Computer Science ›› 2018, Vol. 45 ›› Issue (9): 129-134.doi: 10.11896/j.issn.1002-137X.2018.09.020

• Network & Communication • Previous Articles     Next Articles

HMM Cooperative Spectrum Prediction Algorithm Based on Density Clustering

WU Jian-wei, LI Yan-ling, ZHANG Hui, ZANG Han-lin   

  1. Department of Information and Communication Engineering,Rocket Engineering University,Xi’an 710025,China
  • Received:2017-07-25 Online:2018-09-20 Published:2018-10-10

Abstract: Aiming at the problems of long time delay and low prediction accuracy in traditional hidden Markov spectrum prediction,this paper proposed an HMM cooperative spectrum prediction algorithm based on density-based spatial clustering of applications with noise (DBSCAN).BSCAN algorithm is used to cluster the frequency domain channels with strong correlation and predict the channel state in units of clusters,and the prediction delay is reduced by reducing the number of predicted times.At the same time,the method of multiple sub-users cooperative prediction is used in the time domain,and the forecast uncertainty is reduced by fusing the initial prediction results of each subordinate user.Simulation results show thatthe proposed algorithm has shorter spectral delay and higher accuracy compared with the traditional HMM-based local spectrum prediction algorithm and HMM-based packet fusion prediction algorithm.

Key words: Channel correlation, Cooperative spectrum prediction, DBSCAN, Hidden Markov model, Time delay

CLC Number: 

