iet-com.2019.1254

Exploiting a single-antenna receiver to realise three-dimensional (3D) positioning in a millimetre-wave (mmWave) system is considered. The primary motivation is that the massive antenna arrays will be deployed in the fifth-generation (5G) base stations shortly soon, which not only tremendously promote the data transmission rate, but also enable the user equipment to realise high-precision positioning with a single antenna. Based on the sparsity of the mmWave channel, the tensor decomposition is proposed to be utilised as an effective mathematical tool to realise 3D positioning. Specifically, the authors model the received signals as a third-order tensor for the inherent third-order low-rank tensor structure of the mmWave channel with a single-antenna receiver and then, the positioning parameters (including the angles of departure and the time of arrival) are estimated from the corresponding factor matrices via CAMDECOMP/PARAFAC (CP) decomposition. Moreover, Cramér–Rao bounds (CRBs) on 3D position uncertainty are derived. Numerical results demonstrate that the proposed method based on CP decomposition realises nearly the same positioning accuracy as the state-of-the-art compressed sensing-based algorithm in the 5G mmWave systems with lower computation complexity, and the root mean square errors of the 3D positioning results obtained via the proposed approach are close to their CRBs.