Name
Title | ||
|---|---|---|
Compressive Sensing Based User Activity Detection And Channel Estimation In Uplink Noma Systems |
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/WCNC45663.2020.9120664 | 2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) |
Keywords | DocType | ISSN |
NOMA, compressive sensing, user activity detection, channel estimation, multipath | Conference | 1525-3511 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuanchen Wang | 1 | 1 | 2.38 |
| Xu Zhu | 2 | 371 | 47.63 |
| Eng Gee Lim | 3 | 22 | 20.78 |
| Zhongxiang Wei | 4 | 37 | 11.26 |
| Liu Yujie | 5 | 122 | 24.79 |
| Yufei Jiang | 6 | 32 | 22.37 |