An Initial Access Optimization Algorithm for millimeter Wave 5G NR Networks

TL;DR

This paper introduces a dynamic-weight based beam sweeping algorithm for mmWave 5G NR networks that improves initial access by increasing user detection accuracy and reducing resource usage.

Contribution

It proposes a novel dynamic SSB allocation algorithm based on learned user detection patterns to optimize initial cell search in mmWave 5G NR networks.

Findings

Detects more users with lower misdetection probability

Achieves similar performance with fewer resources

Demonstrates improved initial access efficiency

Abstract

The millimeter wave (mmWave) communication uses directional antennas. Hence, achieving fine alignment of transmit and receive beams at the initial access phase is quite challenging and time-consuming. In this paper, we provide a dynamic-weight based beam sweeping direction and synchronization signal block (SSB) allocation algorithm to optimize the cell search of the initial access in mmWave 5G NR networks. The number of SSBs transmitted in each beam sweeping direction depends on previously learned experience which is based on the number of detected UEs (user equipment) per SSB for each sweeping direction. Overall, numerical simulation results indicate that 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.