Statistical approaches for initial access in mmwave 5G systems

MmWave communication systems overcome high attenuation by using multiple antennas with beamforming at both the transmitter and the receiver. Upon entrance of a user equipment (UE) into a cell, the base station scans the space in order to find the UE, in what is known as initial access (IA) procedure. In this paper, we start from the observation that UEs are more likely to enter from some directions than others, as they typically move along streets, while other movements are impossible due to the presence of obstacles. Moreover, users are entering with a given time statistics. In this context, we propose scanning strategies for IA that take into account the entrance statistics. In particular, we propose two approaches: a memory-less random illumination (MLRI) algorithm and a statistic and memory-based illumination (SMBI) algorithm. The MLRI algorithm scans a random sector in each slot, based on the statistics of sector entrance, without memory. The SMBI algorithm instead scans sectors in a deterministic sequence selected according to the statistics of sector entrance and time of entrance and taking into account the fact that the user has not yet been discovered (thus including memory). We assess the performance of the proposed methods in terms of misdetection and false alarm probability and average discovery tim