Wang, Yuanchen, Zhu, Xu 
ORCID: 0000-0002-7371-4595, Lim, Eng Gee ORCID: 0000-0003-0199-7386, Wei, Zhongxiang, Liu, Yujie, Jiang, Yufei and IEEE,
(2020)
Compressive Sensing based User Activity Detection and Channel Estimation in Uplink NOMA Systems.
In: 2020 IEEE Wireless Communications and Networking Conference (WCNC), 2020-5-25 - 2020-5-28, Seoul, Korea (South), Korea (South).
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Abstract
Conventional request-grant based non-orthogonal multiple access (NOMA) incurs tremendous overhead and high latency. To enable grant-free access in NOMA systems, user activity detection (UAD) is essential. In this paper, we investigate compressive sensing (CS) aided UAD, by utilizing the property of quasi-time-invariant channel tap delays as the prior information. This does not require any prior knowledge of the number of active users like the previous approaches, and therefore is more practical. Two UAD algorithms are proposed, which are referred to as gradient based and time-invariant channel tap delays assisted CS (g-TIDCS) and mean value based and TIDCS (m-TIDCS), respectively. They achieve much higher UAD accuracy than the previous work at low signal-to-noise ratio (SNR). Based on the UAD results, we also propose a low-complexity CS based channel estimation scheme, which achieves higher accuracy than the previous channel estimation approaches.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Uncontrolled Keywords: | NOMA, compressive sensing, user activity detection, channel estimation, multipath |
| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 08 Apr 2021 10:02 |
| Last Modified: | 16 Mar 2024 02:25 |
| DOI: | 10.1109/WCNC45663.2020.9120664 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3118207 |
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