期刊文献+

考虑业务优先级的多信道CRANET合作动态功率控制 被引量:1

Cooperative dynamic power control with prioritized traffic in multi-channel CRANET
下载PDF
导出
摘要 针对多信道认知自组织网络(CRANET)中不同业务接入类型的优先级对次用户(SU)发射功率的影响,设计了次用户间业务传输的优先级感知因子,考虑到对主用户系统产生的累积干扰量约束,采用微分博弈建立了合作动态功率控制模型(CoDPCM),获得在总联盟下的合作动态功率控制最优解,同时,考虑到自私次用户的非合作性,建立了非合作动态功率控制模型(NoCoDPCM),获得了反馈Nash(纳什)均衡解,并从理论上进行了性能比较。仿真结果表明,与非合作动态功率控制模型相比,合作动态功率控制模型在发射功率、支付量和系统总体吞吐量等方面表现出较好性能。 Aiming at the impact of the priorities of differentiated access categories of data traffic on the transmitted power of secondary" users (SU) in multi-channel cognitive radio Ad Hoe network (CRANET), the priority sensing factor for data transfer of SU was devised. Under the constraint of the accumulated power interference to primary users, the cooperative dynamic power control model (CoDPCM) was proposed by using differential game, and the optimal solution of the CoDPCM was derived under grand coalition. Moreover, due to the non-cooperation of the selfish SU, the non-cooperative dynamic power control model (NoCoDPCM) was also constructed, and the feedback Nash equilibrium solution was obtained. Theoretically, the performanee comparison was investigated. Simulation results demonstrated that the CoDPCM can achieve better performance than the NoCoDPCM in the case of transmitted power, payoff and total throughput.
出处 《电信科学》 北大核心 2016年第7期45-52,共8页 Telecommunications Science
基金 国家自然科学基金资助项目(No.61402147) 河北省自然科学基金资助项目(No.F2013402039) 河北省科学技术研究与发展计划基金资助项目(No.15214404D-1) 河北省高等学校科学技术研究计划基金资助项目(No.QN20131048)~~
关键词 认知无线电 自组织网络 功率控制 业务优先级 微分博弈 cognitive radio, Ad Hoc network, power control, prioritized traffic, differential game
  • 相关文献

参考文献2

二级参考文献21

  • 1Mitola J and Maguire G. Cognitive radio: making software radios more personal. IEEE Personal Communications, 1999, 6(4): 13-18.
  • 2Haykin S. Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 2005, 23(2): 201-220.
  • 3Neel J. Analysis and design of cognitive radio networks and distributed radio resource management algorithms. [Ph.D dissertation], Virginia Polytechnic Institute and State University, 2006.
  • 4Niyato D and Hossain E. Radio resource management games in wireless networks:an approach to bandwidth allocation and admission control for polling service in IEEE 802.16. IEEE Wireless Communications, 2007, 14(1): 27-35.
  • 5Yeung D and Petrosyan L. Cooperative Stochastic Differential Games. New York: Springer, 2005, Chap. 2 & 3.
  • 6Qiu x and Chawla K. On the performance of adaptive modulation in cellular systems. IEEE Transactions on Communications, 1999, 47(6): 884-895.
  • 7Koskie S and Gajic Z. A Nash game algorithm for SIR-based power control in 3G wireless CDMA networks. IEEE/ACM Transactions on Networking, 2005, 13(5): 1017-1026.
  • 8FCC 02-155. Federal Communications Commission. Spectrum Policy Task Force Report, Nov 2002.
  • 9Haykin S. Cognitive radio: brain-empowered wireless IEEE Journal Selected Areas in Communications, 2005, 23(2): 201-220.
  • 10Aldhaibani J A, Yahya A, Ahmad R B, et ol. Effect of relay location on two-way DF and AF relay for muhi-user system in LTE-A cellular networks. Proceedings of 2013 IEEE Business Engineering and Industrial Applications Colloquium, Langkawi, Malaysia, 2013.

共引文献5

同被引文献6

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部