Covariance-Based Activity Detection With Orthogonal Pilot Sequences for Cell-Free Distributed Massive MIMO Systems

The grant-free random access (GFRA) has been the mainstream access scheme in the massive ultra-reliable low-latency communications (mURLLC). Device activity detection is the foremost issue in GFRA. Most of previous works assume unique non-orthogonal pilot sequence assignment in device activity detection which brings about severe inter-device interference and requires high-complexity access point (AP) coordination to eliminate interference. Taking advantage of the good cross-correlation characteristic of orthogonal pilot sequences and the sparsity in power domain of cell-free (CF) distributed massive multiple-input multiple-output (mMIMO) systems, this paper proposes a novel orthogonal pilot sequences based activity detection (OPSAD) algorithm to alleviate inter-device interference and thus improve device activity detection performance. In the proposed OPSAD algorithm, the min-max covariance interference (MMCI) pilot assignment algorithm considering AP selection and power control is introduced and a new interference metric is defined to efficiently capture the inter-device interference in this algorithm. Simulation results show that the proposed algorithm reduces computational complexity and achieves better performance than the benchmark algorithm utilizing non-orthogonal pilot sequences in practical mURLLC scenario.