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B. Tahir, S. Schwarz, M. Rupp:
"Impact of Channel Correlation on Subspace-Based Activity Detection in Grant-Free NOMA";
Talk: 2022 IEEE 95th Vehicular Technology Conference (VTC2022-Spring), Helsinki (hybrid); 06-19-2022 - 06-22-2022; in: "Proceedings of the 95th IEEE Vehicular Technology Conference", (2022), ISBN: 978-1-6654-8243-1.

In this paper, we consider the problem of activity detection in grant-free code-domain non-orthogonal multiple access (NOMA). We focus on performing activity detection via subspace methods under a setup where the data and pilot spreading signatures are of different lengths, and consider a realistic frame-structure similar to existing mobile networks. We investigate the impact of channel correlation on the activity detection performance; first, we consider the case where the channel exhibits high correlation in time and frequency and show how it can heavily deteriorate the performance. To tackle that, we propose to apply user-specific masking sequences overlaid on top of the pilot signatures. Second, we consider the other extreme with the channel being highly selective, and show that it can also negatively impact the performance. We investigate possible pilots' reallocation strategies that can help reduce its impact.

Activity Detection, Channel Correlation, Channel Selectivity, Grant Free, Music, Noma, Non Orthogonal Multiple Access, Subspace

https://publik.tuwien.ac.at/files/publik_304359.pdf