Abstract:
In this paper, a novel target recognition based clustering algorithm is proposed for time-varying channels. Power angle spectrum (PAS) is extracted from measurement data ...Show MoreMetadata
Abstract:
In this paper, a novel target recognition based clustering algorithm is proposed for time-varying channels. Power angle spectrum (PAS) is extracted from measurement data by using Bartlett beamformer. Then the clusters in the PAS are separated from the background by using the proposed algorithm, where the amplitude distribution of the elements in the PAS is considered. Moreover, morphology operations are applied to further divide the clusters which are connected to each other. It is found that, the dominating clusters in both line-of-sight (LoS) and non-line-of-sight (NLoS) environments can be well recognized by the proposed algorithm with low computation cost. By using the proposed algorithm, the dynamic changes of the clusters in real-time channel measurement can be clearly observed, without using any high-resolution parameter estimation.
Published in: 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)
Date of Conference: 18-20 October 2018
Date Added to IEEE Xplore: 02 December 2018
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ISSN Information:
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
Huawei Technologies Ltd.
Institute for Information and Communication Technologies, Electronics and Applied Mathematics, Universit Catholique de Louvain, Louvain-la-Neuve, Belgium
Department of Radio Science and Engineering, Aalto University, Aalto, Finland
Contents School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
Huawei Technologies Ltd.
Institute for Information and Communication Technologies, Electronics and Applied Mathematics, Universit Catholique de Louvain, Louvain-la-Neuve, Belgium
Department of Radio Science and Engineering, Aalto University, Aalto, Finland
