Open AccessOn the Performance Analysis of UE-VBS-Based Wireless Communications: Network Outages, Resource Utilization and Optimization
Author(s) -
Iacovos Ioannou,
Ala' Khalifeh,
Prabagarane Nagaradjane,
Christophoros Christophorou,
Vasos Vassiliou,
Orestis Neokleous,
Andreas Pitsillides
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3573846
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
User Equipment as a Virtual Base Station (UE-VBS) computing paradigm represents a significant advancement in wireless networking. It enables User Equipment (UE) to form: i) Virtual Base Stations (VBSs) by dynamically integrating Cluster Heads (referred to as UE-VBS CH ), or Virtual Relays (referred to as UE-VBS RL ), in the far-edge domain. This research focuses on enhancing the Quality of Service (QoS) (and thereby improving user experience) in networks supported by UE-VBS computing through outage prediction, network optimization, and advanced wireless techniques. In addition, the paper presents a detailed outage probability analysis and explores the trade-off between efficiency and reliability (namely, spectral and energy efficiency and link-level reliability (outage probability)), which are core contributions of this work. For a representative urban density of 2 UEs per m 2 , a single-hop UE-VBS slice lowers the outage probability from 0.78 to 0.23, raises the peak area-spectral efficiency to 4.3 bit s −1 Hz −1 (≈ 4.8× the baseline), and delivers an energy efficiency of 2.4×10 5 bit J −1 (≈ 4.6× improvement). These concrete figures substantiate the claimed gains and illustrate how UE-VBS computing simultaneously improves efficiency and reliability . Specifically, it provides a thorough examination of UE-VBS computing’s capacity to enhance service quality, reduce congestion, and promote energy efficiency. Also, it empirically confirms UE-VBS computing’s superior performance, including mitigating coverage gaps coverage gaps are localized areas inside a nominally covered cell where received SINR falls below the outage threshold because of shadowing or cell-edge distance), optimizing network traffic, and reducing battery consumption compared to traditional networks/non-UE-VBS computing-supported networks. Enhanced QoS aims to minimize the challenges associated with restricted network coverage, ensuring consistent data transmission rates and improving overall user satisfaction. The potential exists for adopting effective network traffic offloading to mitigate the heavy traffic on primary base stations known as Next Generation Node B (gNodeB). Consequently, this can result in enhanced spectrum utilization and heightened data throughput. Leveraging UE-VBS computing also contributes to power conservation and fosters sustainability.