We address the problem of resource allocation (RA) in a cognitive radio (CR) communication system with multiple secondary operators sharing spectrum with an incumbent primary operator. The key challenge of the RA problem is the inter-operator coordination arising in the optimization problem so that the aggregated interference at the primary users (PUs) does not exceed the target threshold. While this problem is easily solvable if a centralized unit could access information of all secondary operators, it becomes challenging in a realistic scenario. In this paper, considering a satellite setting, we alleviate this problem by proposing two approaches to reduce the information exchange level among the secondary operators. In the first approach, we formulate an RA scheme based on a partial information sharing method which enables distributed optimization across secondary operators. In the second approach, instead of exchanging secondary users (SUs) information, the operators only exchange their contributions of the interference-level and RA is performed locally across secondary operators. These two approaches, for the first time in this context, provide a trade-off between performance and level of inter-operator information exchange. Through the numerical simulations, we explain this trade-off and illustrate the penalty resulting from partial information exchange.
A Proposed Sub-optimal Power Allocation using Simulated Annealing in Cognitive Radio Networks
随着无线业务需求的增长和无线设备数量的增加，可用频段的不足制约了无线通信的进一步发展，认知无线电（Cognitive Radio，CR）因其能够充分利用授权频段的频谱资源而被认为是一种很有前途的解决方案。正交频分复用（Orthogonal Frequency Division Multiplexing，OFDM）技术因其在动态环境下灵活分配可用频谱的能力而成为CR的使能技术。本文提出了一种基于模拟退火算法的认知无线电网络（CRN）下行链路分布式资源分配框架。该算法以较小的计算复杂度最大化SU的总传输容量。此外，将考虑从其他次用户（SU）引入的干扰。为了便于比较，将使用拉格朗日对偶方法。仿真结果表明，与拉格朗日对偶方法相比，该算法具有更好的传输容量。被考虑用于比较的参数是最大发射功率、主用户（PU）的数量和SU的数量。
