Review of Spectrum Sensing Techniques in Cognitive Radio Networks

被引:0
|
作者
Omer, Ala Eldin [1 ]
机构
[1] AUS, Dept Elect Engn, Sharjah, U Arab Emirates
关键词
Cognitive Radio; spectrum sensing; Matched filter; Cyclostationary; Periodogram; cross-correlation;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Most frequency spectrum bands are licensed to certain services to avoid the interference between various networks but measurements of spectrum occupancy show that only portions of the spectrum band are fully efficiently used. Cognitive Radio (CR) is a future radio technology that is aware of its environment, internal state and can change its operating behaviour (transmitter parameters) accordingly. Through this technology the unlicensed users can use the underutilized spectrum without any harmful interference to the licensed users. Its key domains are sensing, cognition and adaptation. The spectrum sensing problem is one of the most challenging issues in cognitive radio systems to detect the available frequency bands. In this paper we have implemented various transmitter detection techniques: Energy detection, Matched filter and Cyclostationary feature detection in MATLAB. Along with other techniques to enhance the detection performance of the conventional Energy detector. The Implementation is based on BPSK and QPSK modulation schemes under various SNR values for AWGN noisy channel with Rayleigh fading. The techniques are compared in term of sensing time, detection sensitivity and the ease of implementation.
引用
收藏
页码:439 / 446
页数:8
相关论文
共 50 条
  • [41] Spectrum Allocation Techniques for Cognitive Radio Networks
    Helmy, Maram
    Hassan, Mohamed S.
    Ismail, Mahmoud H.
    [J]. IEEE ACCESS, 2022, 10 : 28180 - 28193
  • [42] A Review Study on Different Narrowband Spectrum Sensing Techniques Classifications in Cognitive Radio
    Singhal, Cheena
    Kumar, Amit
    [J]. JOURNAL OF ACTIVE AND PASSIVE ELECTRONIC DEVICES, 2023, 17 (03): : 173 - 184
  • [43] Sub-Nyquist wideband spectrum sensing techniques for cognitive radio: A review and proposed techniques
    Aswathy, G. P.
    Gopakumar, K.
    [J]. AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 2019, 104 : 44 - 57
  • [44] Wavelet Based Spectrum Sensing Techniques in Cognitive Radio
    Rao, S. V. R. K.
    Singh, G.
    [J]. INTERNATIONAL CONFERENCE ON MODELLING OPTIMIZATION AND COMPUTING, 2012, 38 : 880 - 888
  • [45] Comparative analysis of cognitive radio techniques for sensing spectrum
    Deshmukh, M.N.
    Padaganur, S.K.
    [J]. 2021 2nd International Conference for Emerging Technology, INCET 2021, 2021,
  • [46] A Survey of Spectrum Sensing Techniques in Cognitive Radio Network
    Alom, Md. Zulfikar
    Godder, Tapan Kumar
    Morshed, Mohammad Nayeem
    [J]. 2015 INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL ENGINEERING (ICAEE), 2015, : 161 - 164
  • [47] Blind spectrum sensing techniques for cognitive radio system
    Lee, Jaekwon
    [J]. International Journal of Multimedia and Ubiquitous Engineering, 2008, 3 (02): : 117 - 128
  • [48] Spectrum Sensing in Cognitive Radio Enabled Vehicular Ad Hoc Networks A Review
    Abeywardana, Rajith C.
    Sowerby, Kevin W.
    Berber, Stevan M.
    [J]. 2014 7TH INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION FOR SUSTAINABILITY (ICIAFS), 2014,
  • [49] SPECTRUM SENSING IN COGNITIVE RADIO NETWORKS: UP-TO-DATE TECHNIQUES AND FUTURE CHALLENGES
    Hussain, Sattar
    Fernando, Xavier
    [J]. IEEE TIC-STH 09: 2009 IEEE TORONTO INTERNATIONAL CONFERENCE: SCIENCE AND TECHNOLOGY FOR HUMANITY, 2009, : 736 - 741
  • [50] Machine Learning Techniques with Probability Vector for Cooperative Spectrum Sensing in Cognitive Radio Networks
    Lu, Yingqi
    Zhu, Pai
    Wang, Donglin
    Fattouche, Michel
    [J]. 2016 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, 2016,