基于能量收割的认知无线电预编码优化

删除或更新信息，请邮件至freekaoyan#163.com(#换成@)

清华大学辅仁网/2017-07-07

基于能量收割的认知无线电预编码优化

朱锐^1,²,李云洲¹(

),王京¹

2. 空军工程大学信息对抗系, 陕西 710077

Optimal precoding for energy harvesting cognitive radio

Rui ZHU^1,²,Yunzhou LI¹(

),Jing WANG¹

1. State Key Laboratory of Microware and Digital Communication, Tsinghua National Laboratory for Information Science andTechnology, State Key Laboratory of Wireless Mobile Communications, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
2. Department of information Countermeasure, Air Force Engineering University, Shannxi 710077, China

摘要:

HTML
输出: BibTeX | EndNote (RIS) 背景资料

文章导读

摘要认知无线电(cognitive radio, CR)和能量收割(energy harvesting, EH)技术是提高频谱效率,实现绿色通信的重要手段。但是目前一般将CR和EH作为两个不同的对象分别进行研究。少部分将CR和EH联合研究的工作又均基于输入信号服从Gauss分布的假设。这些不足严重地限制了CR-EH技术在实际情况中的应用。该文基于目前大多数数字通信信号服从的等概率有限字符集分布,分析了EH-CR系统的信道容量,给出了一种基于随机动态规划的预编码算法,提高了EH-CR系统的实用性。仿真结果表明: 该算法可以有效地逼近EH-CR系统所能达到的信道容量上界。

关键词 ：认知无线电,能量收割,随机动态规划

Abstract：Cognitive radio (CR) can effectively improve spectrum efficiencies while energy harvesting (EH) gives green communications. However, these methods have always been analyzed separately. The small amount of combined research has used the Gaussian input assumption. These drawbacks limit practical applications of combined systems. This study analyzed a combined system using the equip probability finite-alphabet input assumption which is more suitable for digital communication signals. A pre-coder algorithm was developed based on the stochastic dynamic program to improve the system utility. Numerical results show that the algorithm performance approaches the channel capacity upper bound for the combined system.

Key words：cognitive radio energy harvesting stochastic dynamic program

收稿日期: 2013-10-25 出版日期: 2015-04-16

基金资助:国家自然科学基金资助项目 (61021001);北京自然科学基金项目 (4110001);国家 “九七三” 重点基础研究项目 (2012CB316000);国家 “八六三” 高技术项目(2012AA011402)

引用本文:

朱锐,李云洲,王京. 基于能量收割的认知无线电预编码优化[J]. 清华大学学报（自然科学版）, 2014, 54(4): 407-412.
Rui ZHU,Yunzhou LI,Jing WANG. Optimal precoding for energy harvesting cognitive radio. Journal of Tsinghua University(Science and Technology), 2014, 54(4): 407-412.

链接本文:

http://jst.tsinghuajournals.com/CN/或 http://jst.tsinghuajournals.com/CN/Y2014/V54/I4/407

图表:

EH-CR网络拓扑结构

EH系统示意图

输入信号服从2元等概分布时,不同SNR条件下的信道容量

输入信号服从2元等概率时,不同时隙条件下的信道容量

输入信号服从2元等概率时,不同最小信道容量条件下的电池容量

参考文献:

[1]	Gastpr M. On capacity under receive and spatial spectrum-sharing constraints [J]. IEEE Trans Inf Theory, 2007, 53(2): 471-487.
[2]	Huang J, Berry R, Honig M L. Auction-based spectrum sharing[J]. ACM/Springer Mobile Networks and Applications Journal (MONET), 2006, 11(3): 405-418.
[3]	Yan Y, Huang J, Wang J. Dynamic bargaining for relay based cooperative spectrum sharing[J]. IEEE J Sel Areas Commun, 2013, 31(8):1480-1493.
[4]	Lu X, Erkip E, Wang Y. Power efficient multimedia communication over wireless channels[J]. IEEE J Sel Areas Commun., 2003, 21(5): 1738-1751.
[5]	Cui Q, Jantti R, Tao X. Energy-efficient relay selection and power allocation for two-way relay channel with analog network coding[J]. IEEE Communications Letters, 2012, 16(6):816-819
[6]	Ozel O, Ulukus S. Achieving AWGN capacity under stochastic energy harvesting[J]. IEEE Trans Inf Theory, 2012, 58(10): 6471-6483.
[7]	Ozel O, Tutuncuoglu K, Yang J. Transmission with energy harvesting nodes in fading wireless channels: Optimal policies[J]. IEEE J Sel Areas Commun, 2011, 29(8): 1732-1743.
[8]	Chin K, Zhang R. Optimal energy allocation for wireless communications with energy harvesting constraints[J]. IEEE Trans Signal Process, 2012, 60(9): 4808-4818.
[9]	Tutuncuoglu K, Yener A. Optimum transmission policies for battery limited energy harvesting nodes[J]. IEEE Trans Commun, 2012, 11(3): 1180-1189.
[10]	Guo D, Shamai S, Verdú S. Mutual information and minimum mean-square error in Gaussian channels[J]. IEEE Trans Inf Theory, 2005, 51(4): 1261-1282.
[11]	Cheng H, Zheng Y, Rosa M. Globally optimal linear precoders for finite alphabet signals over complex vector Gaussian channels[J]. IEEE Trans on signal processing, 2011, 59(7):3301-3314.
[12]	Zeng W, Xiao C, Lu J. Globally optimal precoder design with finite-alphabet input for cognitive radio networks[J]. IEEE Selected area in communications, 2012, 30(10): 1861-1874.
[13]	Zeng W, Xiao C, Wang M.et al.Linear precoding for finite- alphabet inputs over MIMO fading channels with statistical CSI[J]. IEEE Trans Signal Process, 2012, 60(6): 3134-3148.
[14]	Lozano A, Tulino A, Verdú S. Optimum power allocation for parallel Gaussian channels with arbitrary input distribu- tions[J]. IEEE Trans Inf Theory, 2006, 52(7): 3033-3051.

No related articles found!