基于QoS需求的认知无线电资源分配算法

doi:10.3969/j.issn.1000-3428.2013.02.017

计算机工程 ›› 2013, Vol. 39 ›› Issue (2): 85-89.doi: 10.3969/j.issn.1000-3428.2013.02.017

基于QoS需求的认知无线电资源分配算法

赵知劲^1,2，赖海超¹，尚俊娜^1,2

(1. 杭州电子科技大学通信工程学院，杭州 310018； 2. 中国电子科技集团公司第36研究所通信系统信息控制技术国家级重点实验室，浙江嘉兴 314001)

收稿日期:2011-12-16 修回日期:2012-02-09 出版日期:2013-02-15 发布日期:2013-02-13
作者简介:赵知劲(1959－)，女，教授、博士、博士生导师，主研方向：认知无线电，通信信号处理；赖海超，硕士研究生；尚俊娜，副教授、博士

Resource Allocation Algorithm for Cognitive Radio Based on QoS Requirements

ZHAO Zhi-jin ^1,2, LAI Hai-chao ¹, SHANG Jun-na^1,2

(1. School of Telecommunication Engineering, Hangzhou Dianzi University, Hangzhou 310018, China; 2. State Key Lab of Information Control Technology in Communication System, The 36th Research Institute of China Electronics Technology Group Corporation, Jiaxing 314001, China)

Received:2011-12-16 Revised:2012-02-09 Online:2013-02-15 Published:2013-02-13

摘要/Abstract

摘要： 在误比特率、总发射功率以及主用户可容忍干扰门限的约束下，提出一种基于正交频分复用的认知无线电系统多目标优化贪婪分配算法。以最小化发射功率、最小化跨频干扰及满足次用户QoS需求为优化目标，线性组合这3个目标函数，把多目标优化问题转化为单目标优化问题，采用贪婪算法实现多目标优化。仿真结果表明，该算法的系统总容量趋近于最优，在降低对主用户跨频干扰的同时，能够有效地满足次用户的QoS需求。

关键词: 资源分配, 贪婪算法, QoS需求, 认知无线电, 正交频分复用, 多目标优化

Abstract: Dynamic spectrum allocation is a key technology of the Cognitive Radio(CR). Subject to bit error rates, total transmit powers and interference thresholds that primary users can tolerate, a greedy allocation algorithm for multi-objective optimization of Orthogonal Frequency Division Multiplexing(OFDM)-based CR systems is proposed in this paper. The proposed algorithm minimizes the transmit power and the mutual interference, and meets the Quality of Service(QoS) requirements of Secondary User(SU). The multi-objective optimization problem is converted to a single-objective one through linearly combining the three objective functions, and the greedy algorithm is used to solve the optimization problem. Simulation results show that the total system capacity of the proposed algorithm is close to its maximum, and the mutual interference is reduced as well as the QoS requirements of SU are effectively met.

Key words: resource allocation, greedy algorithm, Quality of Service(QoS) requirement, Cognitive Radio(CR), Orthogonal Frequency Division Multiplexing(OFDM), multi-objective optimization

中图分类号:

TN919.2

赵知劲, 赖海超, 尚俊娜. 基于QoS需求的认知无线电资源分配算法[J]. 计算机工程, 2013, 39(2): 85-89.

DIAO Zhi-Jin, LAI Hai-Chao, CHANG Dun-Na. Resource Allocation Algorithm for Cognitive Radio Based on QoS Requirements[J]. Computer Engineering, 2013, 39(2): 85-89.

参考文献

[1] Federal Communications Commission. Spectrum Policy Task Force Report[EB/OL]. (2002-11-02). http://hraunfoss. fcc.gov/edocs_public/attachmatch/DOC-228542A1.pdf.
[2] Mitola J, Maguire G Q. Cognitive Radios: Making Soft- ware Radios More Personal[J]. IEEE Personal Communi- cations, 1999, 6(4): 13-18.
[3] Weiss T, Hillenbrand J, Krohn A, et al. Mutual Interference in OFDM-based Spectrum Pooling Systems[C]//Proc. of Vehicular Technology Conference. Milan, Italy: [s. n.], 2004: 1873-1877.
[4] Weiss T, Jondral F. Spectrum Pooling: An Innovative Strategy for the Enhancement of Spectrum Efficiency[J]. IEEE Communications Magazine, 2004, 42(3): 8-14.
[5] Chen C H, Wang C L, Chen C T. A Resource Allocation Scheme for Cooperative Multiuser OFDM-based Cognitive Radio Systems[J]. IEEE Transactions on Communications, 2011, 59(11): 1-12.
[6] Wu Jian, Yang Longxiang, Liu Xu. Subcarrier and Power Allocation in OFDM Based Cognitive Radio Systems[C]//Proc. of International Conference on Intelligent Computation Technology and Automation. Shenzhen, China: [s. n.], 2011: 728-731.
[7] Bansal G, Hossain M J, Bhargava V K. Optimal and Suboptimal Power Allocation Schemes for OFDM-based Cognitive Radio Systems[J]. IEEE Transactions on Wireless Communications, 2008, 7(11): 4710-4718.
[8] Hughes-Hartogs D. Ensemble Modem Structure for Imper- fect Transmission Media: USA, 4731816[P]. 1988-05-15.
[9] Sun Dawei, Zheng Baoyu. A Novel Multi-user Low Complexity Bit Allocation Algorithm in Cognitive OFDM Networks Based on AM-GM Inequality[C]//Proc. of the 3rd International Conference on Wireless, Mobile and Multimedia Networks. Beijing, China: [s. n.], 2010: 217-220.
[10] Zhang Jian, Zhu Qi. A Novel Adaptive Resource Allocation Algorithm for Multiuser OFDM-based Cognitive Radio Systems[C]//Proc. of International Conference on Network Computing and Information Security. Guilin, China: [s. n.], 2011: 442-445.

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基于QoS需求的认知无线电资源分配算法

Resource Allocation Algorithm for Cognitive Radio Based on QoS Requirements

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