Channel Estimation and Indoor Positioning for Wideband Multiuser Millimeter Wave Systems
ID:150 View Protection:ATTENDEE Updated Time:2020-08-05 10:17:28 Hits:406 Oral Presentation

Start Time:2020-06-08 14:00(Asia/Shanghai)


Session:S Special Session » SS04Structured Tensor And Matrix Methods For Sensing, Communications, And Machine Learning

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We focus on channel estimation and indoor positioning of wideband multiuser millimeter wave systems. Leveraging the sparse channel characteristics, we transform the estimation problem to recovery problems of multipath parameters, e.g., angle of arrival, time delay and path fading. We model the training signal as a matricization form of a third-order canonical polyadic tensor, which consists of three factor matrices containing channel information. Inspired by array signal processing methods, we exploit the structural feature of our tensor and develop an uniqueness condition of tensor factorization, leading to a tensor-based channel estimation algorithm. In order to distinguish the multiuser signal components, we further develop a clustering-aided indoor positioning scheme. Simulation results show that the proposed methods apply to different system configurations and can achieve satisfactory estimation and positioning performance.
channel estimation; hybrid beamforming; indoor positioning; mmWave systems; tensor signal processing
Submission Author
Shi Jin Southeast University, China
Michail Matthaiou Queen's University Belfast, United Kingdom (Great Britain)
Xiaohu You National Mobile communication Research Lab., Southeast University, China
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    Jun 11


  • Jan 12 2020

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  • Apr 15 2020

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