  Grant-free random access (RA) with massive MIMO is a promising RA technique
with low signaling overhead that provides significant benefits in increasing
the channel reuse efficiency. Since user equipment (UE) detection and channel
estimation in grant-free RA rely solely on the received preambles, preamble
designs that enable high success rate of UE detection and channel estimation
are very much in need to ensure the performance gain of grant-free RA with
massive MIMO. In this paper, a super preamble consisting of multiple
consecutive preambles is proposed for high success rate of grant-free RA with
massive MIMO. With the proposed approach, the success of UE detection and
channel estimation for a RA UE depends on two conditions: 1) it is a solvable
UE; 2) its super preamble is detected. Accordingly, we theoretically analyze
the solvable rate of RA UEs with multiple preambles and propose a reliable UE
detection algorithm to obtain the super preambles of RA UEs by exploiting the
quasi-orthogonality characteristic of massive MIMO. Theoretical analysis and
simulation results show that turning a preamble into a super preamble
consisting of two or three shorter preambles, the success rate of UE detection
and channel estimation could be significantly increased using the proposed
approach.
