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Grant-free random access is promising for massive connectivity with sporadictransmissions in massive machine type communications (mMTC), where thehand-shaking between the access point (AP) and users is skipped, leading tohigh access efficiency. In grant-free random access, the AP needs to identifythe active users and perform channel estimation and signal detection.Conventionally, pilot signals are required for the AP to achieve user activitydetection and channel estimation before active user signal detection, which maystill result in substantial overhead and latency. In this paper, to furtherreduce the overhead and latency, we explore the problem of grant-free randomaccess without the use of pilot signals in a millimeter wave (mmWave) multipleinput and multiple output (MIMO) system, where the AP performs blind joint useractivity detection, channel estimation and signal detection (UACESD). We showthat the blind joint UACESD can be formulated as a constrained composite matrixfactorization problem, which can be solved by exploiting the structures of thechannel matrix and signal matrix. Leveraging our recently developed unitaryapproximate message passing based matrix factorization (UAMP-MF) algorithm, wedesign a message passing based Bayesian algorithm to solve the blind jointUACESD problem. Extensive simulation results demonstrate the effectiveness ofthe blind grant-free random access scheme.

Matrix Factorization Based Blind Bayesian Receiver for Grant-Free Random Access in mmWave MIMO mMTC