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Journal Article Performance Improvement of Random Access by Prioritizing Collisions
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Authors
Yunbae Kim, Seungkeun Park
Issue Date
2023-05
Citation
IEEE Access, v.11, pp.49895-49912
ISSN
2169-3536
Publisher
Institute of Electrical and Electronics Engineers Inc.
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1109/ACCESS.2023.3278260
Project Code
23HH2900, Development of Incumbent Radio Stations Protection and Frequency Sharing Technology through Spectrum Challenge, Seung Keun Park
Abstract
The importance of unlicensed spectrum is highlighted in terms of the flexibility of network deployment for various services envisioned in 5G and beyond. Since listen before talk is mandatory for channel access in unlicensed spectrum and it causes an unavoidable waste of resources due to collisions, an efficient random backoff mechanism is required. In the existing backoff schemes that impose waiting penalties on collided packets, a degraded fairness performance is observed. In this work, we analyze how prioritizing collided packets can improve performance compared to existing schemes. To this end, we devise a random backoff scheme called the Collision Priority Backoff (CPB) under the concept of giving priority to collided packets. We apply Bayesian optimization to carefully determine channel access parameters of the CPB to maximize network throughput. Since the optimized access parameters require the number of stations in the network, we also devise an adaptive version of the CPB called the Adaptive CPB (ACPB). We deal with an environment where the number of stations changes as a switching bandit problem, and employ a variant of upper confidence bound policy in the ACPB. Various simulation results validate that the proposed backoff scheme shows high throughput and fairness performance.
KSP Keywords
5G and beyond, Backoff mechanism, Bayesian Optimization, Channel Access(CA), Collision Priority, Existing schemes, High throughput(HTP), Listen before talk, Network throughput, Random Access, Upper Confidence Bound(UCB)
This work is distributed under the term of Creative Commons License (CCL)
(CC BY NC ND)
CC BY NC ND