Iterative joint channel estimation, user activity tracking, and data detection for FTN-NOMA systems supporting random access

Given the requirements of increased data rate and massive connectivity in the Internet-of-things (IoT) applications of the fifth-generation communication systems (5G), non-orthogonal multiple access (NOMA) was shown to be capable of supporting more users than OMA. As a further potential enhancement, the faster-than-Nyquist (FTN) signaling is also capable of increasing the symbol rate. Since NOMA and FTN signaling impose non-orthogonalities from different perspectives, it is possible to achieve further increased spectral efficiency by exploiting both. Hence we investigate the FTN-NOMA uplink in the context of random access. Although random access schemes reduce the signaling overheads as well as latency, they require the base station to identify active users before performing data detection. As both inter-symbol and inter-user interferences exist, performing optimal detection requires a prohibitively high complexity. Moreover, in typical mobile communication environments, the channel envelope of users fluctuates violently, which imposes challenges on the receiver design. To tackle this problem, we propose a joint user activity tracking and data detection algorithm based on the factor graph framework, which relies on a sophisticated amalgam of expectation maximization (EM) and hybrid message passing algorithms. The complexity of the algorithm advocated only increases linearly with the number of active users. Our simulation results show that the proposed algorithm is effective in tracking user activity and detecting data symbols in dynamic random access systems.

birth and survive probability, dynamic networks, faster-than-Nyquist signaling, hybrid message passing, Machine-type communications, non-orthogonal multiple access, random access

10.1109/TCOMM.2020.2975169

0090-6778

2963-2977

Yuan, Weijie

f1d6dc8e-6e97-4c5b-bfc7-78f48efb93b7

Wu, Nan

b22977ef-fd11-4eb1-8c5c-2b108b58907b

Guo, Qinghua

6839629b-2c16-461d-a8d7-6fa8a5176e25

Ng, Derrick Wing Kwan

8e2a32d3-cb0d-4c38-b05c-03ef16a5c707

Yuan, Jinhong

d50102f7-4fbd-45e3-a5a9-7fee391481ce

Hanzo, Lajos

66e7266f-3066-4fc0-8391-e000acce71a1

1 May 2020

Yuan, Weijie

f1d6dc8e-6e97-4c5b-bfc7-78f48efb93b7

Wu, Nan

b22977ef-fd11-4eb1-8c5c-2b108b58907b

Guo, Qinghua

6839629b-2c16-461d-a8d7-6fa8a5176e25

Ng, Derrick Wing Kwan

8e2a32d3-cb0d-4c38-b05c-03ef16a5c707

Yuan, Jinhong

d50102f7-4fbd-45e3-a5a9-7fee391481ce

Hanzo, Lajos

66e7266f-3066-4fc0-8391-e000acce71a1

Yuan, Weijie, Wu, Nan, Guo, Qinghua, Ng, Derrick Wing Kwan, Yuan, Jinhong and Hanzo, Lajos (2020) Iterative joint channel estimation, user activity tracking, and data detection for FTN-NOMA systems supporting random access. IEEE Transactions on Communications, 68 (5), 2963-2977, [9006927]. (doi:10.1109/TCOMM.2020.2975169).

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Accepted/In Press date: 13 February 2020

e-pub ahead of print date: 21 February 2020

Published date: 1 May 2020

Additional Information: Funding Information: This work was supported by the National Science Foundation of China (NSFC) (Grant No.61571041,61971041), a Foundation for the Author of National Excellent Doctoral Dissertation of P. R. China (FANEDD) (Grant No. 201445), the Australia Research Council Discovery Project (DP190101363) and Linkage Projects (LP 160100708 and LP170101196), L. Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EP/Noo4558/1, EP/PO34284/1, COALESCE, of the Royal Society's Global Challenges Research Fund Grant as well as of the European Research Council's Advanced Fellow Grant QuantCom. D. W. K. Ng is supported by funding from the UNSW Digital Grid Futures Institute, UNSW, Sydney, under a crossdisciplinary fund scheme and by the Australian Research Council's Discovery Project (DP190101363). Funding Information: Manuscript received October 12, 2019; revised January 7, 2020; accepted February 13, 2020. Date of publication February 21, 2020; date of current version May 15, 2020. This work was supported by the National Science Foundation of China (NSFC) (Grant No.61571041,61971041), a Foundation for the Author of National Excellent Doctoral Dissertation of P. R. China (FANEDD) (Grant No. 201445), the Australia Research Council Discovery Project (DP190101363) and Linkage Projects (LP 160100708 and LP170101196), L. Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EP/Noo4558/1, EP/PO34284/1, COALESCE, of the Royal Society’s Global Challenges Research Fund Grant as well as of the European Research Council’s Advanced Fellow Grant QuantCom. D. W. K. Ng is supported by funding from the UNSW Digital Grid Futures Institute, UNSW, Sydney, under a cross-disciplinary fund scheme and by the Australian Research Council’s Discovery Project (DP190101363). The associate editor coordinating the review of this article and approving it for publication was A. Nallanathan. (Corresponding Author: Nan Wu.) Weijie Yuan was with the School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China. He is now with the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW 2052, Australia (e-mail: weijie.yuan@unsw.edu.au). Publisher Copyright: © 2020 IEEE.

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Keywords: birth and survive probability, dynamic networks, faster-than-Nyquist signaling, hybrid message passing, Machine-type communications, non-orthogonal multiple access, random access