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Coexistence of 5G new radio unlicensed (NR-U) and Wi-Fi is highly prone to the collisions among NR-U gNBs (5G base stations) and Wi-Fi APs (access points). To improve performance and fairness for both networks, various collision resolution mechanisms have been proposed to replace the simple listen-before-talk (LBT) scheme used in the current 5G standard. We address two gaps in the literature: first, the lack of a comprehensive performance comparison among the proposed collision resolution mechanisms and second, the impact of multiple traffic priority classes. Through extensive simulations, we compare the performance of several recently proposed collision resolution mechanisms for NR-U/Wi-Fi coexistence. We extend one of these mechanisms to handle multiple traffic priorities. We then develop a traffic-aware multi-objective deep reinforcement learning algorithm for the scenario of coexistence of high-priority traffic gNB user equipment (UE) with multiple lower-priority traffic UEs and Wi-Fi stations. The objective is to ensure low latency for high-priority gNB traffic while increasing the airtime fairness among the NR-U and Wi-Fi networks. Our simulation results show that the proposed algorithm lowers the channel access delay of high-priority traffic while improving the fairness among both networks.
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RanCAD: Random Channel Access Deterrence Attack against Spectrum Coexistence between NR-U and Wi-Fi on the 5GHz Unlicensed Band
Spectrum coexistence between 5G and Wi-Fi in the coveted 5GHz spectrum band unleashes new possibilities for more effective spectrum utilization. While the Listen-Before-Talk-based channel access mechanism with the self-deferral-based method enhances the relative fairness of this coexistence framework, it introduces new vulnerabilities yet to be addressed. This research presents a unique attack approach, Random Channel Access Deterrence (RanCAD), that exploits a novel vulnerability in the channel access mechanism. In the proposed attack, a malicious access point deceives a victim 5G base station into deferring its access to the shared channel, resulting in higher channel access delay and lower spectrum utilization. In addition, we propose a Discrete Time Markov Chain (DTMC) to study the proposed attack model, which helps illustrate the attack's impact on the victim's performance. To our knowledge, this is the first work to introduce this vulnerability in the channel access mechanism between coexisting 5G and Wi-Fi networks in the 5GHz band.
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- Award ID(s):
- 2304668
- PAR ID:
- 10538959
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- IEEE International Conference on Communications
- ISSN:
- 1938-1883
- ISBN:
- 978-1-7281-9054-9
- Page Range / eLocation ID:
- 2107 to 2112
- Format(s):
- Medium: X
- Location:
- Denver, CO, USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICC51166.2024.10622917
