A Novel Power Spectrum-Based Sequential Tracker for Time-Variant Radio Propagation Channel

IEEE Access

Xuefeng Yin¹  Tianqi Wu¹  Juyul Lee² 

[1] College of Electronics and Information Engineering, Tongji University, Shanghai, China;Electronics and Telecommunications Research Institute (ETRI), Daejeon, South Korea;

关键词: Time-variant radio channel;    cluster tracking;    power spectrum;    fuzzy clustering;    cluster detection;    V2X;   

DOI  :  10.1109/ACCESS.2020.3017482

来源: DOAJ

【 摘 要 】

Cluster tracking is a mainstream approach for the study of time-variant channel characteristics. In the paper, we propose a power spectrum based sequential tracker (PSBST) to compensate for the disadvantages of existing cluster tracking algorithms. The proposed tracker identifies clusters via simple three-stage power spectrum processing. Furthermore, fuzzy c-means (FCM) algorithm is incorporated to separate clusters considering the overlapped clusters which may appear in the power spectrum. In terms of tracking, we implement Kalman filter to sequentially predict candidate ranges of tracked clusters in consecutive snapshots and simultaneously a novel gradient-based histogram of power (GBHOP) method is devised to determine the evolution of clusters. We also investigate the performance of the tracker by synthetic channel simulation. It demonstrates high accuracy and less computational time compared with the results derived from the existing cluster tracking algorithms. Besides, we verify applicability of the tracker by analyzing the field measurement conducted in vehicle-to-everything (V2X) scenario, and preliminary statistical characteristics for intra-cluster and inter-cluster parameters can be readily obtained in the sequel.

【 授权许可】

Unknown