[1]田峰,朱雯君. 基于信干噪比模型的多跳认知网络速率优化[J].计算机技术与发展,2016,26(08):113-118.
　TIAN Feng,ZHU Wen-jun. Rate Optimization Based on SINR in Cognitive Radio Network[J].,2016,26(08):113-118.
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 基于信干噪比模型的多跳认知网络速率优化()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年08期
页码:
113-118
栏目:
应用开发研究
出版日期:
2016-08-10

文章信息/Info

Title:
 Rate Optimization Based on SINR in Cognitive Radio Network
文章编号:
1673-629X（2016)08-0113-06
作者:
 田峰; 朱雯君
 南京邮电大学 通信与信息工程学院
Author(s):
 TIAN Feng; ZHU Wen-jun
关键词:
 ; 多跳认知网络; 重构线性化技术; 信干噪比模型; 速率
Keywords:
 ; multi-hop cognitive radio network; RLT; SINR; rate
分类号:
TP39
文献标志码:
A
摘要:
 随着无线通信技术的迅速发展,频谱短缺问题日益突出。认知无线电技术作为缓解频谱供需矛盾的重要技术受到了广泛关注。文中综合研究了多跳认知网络的物理层、链路层及网络层的限制,以信干噪比( Signal to Interference plus Noise Ratio,SINR)模型下多跳认知网络的速率问题为优化目标,形成混合整数非线性规划( MINLP)问题。针对该问题,通过重构线性化技术( RLT)实现线性松弛,得到问题的最优解。仿真验证了该方法的有效性及多跳认知网络跨层设计对系统性能的影响,实现了认知网络速率优化的目标。
Abstract:
 With the rapid development of wireless communication,problem of spectrum scarcity is becoming more and more prominent. Cognitive radio network,as an important technology to ease the contradiction between supply and demand,has been widely followed. In this paper,the constraints of physical,link and network layers is researched comprehensively with objective of maximizing rate in cogni-tive radio networks under Signal to Interference plus Noise Ratio ( SINR) . The problem is formed of mixed integer nonlinear program. To solve the problem,a Reformulation Linearization Technique ( RLT) is adopted and optimal solution for it is obtained. Simulation demon-strates the efficacy of the solution procedure,offering the benefit for cross-layer design and achieving the goal of rate optimization for cognitive radio network.

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更新日期/Last Update: 2016-09-29