  • P922
[1]LIU Y N,YANG J G,YANG H L,et al.Combined probabilistic channel prediction dynamic cognitive radio spectrum access based on Hidden Markov Model [J].Journal of Shanghai University(Natural Science Edition),2011,17(5):581-585.(in Chinese)
刘永年,杨建国,杨辉联,等.基于隐马尔可夫模型的联合概率信道预测动态认知无线电频谱接入[J].上海大学学报(自然科学版),2011,17(5):581-585.
[2]WANG D L,CAO P,HUANG G C,et al.Selection of shortwave cognitive frequency based on hidden Markov model [J].Journal of Computer Applications,2016,36(5):1179-1182.(in Chinese)
王董礼,曹鹏,黄国策,等.基于隐马尔可夫模型的短波认知频率选择方法[J].计算机应用,2016,36(5):1179-1182.
[3]ZHANG K,QI L N.An Adaptive Joint Spectral Prediction
Method Based on Hidden Markov Model [J].Journal of Nanjing University of Posts and Telecommunications(Natural Scien-ce),2015,35(1):79-83.(in Chinese)
张凯,齐丽娜.一种基于隐马尔可夫模型的自适应联合频谱预测方法[J].南京邮电大学学报(自然科学版),2015,35(1):79-83.
[4]LIN G,CHENG Y P,JIANG H,et al.Analysis of three-state
HMM performance in HF channel estimation [J].Communications Technology,2016,49(3):286-292.(in Chinese)
林刚,程云鹏,江汉,等.短波信道估计中的三状态HMM性能分析[J].通信技术,2016,49(3):286-292.
[5]XING X,JING T,CHENG W,et al.Cooperative Spectrum Prediction in Multi-PU Multi-SU Cognitive Radio Networks[J].Mobile Networks & Applications,2014,19(4):502-511.
[6]CHEN Z,QIU R C.Prediction of channel state for cognitive radio using higher-order hidden Markov model[C]∥Proceedings of the IEEE SoutheastCon 2010(SoutheastCon).IEEE,2010:276-282.
[7]MAN F W,SHI R,HE B B.Prediction of Radio Spectrum Occupancy Based on Association Rules Mining [J].Telecommunications Technology,2016,56(11):1183-1188.(in Chinese)
满方微,石荣,何彬彬.基于关联规则挖掘的无线电频谱占用预测[J].电讯技术,2016,56(11):1183-1188.
[8]JIA Y F,QIU L,WEI H H.Prediction of Spectrum Occupancy Based on k Nearest Neighbor Regression [J].Telecommunications Technology,2016,56(8):844-849.(in Chinese)
贾云峰,邱琳,魏鸿浩.基于k最近邻回归的频谱占用度预测[J].电讯技术,2016,56(8):844-849.
[9]ZHANG D Y,OUYANG J F,WU W L.Clustering Hidden
Markov Model for Multi-step Prediction of Time Series[J].Transactions of Chinese Electronics,2014,42(12):2359-2364.(in Chinese)
章登义,欧阳黜霏,吴文李.针对时间序列多步预测的聚类隐马尔科夫模型[J].电子学报,2014,42(12):2359-2364.
[10]SAAD A,STAEHLE B,KNORR R.Spectrum prediction using hidden Markov models for industrial cognitive radio[C]∥IEEE,International Conference on Wireless and Mobile Computing,Networking and Communications.IEEE,2016:1-7.
[11]HOU M S,XIE X Z.Prediction of Channel State Estimation and Capacity Estimation Based on Markov Chain[J].Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition),2009,21(6):710-716.(in Chinese)
后茂森,谢显中.基于马氏链的感知无线电信道状态预测及容量估计[J].重庆邮电大学学报(自然科学版),2009,21(6):710-716.
[12]GAO M F.Fast spectrum sensing algorithm and scheme based on prediction[D].Beijing:Beijing University of Posts and Telecommunications,2015.(in Chinese)
高明菲.基于预测的快速频谱感知算法与方案研究[D].北京:北京邮电大学,2015.
[13]CHEN B H.Research on Spectrum Prediction Algorithm in
Cognitive Radio Systems[D].Beijing:Beijing University of Posts and Telecommunications,2011.(in Chinese)
陈斌华.认知无线电系统中的频谱预测算法研究[D].北京:北京邮电大学,2011.
[14]WU J R,HU J M,QIN J X.Recognition Radio Spectrum Prediction Based on K-RBF Neural Network[J].Technology of Television,2014,38(5):105-108.(in Chinese)
吴建绒,胡津铭,秦继新.基于K-RBF神经网络的认知无线电频谱预测[J].电视技术,2014,38(5):105-108.
[15]ZHANG K,QI L N.Collaborative Spectrum Detection Based on Continuous Hidden Markov Model[J].Computer Technology & Development,2015,25(6):64-68.(in Chinese)
张凯,齐丽娜.基于连续隐马尔科夫模型的协作频谱检测[J].计算机技术与发展,2015,25(6):64-68.
[16]LING X,WU B,WEN H,et al.Adaptive Threshold Control for Energy Detection Based Spectrum Sensing in Cognitive Radios[J].IEEE Wireless Communications Letters,2012,1(5):448-451.
[17]DIGHAM F F,ALOUINI M S,SIMON M K.On the Energy
Detection of Unknown Signals Over Fading Channels[J].IEEE Transactions on Communications,2007,55(1):21-24.
[18]XING X S.Research on Spectrum Prediction in Cognitive Radio Network [D].Beijing:Beijing Jiao Tong University,2014.(in Chinese)
邢晓双.认知无线电网络中的频谱预测技术研究[D].北京:北京交通大学,2014.
[19]NI S,BAI X,WANG Z,et al.A new method of cognitive radio spectrum prediction research[C]∥International Congress on Image and Signal Processing,Biomedical Engineering and Informatics.IEEE,2017:982-986.
[1] XU Tian-hui, GUO Qiang, ZHANG Cai-ming. Time Series Data Anomaly Detection Based on Total Variation Ratio Separation Distance [J]. Computer Science, 2022, 49(9): 101-110.
[2] MA Li-wen, ZHOU Ying. BBR Unilateral Adaptation Algorithm for Improving Empty Window Phenomenon in STARTUP Phase [J]. Computer Science, 2022, 49(2): 321-328.
[3] ZHANG Ren-jie, CHEN Wei, HANG Meng-xin, WU Li-fa. Detection of Abnormal Flow of Imbalanced Samples Based on Variational Autoencoder [J]. Computer Science, 2021, 48(7): 62-69.
[4] LUO Jin-nan and ZHANG Ji-min. Rail Area Extraction Using Extended Haar-like Features and DBSCAN Clustering [J]. Computer Science, 2020, 47(6A): 153-156.
[5] MO Cai-wang, CHANG Kan, LI Heng-xin, LI Ming-hong, QIN Tuan-fa. Color Image Super-resolution Algorithm Based on Inter-channel Correlation and Nonlocal Self-similarity [J]. Computer Science, 2020, 47(6): 138-143.
[6] CHEN Qian, ZHOU Jie, SHAO Gen-fu. MIMO Channels with Arbitrary AoA Power Spectrum for Various Wireless Environments [J]. Computer Science, 2020, 47(6): 271-275.
[7] DENG Ding-sheng. Application of Improved DBSCAN Algorithm on Spark Platform [J]. Computer Science, 2020, 47(11A): 425-429.
[8] ZHANG Cheng-wei, LUO Feng-e, DAI Yi. Prediction Method of Flight Delay in Designated Flight Plan Based on Data Mining [J]. Computer Science, 2020, 47(11A): 464-470.
[9] ZHANG Jing, YANG Jian, SU Peng. Survey of Monosyllable Recognition in Speech Recognition [J]. Computer Science, 2020, 47(11A): 172-174.
[10] JIA Zhi-chun, LI Xiang, YU Zhan-lin, LU Yuan, XING Xing. QoS Satisfaction Prediction of Cloud Service Based on Second Order Hidden Markov Model [J]. Computer Science, 2019, 46(9): 321-324.
[11] ZHANG Jian-xin, LIU Hong, LI Yan. Efficient Grouping Method for Crowd Evacuation [J]. Computer Science, 2019, 46(6): 231-238.
[12] HU Ying-shuang, LU Yi-hong. Cell Clustering Algorithm Based on MapReduce and Strongly Connected Fusion [J]. Computer Science, 2019, 46(11A): 204-207.
[13] YUE Xin, DU Jun-wei, HU Qiang, WANG Yan-ping. Fault Tree Structure Matching Algorithm and Its Application [J]. Computer Science, 2018, 45(9): 202-206.
[14] WANG, Xin-ling FU, Ying HUANG Hua. Deblurring for Imaging through Simple LensCombining Adaptive Gradient Sparsity and Interchannel Correlation [J]. Computer Science, 2018, 45(8): 1-6.
[15] GONG Fa-ming,ZHU Peng-hai. Word Segmentation Based on Adaptive Hidden Markov Model in Oilfield [J]. Computer Science, 2018, 45(6A): 97-100.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!