吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (5): 1481-1487.doi: 10.7964/jdxbgxb201405041

• • 上一篇    下一篇

基于DF中继的认知OFDM协作系统的资源分配算法

赵晓晖, 沙京祺   

  1. 吉林大学 通信工程学院信息科学实验室,长春 130012
  • 收稿日期:2013-05-15 出版日期:2014-09-01 发布日期:2014-09-01
  • 作者简介:赵晓晖(1957), 男, 教授, 博士生导师.研究方向:信号处理理论在通信中的应用.E-mail:xhzhao@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(61171079).

Resource allocation algorithm in DF relay assisted OFDM cognitive radio systems

ZHAO Xiao-hui,SHA Jing-qi   

  1. Laboratory of Information Science, College of Communication Engineering, Jilin University, Changchun 130012, China
  • Received:2013-05-15 Online:2014-09-01 Published:2014-09-01

RICH HTML

0   

PDF (PC)

418

摘要： 针对多中继认知OFDM协作系统的中继和功率分配采用的拉格朗日对偶分解法虽然具有较好的性能,但计算复杂度较高这一问题,提出了一种低复杂度的资源分配算法。该算法放宽了中继选择因子的整数约束条件,综合考虑认知用户各子载波的信道条件和对主用户的干扰进行中继选择。根据系统总功率和干扰约束的特点,提出一种次优功率分配算法对功率进行分步求解,在保证系统容量有所增加的基础上降低了算法的计算复杂度。仿真结果表明:本文提出的算法不仅保证了认知用户对主用户产生的干扰在临界值以内,而且使认知用户的系统容量得到了较大的提升,具有一定的可行性。

关键词: 通信技术, 多中继OFDM系统, 认知无线电, 中继选择, 功率分配

Abstract: For resource allocation in multi-relay assisted OFDM radio systems, most current relay and power allocation algorithms use Lagrangian dual decomposition technique to find the optimal solutions. This approach has good performance but the computational complexity is higher. To solve this problem, a resource allocation algorithm with low computational complexity is proposed. The proposed algorithm relaxes the integrality constraint on the relay selection factor. It takes both subcarriers channel conditions and the interference to the primary users introduced by the secondary users into account in the relay selection. A sub-optimal power allocation scheme is given on the basis of the properties of the total system power and interference constraints, in which the power allocation is conducted step by step. The system capacity is guaranteed with lower computational complexity. Simulation results show that the proposed algorithm can ensure that the interference introduced to the primary users is within the threshold, and can also improve the system capacity of the secondary users at the same time. Thus, the feasibility of the proposed algorithm is verified.

Key words: communication technology, multi-relay-assisted OFDM systems, cognitive radio, relay selection, power allocation

中图分类号: 

