Statistical Approaches for Initial Access in mmWave 5G Systems

mmWave communication systems overcome high attenuation by using multiple antennas at both the transmitter and the receiver to perform beamforming. Upon entrance of a user equipment (UE) into a cell a scanning procedure must be performed by the base station 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 from 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, for example described by inter-arrival times. 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 average discovery time

Initial Access in 5G mm-Wave Cellular Networks

The massive amounts of bandwidth available at millimeter-wave frequencies (roughly above 10 GHz) have the potential to greatly increase the capacity of fifth generation cellular wireless systems. However, to overcome the high isotropic pathloss experienced at these frequencies, high directionality will be required at both the base station and the mobile user equipment to establish sufficient link budget in wide area networks. This reliance on directionality has important implications for control layer procedures. Initial access in particular can be significantly delayed due to the need for the base station and the user to find the proper alignment for directional transmission and reception. This paper provides a survey of several recently proposed techniques for this purpose. A coverage and delay analysis is performed to compare various techniques including exhaustive and iterative search, and Context Information based algorithms. We show that the best strategy depends on the target SNR regime, and provide guidelines to characterize the optimal choice as a function of the system parameters.Comment: 6 pages, 3 figures, 3 tables, 15 references, submitted to IEEE COMMAG 201

An initial access optimization algorithm for millimetre wave 5G NR networks

Abstract. The fifth generation (5G) of cellular technology is expected to address the ever-increasing traffic requirements of the digital society. Delivering these higher data rates, higher bandwidth is required, thus, moving to the higher frequency millimetre wave (mmWave) spectrum is needed. However, to overcome the high isotropic propagation loss experienced at these frequencies, base station (BS) and the user equipment (UE) need to have highly directional antennas. Therefore, BS and UE are required to find the correct transmission (Tx) and reception (Rx) beam pair that align with each other. Achieving these fine alignment of beams at the initial access phase is quite challenging due to the unavailability of location information about BS and UE. In mmWave small cells, signals are blocked by obstacles. Hence, signal transmissions may not reach users. Also, some directions may have higher user density while some directions have lower or no user density. Therefore, an intelligent cell search is needed for initial access, which can steer its beams to a known populated area for UEs instead of wasting time and resources emitting towards an obstacle or unpopulated directions. In this thesis, we provide a dynamic weight-based beam sweeping direction and synchronization signal block (SSB) allocation algorithm to optimize the cell search in the mmWave initial access. The order of beam sweeping directions and the number of SSBs transmitted in each beam sweeping direction depend on previously learned experience. Previous learning is based on the number of detected UEs per SSB for each sweeping direction. Based on numerical simulations, the proposed algorithm is shown to be capable of detecting more users with a lower misdetection probability. Furthermore, it is possible to achieve the same performance with a smaller number of dynamic resource (i.e., SSB) allocation, compared to constant resource allocation. Therefore, this algorithm has better performance and optimum resource usage

Context Information Based Initial Cell Search for Millimeter Wave 5G Cellular Networks

Millimeter wave (mmWave) communication is envisioned as a cornerstone to fulfill the data rate requirements for fifth generation (5G) cellular networks. In mmWave communication, beamforming is considered as a key technology to combat the high path-loss, and unlike in conventional microwave communication, beamforming may be necessary even during initial access/cell search. Among the proposed beamforming schemes for initial cell search, analog beamforming is a power efficient approach but suffers from its inherent search delay during initial access. In this work, we argue that analog beamforming can still be a viable choice when context information about mmWave base stations (BS) is available at the mobile station (MS). We then study how the performance of analog beamforming degrades in case of angular errors in the available context information. Finally, we present an analog beamforming receiver architecture that uses multiple arrays of Phase Shifters and a single RF chain to combat the effect of angular errors, showing that it can achieve the same performance as hybrid beamforming