  Grant-free random access is promising for massive connectivity with sporadic
transmissions in massive machine type communications (mMTC), where the
hand-shaking between the access point (AP) and users is skipped, leading to
high access efficiency. In grant-free random access, the AP needs to identify
the active users and perform channel estimation and signal detection.
Conventionally, pilot signals are required for the AP to achieve user activity
detection and channel estimation before active user signal detection, which may
still result in substantial overhead and latency. In this paper, to further
reduce the overhead and latency, we explore the problem of grant-free random
access without the use of pilot signals in a millimeter wave (mmWave) multiple
input and multiple output (MIMO) system, where the AP performs blind joint user
activity detection, channel estimation and signal detection (UACESD). We show
that the blind joint UACESD can be formulated as a constrained composite matrix
factorization problem, which can be solved by exploiting the structures of the
channel matrix and signal matrix. Leveraging our recently developed unitary
approximate message passing based matrix factorization (UAMP-MF) algorithm, we
design a message passing based Bayesian algorithm to solve the blind joint
UACESD problem. Extensive simulation results demonstrate the effectiveness of
the blind grant-free random access scheme.
