Identification of STBC-OFDM Signals by Second-Order Cyclostationarity Method

Document Type : Original Article

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Abstract

Signal identification’s intrinsic application is in the military field, where the detection, analysis and identification of unknown signals from potentially hostile communication sources is a vital task in signal interception, radio surveillance, interference identification and mitigation, and electronic warfare. So signal identification has continued to be a major part of intelligent radios employed in military wireless communications up to present. With the deployment of the MIMO, new and challenging signal identification problems have emerged, which did not exist for single antenna systems. An example of identifying these types of signals is identifying the space-time block (STBC) code in the MIMO-OFDM system. MIMO-OFDM systems have different types, three of which are identified in this paper. These three types of systems include SM-OFDM, AL-OFDM, STC3-OFDM. Previously, these three types of systems were identified by the second-order moment of the signal method. In this paper, this identification is performed by the second-order rotating stationarity of the signal. This method can perform better in lower SNRs. In addition, the proposed method provides good performance with low sensitivity to time offset and channel conditions.

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References

[1]     W. Su, J. Xu, and M. Zhou, “Real-time Modulation Classification Based on Maximum Likelihood,” IEEE Communications Letters, vol. 12, pp. 801– 803, Nov. 2008.##
[2]     W. Gardner and C. Spooner, “Signal Interception: Performance Advantages of Cyclic-Feature Detectors,” IEEE Transactions on Communications, vol. 40, pp. 149–159, Jan. 1992. ##
[3]     O. A. Dobre, A. Abdi, Y. Bar-Ness, and W. Su, “A Survey of Automatic Modulation Classification Techniques: Classical Approaches and New Developments,” IET Communications, vol. 1, pp. 137–156, Apr. 2007.## 
[4]     T. Ulversoy, “Software Defined Radio: Challenges and Opportunities,” IEEE Communications Surveys and Tutorials, vol. 12, pp. 531 – 550, Sep. 2010.## 
[5]     D. Cabric, “Addressing Feasibility of Cognitive Radios,” IEEE Signal Processing Magazine, vol. 25, pp. 85–93, Nov. 2008. ##
[6]     T. Yucek and H. Arslan, “A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications,” IEEE Communications Surveys and Tutorials, vol. 11, pp.       116–130, Mar. 2009.##
[7]     A. Ghosh, J. Zhang, J. Andrews, and R. Muhamed, “Fundamentals of LTE, ” Prentice Hall, 2010. ##
[8]     C. Eklund, R. B. Marks, K. Stanwood, and S. Wan, “IEEE standard 802.16: A technical overview of the wireless MAN air interface for broadband wireless access,” Wireless Personal Communications, vol. 40, pp. 98–107, June 2002.##  
[9]     J. Andrews, A. Ghosh, and R. Muhamed, “Fundamentals of WiMAX: Understanding Broadband Wireless Networking,” Prentice Hall, 2007.##
[10]  O. Torabian, K. Mohamedpour, A. Golestani, and H. Ahmadian Yazdi, “Blind Frequency Offset Estimation using Adaptive Algorithms in Non-Coherent OFDM Systems,” Journal of Electronical & Cyber Defence, vol. 3, no. 4, 2016. (In Persian) ##        
[11]  Y. A. Eldemerdash, O. A. Dobre, and M. Öner, “Signal identification for multiple-antenna wireless systems: Achievements and challenges,” IEEE Commun. Surveys Tut., vol. 18, no. 3, pp. 1524–1551, 2016.##
[12]  E. Karami and O. A. Dobre, “Identification of SM-OFDM and ALOFDM signals based on their second-order cyclostationarity,” IEEE Trans. Veh. Technol., vol. 64, pp. 942–953, Mar. 2015.##
[13]  M. Marey, O. A. Dobre, and R. Inkol, “Novel algorithm for stbc-ofdm identification in cognitive radios,” in Proc. IEEE ICC. IEEE, pp. 2770–2774, 2013.##
[14]  M. Marey, O. A. Dobre, and R. Inkol, “Blind STBC identification for multiple-antenna OFDM systems,” IEEE Trans. Commun., vol. 62, pp. 1554–1567, May 2014.##    
[15]  Y. A. Eldemerdash, O. A. Dobre, O. ÃIJreten, and T. Yensen, “A robust modulation classification method for psk signals using random graphs,” IEEE Transactions on Instrumentation and Measurement, pp. 1–4, 2018.##

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History

  • Receive Date: 18 February 2019
  • Revise Date: 07 May 2019
  • Accept Date: 02 July 2019
  • Publish Date: 20 February 2020

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