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Multi-Sequence Spreading Random Access (MSRA) for Compressive Sensing-Based Grant-Free Communication.
- Source :
- IEEE Transactions on Communications; Nov2021, Vol. 69 Issue 11, p7531-7543, 13p
- Publication Year :
- 2021
-
Abstract
- The performance of grant-free random access (GF-RA) is limited by the number of accessible random access resources (RRs) due to the absence of collision resolution. Compressive sensing (CS)-based RA schemes scale up the RRs at the expense of increased non-orthogonality among transmitted signals. This paper presents the design of multi-sequence spreading random access (MSRA) which employs multiple spreading sequences to spread the different symbols of a user as opposed to the conventional schemes in which a user employs the same spreading sequence for each symbol. We show that MSRA provides code diversity, enabling the multi-user detection (MUD) to be modeled into a well-conditioned multiple measurement vectors (MMVs) CS problem. The code diversity is quantified by the decrease in the average Babel mutual coherence among the spreading sequences. Moreover, we present a two-stage active user detection (AUD) scheme for both wideband and narrowband implementations. Our theoretical analysis shows that with MSRA activity misdetection falls exponentially while the size of GF-RA frame is increased. Finally, the simulation results show that about 82% increase in utilization of RRs, i.e., more active users, is supported by MSRA than the conventional schemes while achieving the RA failure rate lower bound set by random access collision. [ABSTRACT FROM AUTHOR]
- Subjects :
- RANDOM numbers
RANDOM sets
CHANNEL estimation
DATA transmission systems
MUD
Subjects
Details
- Language :
- English
- ISSN :
- 00906778
- Volume :
- 69
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Communications
- Publication Type :
- Academic Journal
- Accession number :
- 153711037
- Full Text :
- https://doi.org/10.1109/TCOMM.2021.3103542