DRX in NR Unlicensed for B5G Wireless: Modeling and Analysis
Publication Date
1-1-2022
Document Type
Article
Publication Title
IEEE Transactions on Mobile Computing
DOI
10.1109/TMC.2022.3168510
Abstract
The proliferation in the demand of high data rate and improved performance has urged wireless vendors to think of extending 5G New Radio (NR) in unlicensed bands. The unlicensed band is mainly used by Wi-Fi and Wi-Gig resulting in the reduced probability of channel availability. The User Equipment (UE) has to remain active and wait for the availability of unlicensed channel. This process escalates the energy expense of battery-constrained mobile devices. Discontinuous Reception (DRX) introduced in 3GPP can also be used in NR-Unlicensed (NR-U) to reduce UEs energy consumption. This article introduces a DRX mechanism over NR-U networks for both Standalone (SA) and Non-Standalone (NSA) deployment modes. We have used two different flavors, Beam-Search and Beam-Aware, to model DRX mechanism. Hence, the proposed DRX mechanisms are: Standalone DRX with Beam-Search (SBS-DRX), Standalone DRX with Beam-Aware (SBA-DRX), Non-Standalone DRX with Beam-Search (NBS-DRX), and Non-Standalone DRX with Beam-Aware (NBA-DRX). Semi-Markov based modeling is used to show the estimation of power-saving, average delay, and resource utilization. The power-saving achieved with SBA-DRX is 21.13% and 24.84% higher than 5G NR DRX for both Trace 1 and Trace 2, respectively. Moreover, delay achieved with NBA-DRX is 19.16% less than NBS-DRX with 18% less resource utilization.
Keywords
3GPP, 5G mobile communication, 5G NR, Array signal processing, Bandwidth, Beam-Aware, Beam-Search, Cellular networks, Delays, Discontinuous Reception (DRX), Long Term Evolution, Non-Standalone NR-U, NR-Unlicensed (NR-U), semi-Markov, Standalone NR-U
Department
Computer Science
Recommended Citation
Mukesh Kumar Maheshwari, Eshita Rastogi, Abhishek Roy, Navrati Saxena, and Dong Ryeol Shin. "DRX in NR Unlicensed for B5G Wireless: Modeling and Analysis" IEEE Transactions on Mobile Computing (2022). https://doi.org/10.1109/TMC.2022.3168510