合作感知中基于吞吐量的联合折中优化算法

姬国庆; 王刚; 朱洪波

doi:1000-436X(2011)11-0071-07

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合作感知中基于吞吐量的联合折中优化算法

学术论文 | 更新时间：2024-06-05

- 合作感知中基于吞吐量的联合折中优化算法
- Joint trade-off optimization algorithm based on cooperative spectrum sensing throughput
- 通信学报 2011年32卷第11期页码：71-77
- 作者机构：
  
  1. 南京邮电大学江苏省无线通信重点实验室，江苏南京210003
  2. 中国矿业大学信息与电气工程学院，江苏徐州 221116
- 作者简介：
  
  [ "姬国庆（1972-），男，江苏徐州人，南京邮电大学博士生，主要研究方向为无线通信的信号处理、电磁兼容等。" ]
  [ "王刚（1977-），男，江苏徐州人，中国矿业大学副教授，主要研究方向为无线传感网、物联网技术等。" ]
  [ "朱洪波（1956-），男，江苏扬州人，南京邮电大学教授、博士生导师，南京邮电大学副校长，主要研究方向为通信工程、无线通信与电磁兼容、移动通信与宽带无线技术。" ]
- 基金信息：
  
  国家重点基础研究发展计划(“973”计划)基金资助项目;The National Basic Research Program of China (973 Program)(2007CB310607);国家科技重大专项基金资助项目;The Important National Science and Technology Specific Project(2009ZX03003-002);国家科技重大专项基金资助项目;The Important National Science and Technology Specific Project(2009ZX03007-003);国家自然科学基金资助项目;The National Natural Science Foundation of China(61101104)
- DOI：1000-436X(2011)11-0071-07
  中图分类号： TN92
- 网络出版日期：2011-11，
  
  纸质出版日期：2011-11-25
- 稿件说明：
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姬国庆, 王刚, 朱洪波. 合作感知中基于吞吐量的联合折中优化算法[J]. 通信学报, 2011,32(11):71-77.

Guo-qing JI, Gang WANG, Hong-bo ZHU. Joint trade-off optimization algorithm based on cooperative spectrum sensing throughput[J]. Journal on communications, 2011, 32(11): 71-77.
姬国庆, 王刚, 朱洪波. 合作感知中基于吞吐量的联合折中优化算法[J]. 通信学报, 2011,32(11):71-77. DOI： 1000-436X(2011)11-0071-07.

Guo-qing JI, Gang WANG, Hong-bo ZHU. Joint trade-off optimization algorithm based on cooperative spectrum sensing throughput[J]. Journal on communications, 2011, 32(11): 71-77. DOI： 1000-436X(2011)11-0071-07.

摘要

为实现认知无线电资源开销和系统性能的全面优化，建模研究了基于合作感知的认知网络的有效数据吞吐量。针对软合并融合判决模式，基于认知网络的吞吐量建立了本地采样数与合作用户数的联合折中优化模型。通过非对称步长的Armijo非精确线搜索最速下降算法求出了全局最优解，与蒙特卡洛仿真实验共同验证了优化模型的有效性。在吞吐量的最大化准则下，实现了合作感知中本地采样数与合作用户数的联合折中优化。

Abstract

The achievable data throughput of the cognitive network was modeled to optimize the overhead and performance of the cooperative system thoroughly.Considering the soft data combination decision

the joint trade-off optimization of the local sampling number and cooperative user number was modeled based on the achievable data throughput.The global optimal solution was achieved with inexact line search algorithm

which is based on Armijo rule and lopsided search step technique.Consequently

the validity of the optimization model was verified both by the numerical computation and by Monte-Carlo simulation tests.The joint trade-off optimization of the sampling number and cooperative user number was achieved in cooperative sensing based on the throughput maximizing criterion.

关键词

Keywords

references

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