  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 vector (MMV) 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 implementation. 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.
