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Dynamic Access Point and Service Selection in Backscatter-Assisted RF-Powered Cognitive Networks

机译:反向散射辅助射频供电的认知网络中的动态接入点和服务选择

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In this paper, we investigate the dynamic access point and service selection in a backscatter-assisted radio-frequency-powered cognitive network, where many secondary transmitters (STs) can choose different transmission services provided by multiple access points. To analyze the access point and service selection of the STs, we formulate the problem as an evolutionary game. The STs act as the players and adjust their selections of the access points and services based on their utilities. Specifically, we model the access point and service adaptation of the STs by the replicator dynamics, and analytically prove the existence and uniqueness, and the stability of the evolutionary equilibrium. We also consider the delay of information used by the STs to adapt their selection and perform the analysis by using delayed replicator dynamics. In particular, the stability region of the delayed replicator dynamics in a special case is derived. Furthermore, we develop a low-complexity algorithm for the access point and service selection in the network based on evolutionary game. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed access point and service selection strategy in the network.
机译:在本文中,我们研究了反向散射辅助射频供电的认知网络中的动态接入点和服务选择,其中许多次级发射机(ST)可以选择多个接入点提供的不同传输服务。为了分析ST的接入点和服务选择,我们将问题表述为一个演化博弈。 ST充当参与者,并根据其效用调整对接入点和服务的选择。具体来说,我们通过复制器动力学对ST的接入点和服务适应进行建模,并通过分析证明演化均衡的存在性和唯一性以及稳定性。我们还考虑了ST用来适应其选择并通过使用延迟复制器动态进行分析的信息延迟。特别地,导出特殊情况下的延迟复制器动力学的稳定性区域。此外,我们开发了一种基于进化博弈的网络中接入点和服务选择的低复杂度算法。已经进行了广泛的仿真,以证明所提出的接入点和服务选择策略在网络中的有效性。

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