Energy Detection Adjustment for Fair Coexistence of Wi-Fi and LAA: A Unimodal Bandit Approach

2019 IEEE 5th International Conference on Computer and Communications (ICCC) Pub Date : 2019-12-01 DOI:10.1109/ICCC47050.2019.9064394

Xinghui Gao, H. Qi, X. Wen, Wei Zheng, Zhaoming Lu, Zhiqun Hu

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引用次数: 4

Abstract

Toward fair coexistence with Wi-Fi, the Listen-Before-Talk (LBT) procedure has been recommended for Licensed-assisted access (LAA) in 3GPP Release 13. The energy detection threshold determines the access opportunity of LAA nodes, which plays a critical role in fairness performance on coexistence network between Wi-Fi and LAA. In this paper, an energy detection dynamic adjustment based on Unimodal Bandits (EDDA-UB) algorithm is proposed to optimize energy detection threshold for LAA eNBs. First, the impact of LAA deployment on Wi-Fi is formulated as the optimal problem with considering the fairness. To solve it, the EDDA-UB algorithm is proposed to learn the optimal energy detection threshold in time varying environment. Simulation results show that the proposed algorithm has a better convergence. Compared with existing constant or adaptive energy detection algorithm, the proposed EDDA-UB algorithm shows the superiority on fair performance and improves the network performance in throughput.

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Wi-Fi和LAA公平共存的能量检测调整:单峰强盗方法

为了与Wi-Fi公平共存，3GPP第13版建议在许可辅助接入(LAA)中使用先听后谈(LBT)过程。能量检测阈值决定了LAA节点的接入机会，对Wi-Fi与LAA共存网络的公平性能起着至关重要的作用。本文提出了一种基于单峰强盗(EDDA-UB)算法的能量检测动态调整，以优化LAA eNBs的能量检测阈值。首先，将LAA部署对Wi-Fi的影响表述为考虑公平性的最优问题。为了解决这一问题，提出了EDDA-UB算法，学习时变环境下的最优能量检测阈值。仿真结果表明，该算法具有较好的收敛性。与现有的恒定或自适应能量检测算法相比，EDDA-UB算法在公平性能上具有优势，在吞吐量上提高了网络性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 IEEE 5th International Conference on Computer and Communications (ICCC)

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