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Cooperative Resource Sharing and Pricing for Proactive Dynamic Spectrum Access via Nash Bargaining Solution

机译:通过Nash讨价还价解决方案进行主动资源动态访问的合作资源共享和定价

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In this paper, we investigate the cooperative resource sharing and pricing for the licensed Primary User (PU) and Cognitive Radio Networks (CRNs), where the PU jointly determines how to share its under-utilized radio resource with Secondary Users (SUs) and how to charge the SUs accordingly. Meanwhile, the SUs jointly determine how to utilize the shared radio resource from the PU and their preferred payments. Since both the PU and SUs expect to benefit from cooperation, we model their interactions as a Nash bargaining problem. Viewing the nonconvexity of bargaining problem, we first propose a two-step procedure to solve it efficiently. The two-step procedure explores the connection between the bargaining problem and its associated social optimization problem, and thus turns the original nonconvex bargaining problem into two consecutive convex optimization problems. We then propose two efficient algorithms, each with guaranteed convergence, to solve these two problems, respectively. Numerical results show that our proposed two-step procedure achieves the optimality of the bargaining problem with significantly reduced computational complexity. Also, our joint resource sharing and pricing scheme guarantees that each SU and PU can positively benefit from the cooperative bargaining, and the benefit is fairly allocated among them.
机译:在本文中,我们研究了许可的主要用户(PU)和认知无线电网络(CRN)的合作资源共享和定价,其中PU共同确定如何与次要用户(SU)共享其未充分利用的无线电资源以及如何相应地为SU充电。同时,SU共同确定如何利用来自PU的共享无线电资源及其首选付款。由于PU和SU都希望从合作中受益,因此我们将其交互建模为Nash讨价还价问题。鉴于议价问题的非凸性,我们首先提出了两步过程来有效地解决它。两步过程探讨了议价问题及其相关的社会优化问题之间的联系,从而将原始的非凸面议价问题转化为两个连续的凸优化问题。然后,我们提出了两种有效的算法,分别保证了收敛性,以分别解决这两个问题。数值结果表明,我们提出的两步过程实现了讨价还价问题的最优性,大大降低了计算复杂度。此外,我们的联合资源共享和定价方案保证了每个SU和PU都可以从合作谈判中积极受益,并且在其中公平分配利益。

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