Statistical Approaches for Initial Access in mmWave 5G Systems

Abstract

When a new user enters a cell in a mmWave cellular system, the beamforming directions must be identified to initiate communication, a procedure known as initial access (IA). However, users are more likely to enter from sorne directions than others (eg, along streets), and beamforming directions (eg, those affected by blockage) may never be used. We exploit the unequal distribution of the entrance direction to speed up the IA procedure, exploring more often the direc­tions wherein the probability of finding new users is higher. Two solutions are proposed: a memory-less random illumination (MLRI) algorithm and a statis­tical and memory-based illumination (SMBI) algorithm. While in MLRI, the direction to be explored is randomly generated according to an optimized dis­tribution, and independent of previously explored directions, in SMBI a precise exploration sequence is designed, thus we take into account previously explored directions. In the analysis, we include the movement of the user within the cell during the IA process, described by a Markov chain whose states correspond to the beamforming directions associated to the user position at a given IA explo­ration time. We assess the performance of the proposed methods in terms of average discovery time.