计算机科学 ›› 2017, Vol. 44 ›› Issue (5): 48-52.doi: 10.11896/j.issn.1002-137X.2017.05.009

• 网络与通信 • 上一篇    下一篇

一种基于OFDM认知无线电网络的次优动态资源分配算法

韩杰,宋晓勤,董莉,金慧   

  1. 南京航空航天大学电子信息工程学院 南京211106,南京航空航天大学电子信息工程学院 南京211106,南京航空航天大学电子信息工程学院 南京211106,南京航空航天大学电子信息工程学院 南京211106
  • 出版日期:2018-11-13 发布日期:2018-11-13
  • 基金资助:
    本文受国家自然科学基金(61301103)资助

Suboptimal Dynamic Resource Allocation Algorithm in OFDM Based Cognitive Radio Network

HAN Jie, SONG Xiao-qin, DONG Li and JIN hui   

  • Online:2018-11-13 Published:2018-11-13

摘要: 研究了采用正交频分复用的认知无线电网络中的多用户资源分配问题,包括子载波分配和功率分配。在认知无线电系统中,除了考虑主用户与次用户之间的相互干扰,还要求将主用户对次用户的干扰控制在预设门限之下,因此,系统模型更为复杂。整数约束条件,使得寻求最优解的算法复杂度高,无法用于对实时性要求高的系统。因此,提出了一种寻求次优解的分步式资源分配算法,以降低算法的复杂度。首先采用一种综合考虑了功率限制和对主用户的干扰限制的新型子载波分配方案,然后提出改进的线性注水算法进行功率分配。仿真结果表明,相比于最优分配算法,所提出的算法可以在获得较好的系统容量的同时,有效地降低系统的复杂度,适用于对实时性要求高的系统。

关键词: 认知无线电网络,正交频分复用,资源分配,线性注水算法

Abstract: This paper investigated the multi-user resource allocation in OFDM-based cognitive radio(CR-OFDM) including subcarrier allocation and power allocation.In CR system,not only the interference between primary uers(PUs) and second users(SUs) is considered,but also the interference caused by SUs need to be controlled under the threshold.Thus the system model is more complicated.Because of the integer constraints,the complexity of the algorithm which can obtain optimal solution is too high to suit for real-time systems.Therefore,this paper proposed a distributed algorithm to obtain the suboptimal solution with low complexity.First,a subcarrier allocation algorithm considering power constraint and interference constraint was proposed and then a modified linear water-filling algorithm was put forward to allocate power.Simulation results show that the proposed algorithm can obtain the satisfactory system capacity and reduce the complexity in comparison with the optimal Lagrange dual method,which is more suitable for real-time systems.

Key words: Cognitive radio network,OFDM,Resource allocation,Linear water-filling algorithm

[1] HAYKIN S.Cognitive radio:brain-empowered wireless communications[J].IEEE J.Sel.Areas Commun,2005,3(2):201-220.
[2] WEISS T,JONDRAL F K.Spectrum pooling:an innovative stra-tegy for the enhancement of spectrum efficiency[J].IEEE Commun.Mag,2004,3(3):S8-S14.
[3] WEISS T,HILLENBRAND J,KROHN A,et al.Mutual interference in OFDM-based spectrum pooling systems[J].Proc.IEEE Vehicular Technol.Conf.(VTC’04 Spring),2004,4(4):1873-1877.
[4] WANG S,HUANG F,et al.Fast power allocation algorithm for cognitive radio networks[J].IEEE Communications Letters,2011,15(8):845-847.
[5] BANSAL G,HOSSAIN M,BHARGAVA V.Optimal and suboptimal power allocation schemes for OFDM-based cognitive radio systems[J].IEEE Transactions on Wireless Communications,2008,7(11):4710-4718.
[6] TANG L,WANG H,CHEN Q,et al.Subcarrier and power allocation for OFDM-based cognitive radio networks[C]∥ IEEE International Conference on Communication and Technology and Applications.IEEE,2009:457-461.
[7] XU L,LV T M,LI Q M,et al.Proportional Fair Resource Allocation Based on Chance-Constrained Programming for Cognitive OFDM Network[J].Wireless Personal Communications,2014,9(2):1591-1607.
[8] ZHANG D M,XU Y Y,CAI Y M.Linear water filling power allocation algorithm in OFDMA system[J].Journal of Electro-nics & Information Technology,2007,9(6):1286-1289.(in Chinese) 张冬梅,徐友云,蔡跃明.OFDMA系统中线性注水功率分配算法[J].电子与信息学报,2007,29(16):1286-1289.
[9] WU J,YANG L X,LIU X.Subcarrier and Power allocation in OFDM Based Cognitive Radio Systems[C]∥International Conference on Intelligent Computation Technology & Automation.2011:728-731.
[10] YAN S C,REN P Y,LV F S.Power allocation algorithms forOFDM-based cognitive radio system[C]∥Proc.WiCOM 2010.2010:1-4.
[11] ZHAO Q,SADLER B M.A Survey of Dynamic Spectrum Access[J].IEEE Signal Processing Magazine,2007,24(3):79-89.
[12] ALMALFOUH S M,STUBER G L.Interference-aware radioresource allocation in OFDMA-based cognitive radio networks[J].IEEE Trans.Veh.Technol.,2011,0(4):1699-1713.
[13] LI W,ZHANG Y,SO A,et al.Slow adaptive OFDMA systems through chance constrained programming[J].IEEE Trans.Signal Process.,2010,8(7):3858-3869.
[14] DANIELS R.Approximation methods for electronic filter design[M].New York:McGraw-Hill,1974.
[15] GOLDSMITH A,CHUA S.Variable-rate variable-power MQAMfor fading channels[J].IEEE Transactions on Communications,1997,5(10):1218-1230.
[16] BANSAL G,Hossain M J,BHARGAVA V K.Adaptive Power Loading for OFDM-Based Cognitive Radio Systems with Statistical Interference Constraint[J].IEEE Transactions on Wireless Communications,2011,0(9):2786-2791.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!