Spatial Based Pilot Allocation (SBPA) in Crowded Massive MIMO Systems

In this study, a new approach of random access and pilot allocation in crowded scenarios of massive multi-input multi-output (MIMO) systems is proposed. When the number of users in a cell is more than number of orthogonal pilots, random access to pilots (RAP) is a promising solution to solve the massive access problem of users; though the collision of pilots is a by-product of this method. There are several methods for pilot collision resolution such as strongest user collision resolution (SUCR), but they have one major limitation; i.e. they cannot serve users more than the number of orthogonal pilots simultaneously in coherent transmission mode. In this paper, angle of arrival (AOA) and angular spread (AS) of the received pilots in a compressed sensing approach are examined by applying sparsity of massive MIMO channels in angular domain. That allows to allocate same orthogonal pilot to non-overlapped users in spatial domain for coherent data transmission. By applying this approach in newly proposed protocol (SBPA), the limitation in number of adopted simultaneous users in crowded scenarios of a massive MIMO system would be resolved. Numerical results show improvement in access failures rate compared to SUCR in crowded massive MIMO systems.