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Distributed power and channel allocation for cognitive femtocell network using a coalitional game approach

机译:用于使用合立游戏方法的认知毫微微小区网络的分布式电力和信道分配

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The cognitive femtocell network (CFN) integrated with cognitive radio-enabled technology has emerged as one of the promising solutions to improve wireless broadband coverage in indoor environment for next-generation mobile networks. In this paper, we study a distributed resource allocation that consists of subchannel- and power-level allocation in the uplink of the two-tier CFN comprised of a conventional macrocell and multiple femtocells using underlay spectrum access. The distributed resource allocation problem is addressed via an optimization problem, in which we maximize the uplink sum-rate under constraints of intra-tier and inter-tier interferences while maintaining the minimum rate requirement of the served femto users. Specifically, the aggregated interference from cognitive femto users to the macrocell base station is also kept under an acceptable level. We show that this optimization problem is NP-hard and propose a distributed framework to maximize the sum-rate of network based on coalitional game in partition form. The proposed framework is tested based on the simulation results and shown to perform efficient resource allocation.
机译:与认知无线电技术集成的认知毫微微小区网络(CFN)已成为改善下一代移动网络的室内环境中的无线宽带覆盖的有希望的解决方案之一。在本文中,我们研究了一个分布式资源分配,该资源分配包括使用底层频谱接入的传统宏小区和多个毫微微小区的两层CFN的上行链路中的子信道和功率级分配。通过优化问题解决了分布式资源分配问题,其中我们在层内和层间干扰的约束下最大化上行链路和速率,同时保持服务的毫微微用户的最小速率要求。具体地,来自认知毫微微用户到宏小区基站的聚合干扰也保持在可接受的水平下。我们表明,这种优化问题是NP-Hard,并提出了一种分布式框架,以最大化基于分配形式的独立游戏的网络的总和率。基于模拟结果测试所提出的框架,并显示用于执行有效的资源分配。

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