TR2016-012
Millimeter wave communications channel estimation via Bayesian group sparse recovery
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- , "Millimeter Wave Communications Channel Estimation via Bayesian Group Sparse Recovery", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP.2016.7472309, March 2016, pp. 3406-3410.BibTeX TR2016-012 PDF
- @inproceedings{Suryaprakash2016mar,
- author = {Suryaprakash, Raj Tejas and Pajovic, Milutin and Kim, Kyeong Jin and Orlik, Philip V.},
- title = {Millimeter Wave Communications Channel Estimation via Bayesian Group Sparse Recovery},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2016,
- pages = {3406--3410},
- month = mar,
- doi = {10.1109/ICASSP.2016.7472309},
- url = {https://www.merl.com/publications/TR2016-012}
- }
- , "Millimeter Wave Communications Channel Estimation via Bayesian Group Sparse Recovery", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP.2016.7472309, March 2016, pp. 3406-3410.
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Abstract:
We consider the problem of channel estimation for millimeter wave communications (mmWave). We formulate channel estimation as a structured sparse signal recovery problem, in which the signal structure is governed by a priori knowledge of the channel characteristics. We develop a Bayesian group sparse recovery algorithm which takes into account for several features unique to mmWave channels, such as spatial (angular) spreads of received signals and power profile of rays impinging on the receiver array. We validate the developed method via numerical simulations and demonstrate an improved estimation performance relative to the existing methods.
Related News & Events
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NEWS MERL researchers present 12 papers at ICASSP 2016 Date: March 20, 2016 - March 25, 2016
Where: Shanghai, China
MERL Contacts: Petros T. Boufounos; Chiori Hori; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Philip V. Orlik; Anthony Vetro
Research Areas: Computational Sensing, Digital Video, Speech & Audio, Communications, Signal ProcessingBrief- MERL researchers have presented 12 papers at the recent IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which was held in Shanghai, China from March 20-25, 2016. ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing, with more than 1200 papers presented and over 2000 participants.