Distributed resource allocation with fairness for cognitive radios in wireless mobile ad hoc networks

Distributed resource allocation with fairness for cognitive radios in wireless mobile ad hoc networks
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无线移动自组织网络中认知无线电的公平分布式资源分配

DOI:
10.1007/s11276-011-0360-9
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发表时间:
2011-08
期刊:
影响因子:
3
通讯作者:
Liao, Xiaofeng
Liao, Xiaofeng
中科院分区:
计算机科学4区
文献类型:
--
作者:
Guo, Songtao;Dang, Chuangyin;Liao, Xiaofeng

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频谱感知和功率分配对无线认知自组织网络的性能有着至关重要的影响。为了获得最佳的可用子载波集和传输功率,本文提出了一种分布式资源分配框架的认知ad hoc网络使用正交频分多址(OFDMA)调制。该框架集成了服务质量(QoS),最大功率和最低速率的约束。通过在链路容量表达式中引入子载波被占用的概率,保证了资源分配的公平性。一个增量次梯度方法被应用到解决最大化的所有链路的加权和容量的优化问题,没有或有公平性约束。给出了分布式子载波选择和功率分配算法。仿真结果表明,该方法收敛到最优解的速度比普通的次梯度法,并展示了关键参数对系统性能的影响。它已被观察到,在我们的文件中提出的算法优于现有的吞吐量和数量的二级链路接纳和资源分配的公平性。
Both spectrum sensing and power allocation have crucial effects on the performance of wireless cognitive ad hoc networks. In order to obtain the optimal available subcarrier sets and transmission powers, we propose in this paper a distributed resource allocation framework for cognitive ad hoc networks using the orthogonal frequency division multiple access (OFDMA) modulation. This framework integrates together the constraints of quality of service (QoS), maximum powers, and minimum rates. The fairness of resource allocation is guaranteed by introducing into the link capacity expression the probability that a subcarrier is occupied. An incremental subgradient approach is applied to solve the optimization problems that maximize the weighted sum capacities of all links without or with fairness constraints. Distributed subcarrier selection and power allocation algorithms are presented explicitly. Simulations confirm that the approach converges to the optimal solution faster than the ordinary subgradient method and demonstrate the effects of the key parameters on the system performance. It has been observed that the algorithms proposed in our paper outperform the existing ones in terms of the throughput and number of secondary links admitted and the fairness of resource allocation.
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