TY - GEN
T1 - Fair Coexistence of Heterogeneous Networks
T2 - 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023
AU - Guo, Zhiwu
AU - Zhang, Chicheng
AU - Li, Ming
AU - Krunz, Marwan
N1 - Publisher Copyright:
© 2023 IFIP.
PY - 2023
Y1 - 2023
N2 - The licensed spectrum of cellular networks has become increasingly crowded, leading to the standardization of LTE licensed assisted access (LTE-LAA) and 5G NR-U for deployment in unlicensed bands such as 5 GHz. To coexist harmoniously with other unlicensed wireless technologies like WiFi, LAA and 5G NR-U enforce listen-before-talk (LBT) protocol. This paper proposes methods to enhance the overall spectrum efficiency and fairness of each coexisting heterogeneous link. To improve the overall spectrum efficiency, we propose enabling concurrent transmissions of multiple links. Motivated by the need for fair coexistence of heterogeneous networks with concurrent transmissions, we formulate a variant of the multi-armed bandit (MAB) problem that finds a probabilistic transmission strategy to maximize the minimum link throughput. We propose the Fair Probabilistic Explore-Then-Commit (FP-ETC) algorithm, which achieves the expected regret of O(T 23 (K log T ) 13) . We compare FP-ETC with existing MAB algorithms via extensive simulations, and the results show that FP-ETC significantly outperforms the baseline algorithms.
AB - The licensed spectrum of cellular networks has become increasingly crowded, leading to the standardization of LTE licensed assisted access (LTE-LAA) and 5G NR-U for deployment in unlicensed bands such as 5 GHz. To coexist harmoniously with other unlicensed wireless technologies like WiFi, LAA and 5G NR-U enforce listen-before-talk (LBT) protocol. This paper proposes methods to enhance the overall spectrum efficiency and fairness of each coexisting heterogeneous link. To improve the overall spectrum efficiency, we propose enabling concurrent transmissions of multiple links. Motivated by the need for fair coexistence of heterogeneous networks with concurrent transmissions, we formulate a variant of the multi-armed bandit (MAB) problem that finds a probabilistic transmission strategy to maximize the minimum link throughput. We propose the Fair Probabilistic Explore-Then-Commit (FP-ETC) algorithm, which achieves the expected regret of O(T 23 (K log T ) 13) . We compare FP-ETC with existing MAB algorithms via extensive simulations, and the results show that FP-ETC significantly outperforms the baseline algorithms.
KW - Online learning
KW - explore-then-commit
KW - max-min fairness
KW - probabilistic multi-armed bandit
UR - http://www.scopus.com/inward/record.url?scp=85184660052&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85184660052&partnerID=8YFLogxK
U2 - 10.23919/WiOpt58741.2023.10349867
DO - 10.23919/WiOpt58741.2023.10349867
M3 - Conference contribution
AN - SCOPUS:85184660052
T3 - Proceedings of the International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt
SP - 358
EP - 365
BT - 2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 August 2023 through 27 August 2023
ER -