Multi-Sequence Spreading Random Access (MSRA) for Compressive Sensing-Based Grant-Free Communication

The performance of grant-free random access (GF-RA) is limited by the number accessible resources (RRs) due to absence collision resolution. Compressive sensing (CS)-based RA schemes scale up RRs at expense increased non-orthogonality among transmitted signals. This paper presents design multi-sequence spreading (MSRA) which employs multiple sequences spread different symbols a user as opposed conventional in same sequence for each symbol. We show that MSRA provides code diversity, enabling multi-user detection (MUD) be modeled into well-conditioned measurement vectors (MMVs) CS problem. diversity quantified decrease average Babel mutual coherence sequences. Moreover, we present two-stage active (AUD) scheme both wideband and narrowband implementations. Our theoretical analysis shows with activity misdetection falls exponentially while size GF-RA frame increased. Finally, simulation results about 82% increase utilization RRs, i.e., more users, supported than achieving failure rate lower bound set collision.