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Resource Allocation with Flexible Channel Cooperation in Cognitive Radio Networks

机译:认知无线电网络中具有灵活信道合作的资源分配

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We study the resource allocation problem in an OFDMA-based cooperative cognitive radio network, where secondary users relay data for primary users in order to gain access to the spectrum. In light of user and channel diversity, we first propose FLEC, a novel flexible channel cooperation scheme. It allows secondary users to freely optimize the use of channels for transmitting primary data along with their own, in order to maximize performance. Further, we formulate a unifying optimization framework based on Nash bargaining solutions to fairly and efficiently allocate resources between primary and secondary networks, in both decentralized and centralized settings. We present an optimal distributed algorithm and a suboptimal centralized heuristic, and verify their effectiveness via realistic simulations. Under the same framework, we also study conventional identical channel cooperation as the performance benchmark, and propose algorithms to solve the corresponding optimization problems.
机译:我们研究了基于OFDMA的协作认知无线电网络中的资源分配问题,在该网络中,次要用户为主要用户中继数据,以便获得对频谱的访问权限。鉴于用户和信道的多样性,我们首先提出FLEC,这是一种新颖的灵活的信道合作方案。它允许次要用户自由优化通道及其主要数据传输方式的使用,以最大化性能。此外,我们在纳什讨价还价解决方案的基础上制定了一个统一的优化框架,可以在分散和集中式环境中公平有效地在主次网络之间分配资源。我们提出了一种最优的分布式算法和次优的集中式启发式算法,并通过现实的仿真验证了它们的有效性。在相同的框架下,我们还研究了常规的相同信道协作作为性能基准,并提出了解决相应优化问题的算法。

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