期刊文献+

认知星地混合网络中基于干扰约束的最优功率控制方法

Optimal power control based on interference power constraint in cognitive satellite terrestrial networks
下载PDF
导出
摘要 在认知星地混合网络中,当卫星用户作为次级用户时,为了不影响地面主用户系统的正常工作,在上行链路中要对卫星用户进行必要的功率控制。针对衰落信道场景,选择最大化卫星用户的遍历容量(EC)作为优化的目标函数,分别提出了基于峰值干扰功率约束(PIC)和平均干扰功率约束(AIC)的功率控制方法,并给出了最优发射功率的闭合表达式。仿真结果表明,卫星信道条件越好、地面干扰链路衰减越大,卫星用户的性能越好;除此之外,基于AIC的功率控制方法要优于基于PIC的功率控制方法。 In cognitive satellite terrestrial networks, when the satellite users are secondary users, power control is necessary to guarantee the communication quality of terrestrial primary user in the uplink case. In the context of fading channels, maximizing the Ergodic Capacity( EC) of the satellite user was selected as the objective function, then two optimal power control schemes were proposed based on Peak Interference power Constraint( PIC) and Average Interference power Constraint( AIC), respectively. Meanwhile, the closed expression of the optimal transmit power was given. Simulation results show that the ergodic capacity of satellite user can be increased when the satellite link experiences the weaker shadowing conditions; moreover, under the the specific satellite link condition, the performance of satellite user becomes better with the increasing of the terrestrial interference link fading parameters. In addition, power control method based on AIC is superior to that based on PIC.
出处 《计算机应用》 CSCD 北大核心 2017年第8期2173-2176,2183,共5页 journal of Computer Applications
基金 国家自然科学基金资助项目(61571464 61601511 91338201 91438109 61401507)~~
关键词 认知卫星 遍历容量 峰值干扰功率约束 平均干扰功率约束 功率控制 cognitive satellite Ergodic Capacity(EC) Peak Interference power Constraint(PIC) Average Interference power Constraint(AIC) power control
  • 相关文献

参考文献1

二级参考文献26

  • 1张更新,甘仲民.浅论我国卫星移动通信系统的发展思路和策略[J].数字通信世界,2005(7):24-27. 被引量:15
  • 2王红霞,潘成胜,宋建辉.星载智能天线波束形成技术[M].北京:国防工业出版社,2013.
  • 3HAYKIN S. Cognitive radio: brain-empowered wireless communica-tions[J]. IEEE Journal on Selected Areas in Communications, 2005,23(2):201-220.
  • 4YIU S, VU M, TAROKH V. Interference and noise reduction bybeamforming cognitive networks [J]. IEEE Transactions on Commu-nications, 2009,57(10):3144-3153.
  • 5LUAN T,GAO F,ZHANG X D, et al. Rate maximization and beam-forming design for relay-aided multiuser cognitive networks[J]. IEEETransactions on Vehicle Technology, 2012,61(4): 1940-1945.
  • 6CUMANAN K, MUSAVIAN L, LAMBOTHARAB S, et al SINRbalancing technique for downlink beamforming cognitive radio net-works[J]. IEEE Signal Processing Letters, 2010,17(2):133-136.
  • 7AKIN S,GURSOY M C. On the throughput and energy efficiency ofcognitive MIMO transmissions[J]. IEEE Transactions on VehicleTechnology, 2013,62(7):3245-3260.
  • 8CoRAS AT [EB/OL]. http://www.ict-corasat.eu. 2012-10-01/ 2014-03-26.
  • 9LIOLOS K, SCHLUETER G, KRAUSE J, et al. Cognitive radioscenarios for satellite communications: the CoRaSat approach[A].Proceedings of Future Network and Mobile Summit[C]. Lisbon, Por-tugal: IEEE, 2013.1-10.
  • 10马陆,陈晓挺,刘会杰等.认知无线电技术在低轨通信卫星系统中的应用研究[A].第六届卫星通信新业务新技术学术年会[C].北京,中国,2010.270-277.

共引文献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