  • TN929
[1] Mahmoud H, Yucek T, Arslan H. OFDM for cognitive radio: merits and challenges[J]. IEEE Wireless Communications, 2009, 16(2): 6-15.
[2] Stuber G L, Barry J R, Mclaughlin S W, et al. Broadband MIMO-OFDM wireless communications[J].Proceedings of the IEEE, 2004, 92(2): 271-294.
[3] Rayliu K J, Sadke A, Su Wei-feng, et al. Cooperative Communications and Networking[M].Cambridge:Cambridge University Press, 2009.
[4] Liu Yong, Chen Wen. Limited-feedback-based adaptive power allocation and subcarrier pairing for OFDM DF relay networks with diversity[J]. IEEE Transactions on Vehicular Technology, 2012, 61(6): 2559-2571.
[5] Li Yong-hui, Vucetic B, Zhou Zhen-dong, et al. Distributed adaptive power allocation for wireless relay networks[J]. IEEE Transactions on Wireless Communications, 2007,6(3): 948-958.
[6] Shaat M, Bader F. Joint subcarrier pairing and power allocation for DF-relayed OFDM cognitive systems[C]∥IEEE Global Telecommunications Conference,Houston, Texas, USA, 2011: 1-6.
[7] Letaief K, Zhang Wei. Cooperative communications for cognitive radio networks[J]. Proceedings of the IEEE,2009, 97(5):878-893.
[8] Sidhu G A S, Gao Feifei, Chen Wen, et al. Joint subcarrier pairing and power loading in relay aided cognitive radio networks[C]∥Wireless Communications and Networking Conference,Shanghai, 2012: 669-673.
[9] Shaat M, Bader F. Asymptotically optimal resource allocation in OFDM-based cognitive networks with multiple relays[J]. IEEE Transactions on Wireless Communications, 2012, 11(3):892-897.
[10] Bharadia D, Bansal G, Kaligineedi P, et al. Relay and power allocation schemes for OFDM-based cognitive radio systems[J]. IEEE Transactions on Wireless Communications, 2011, 10(9):2812-2817.
[11] Boyd S, Vandenberghe L. Convex Optimization[M]. Cambridge: Cambridge University Press, 2004.
[1] 周彦果,张海林,陈瑞瑞,周韬. 协作网络中采用双层博弈的资源分配方案[J]. 吉林大学学报(工学版), 2018, 48(6): 1879-1886.
[2] 孙晓颖, 扈泽正, 杨锦鹏. 基于分层贝叶斯网络的车辆发动机系统电磁脉冲敏感度评估[J]. 吉林大学学报(工学版), 2018, 48(4): 1254-1264.
[3] 董颖, 崔梦瑶, 吴昊, 王雨后. 基于能量预测的分簇可充电无线传感器网络充电调度[J]. 吉林大学学报(工学版), 2018, 48(4): 1265-1273.
[4] 牟宗磊, 宋萍, 翟亚宇, 陈晓笑. 分布式测试系统同步触发脉冲传输时延的高精度测量方法[J]. 吉林大学学报(工学版), 2018, 48(4): 1274-1281.
[5] 丁宁, 常玉春, 赵健博, 王超, 杨小天. 基于USB 3.0的高速CMOS图像传感器数据采集系统[J]. 吉林大学学报(工学版), 2018, 48(4): 1298-1304.
[6] 陈瑞瑞, 张海林. 三维毫米波通信系统的性能分析[J]. 吉林大学学报(工学版), 2018, 48(2): 605-609.
[7] 张超逸, 李金海, 阎跃鹏. 双门限唐检测改进算法[J]. 吉林大学学报(工学版), 2018, 48(2): 610-617.
[8] 关济实, 石要武, 邱建文, 单泽彪, 史红伟. α稳定分布特征指数估计算法[J]. 吉林大学学报(工学版), 2018, 48(2): 618-624.
[9] 李炜, 李亚洁. 基于离散事件触发通信机制的非均匀传输网络化控制系统故障调节与通信满意协同设计[J]. 吉林大学学报(工学版), 2018, 48(1): 245-258.
[10] 孙晓颖, 王震, 杨锦鹏, 扈泽正, 陈建. 基于贝叶斯网络的电子节气门电磁敏感度评估[J]. 吉林大学学报(工学版), 2018, 48(1): 281-289.
[11] 武伟, 王世刚, 赵岩, 韦健, 钟诚. 蜂窝式立体元图像阵列的生成[J]. 吉林大学学报(工学版), 2018, 48(1): 290-294.
[12] 袁建国, 张锡若, 邱飘玉, 王永, 庞宇, 林金朝. OFDM系统中利用循环前缀的非迭代相位噪声抑制算法[J]. 吉林大学学报(工学版), 2018, 48(1): 295-300.
[13] 王金鹏, 曹帆, 贺晓阳, 邹念育. 基于多址干扰和蜂窝间互扰分布的多载波系统联合接收方法[J]. 吉林大学学报(工学版), 2018, 48(1): 301-305.
[14] 石文孝, 孙浩然, 王少博. 无线Mesh网络信道分配与路由度量联合优化算法[J]. 吉林大学学报(工学版), 2017, 47(6): 1918-1925.
[15] 姜来为, 沙学军, 吴宣利, 张乃通. LTE-A异构网络中新的用户选择接入和资源分配联合方法[J]. 吉林大学学报(工学版), 2017, 47(6): 1926-1932.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发