  A high success rate of grant-free random access scheme is proposed to support
massive access for machine-to-machine communications in massive multipleinput
multiple-output systems. This scheme allows active user equipments (UEs) to
transmit their modulated uplink messages along with super pilots consisting of
multiple sub-pilots to a base station (BS). Then, the BS performs channel state
information (CSI) estimation and uplink message decoding by utilizing a
proposed graph combined clustering independent component analysis (GCICA)
decoding algorithm, and then employs the estimated CSIs to detect active UEs by
utilizing the characteristic of asymptotic favorable propagation of massive
MIMO channel. We call this proposed scheme as GCICA based random access
(GCICA-RA) scheme. We analyze the successful access probability, missed
detection probability, and uplink throughput of the GCICA-RA scheme. Numerical
results show that, the GCICA-RA scheme significantly improves the successful
access probability and uplink throughput, decreases missed detection
probability, and provides low CSI estimation error at the same time.
