Joint Fair Resource Allocation for Opportunistic Spectrum Sharing in OFDM-based Cognitive Radio Networks

Yanbo Ma, Piming Ma, Haixia Zhang
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引用次数: 2

Abstract

This paper considers a cooperative Orthogonal Frequency Division Multiplexing (OFDM)-based cognitive radio network, where the primary system leases a fraction of its subcarriers to the secondary system in exchange for the secondary users (SUs) acting as decode-and-forward relays. Our aim is to determine an fair resource allocation strategy among the primary users and SUs as so to maximize the network capacity. To this end, a network utility maximization optimization problem of power, subcarrier allocation and relay selection is formulated based on a class of α-fair utility. This problem is solved by applying the lagrangian dual method and a joint fair resource allocation policy at the SUs is derived in a closed-form expression. Moreover, a novel stochastic algorithm is developed to approach the optimal policy by dynamically learning the intended wireless channels. Simulation results demonstrate that both primary and secondary systems can benefit from the proposed resource allocation policy.
基于ofdm的认知无线网络中机会频谱共享的联合公平资源分配
本文研究了一种基于正交频分复用(OFDM)的协作式认知无线网络,其中主系统将其部分子载波租给辅助系统,以换取辅助用户(su)充当解码转发中继。我们的目标是在主要用户和单元之间确定公平的资源分配策略,从而最大化网络容量。为此,提出了基于一类α-公平效用的功率、子载波分配和中继选择的网络效用最大化优化问题。应用拉格朗日对偶方法解决了这一问题,并以封闭形式导出了su的联合公平资源分配策略。此外,还提出了一种新的随机算法,通过动态学习预期的无线信道来逼近最优策略。仿真结果表明,主系统和辅助系统都能从所提出的资源分配策略中获益。
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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