상세정보
학술지
A Novel Power Spectrum-Based Sequential Tracker for Time-Variant Radio Propagation Channel
- 저자
- Tianqi Wu, Xuefeng Yin, 이주열
- 발행일
- 202008
- 출처
- IEEE Access, v.8, pp.151267-151278
- ISSN
- 2169-3536
- 출판사
- IEEE
- 협약과제
- 20HH1700, 선제적 주파수 이용을 위한 시·공간적 스펙트럼 엔지니어링 기술 개발, 정영준
- 초록
- 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.
- KSP 제안 키워드
- Channel Characteristics, Channel Simulation, Computational time, Field measurement, Fuzzy C-means (FCM) algorithm, High accuracy, Inter-Cluster, Intra-Cluster, Overlapped clusters, Radio propagation channel, Spectrum processing