An Efficient Algorithm for Device Detection and Channel Estimation in Asynchronous IoT Systems

October 20, 2020 Β· Declared Dead Β· πŸ› IEEE International Conference on Acoustics, Speech, and Signal Processing

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Authors Liang Liu, Ya-Feng Liu arXiv ID 2010.09979 Category eess.SP: Signal Processing Cross-listed cs.IT Citations 25 Venue IEEE International Conference on Acoustics, Speech, and Signal Processing Last Checked 4 months ago
Abstract
A great amount of endeavour has recently been devoted to the joint device activity detection and channel estimation problem in massive machine-type communications. This paper targets at two practical issues along this line that have not been addressed before: asynchronous transmission from uncoordinated users and efficient algorithms for real-time implementation in systems with a massive number of devices. Specifically, this paper considers a practical system where the preamble sent by each active device is delayed by some unknown number of symbols due to the lack of coordination. We manage to cast the problem of detecting the active devices and estimating their delay and channels into a group LASSO problem. Then, a block coordinate descent algorithm is proposed to solve this problem globally, where the closed-form solution is available when updating each block of variables with the other blocks of variables being fixed, thanks to the special structure of our interested problem. Our analysis shows that the overall complexity of the proposed algorithm is low, making it suitable for real-time application.
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