【24h】

Multicast throughput optimization and fair spectrum sharing in cognitive radio networks

机译:认知无线电网络中的组播吞吐量优化和公平频谱共享

获取原文

摘要

By enabling opportunistic secondary users' (SUs) usage of licensed spectrum, cognitive radio (CR) technology notably improves spectrum utilization. However, the fundamental multicast throughput optimization problem in cognitive radio networks (CRNs) is still under-explored. Considering spectrum availability and sharing fairness, in this paper, we propose a cross-layer approach to maximize the multicast throughput in multi-hop CRNs. We introduce a new service provider, called secondary service provider (SSP), to harvest the available spectrum and allocate the collected bands among SUs. The SSP also guides the transmissions of multicast CR sessions w.r.t. their contention and spectrum sharing fairness. Leveraging the proposed palmier structure for the multicast session and the multi-radio multi-band multicast (M3) conflict graph, we mathematically characterize the multicast flow routing and link scheduling, respectively. Based on the proportional fairness model, we formulate the multicast maximization problem under multiple cross-layer constraints in CRNs, and provide near-optimal solutions. Through simulations, we show that the performance of the proposed scheme is much better than that of schemes without cross-layer consideration.
机译:通过允许机会性第二用户(SU)使用许可频谱,认知无线电(CR)技术显着提高了频谱利用率。但是,认知无线电网络(CRN)中基本的多播吞吐量优化问题仍未得到充分研究。考虑到频谱可用性和共享公平性,在本文中,我们提出了一种跨层方法来最大化多跳CRN中的多播吞吐量。我们引入了一个称为辅助服务提供商(SSP)的新服务提供商,以收集可用频谱并在SU之间分配收集的频段。 SSP还指导w.r.t.的多播CR会话的传输。它们的竞争和频谱共享的公平性。利用针对多播会话和多无线电多频带多播(M3)冲突图提出的Palmier结构,我们分别对多播流路由和链路调度进行了数学刻画。基于比例公平模型,提出了CRN中多个跨层约束下的组播最大化问题,并提供了接近最优的解决方案。通过仿真,我们证明了所提出方案的性能比不考虑跨层方案的性能要好得多。

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号