Secure Collaborative Spectrum Sensing for Distributed Cognitive Radio Networks

  • سال انتشار: 1394
  • محل انتشار: مجله مهندسی برق مجلسی، دوره: 9، شماره: 2
  • کد COI اختصاصی: JR_MJEE-9-2_007
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 77
دانلود فایل این مقاله

نویسندگان

Abbas Ali Sharifi

Department of Electrical Engineering, Bonab Branch, Islamic Azad University, Bonab, Iran

Mir Javad Musevi Niya

Faculty of Electrical and computer Engineering, University of Tabriz Tabriz, Iran

Hamed Alizadeh Ghazijahani

Faculty of Electrical and computer Engineering, University of Tabriz Tabriz, Iran

چکیده

Spectrum sensing is a key function of Cognitive Radio (CR) networks. An accurate spectrum sensing scheme can improve spectrum utilization. But, in practice, detection performance is often degraded with multipath fading, shadowing and receiver uncertainty issues. To overcome the impact of these issues, Collaborative Spectrum Sensing (CSS) has been shown to be an effective approach to improve the detection performance by exploiting diversity. The reliability of CSS can be severely degraded by Spectrum Sensing Data Falsification (SSDF) attacks. Protecting the CR networks against SSDF attacks, Weighted Sequential Probability Ratio Test (WSPRT) has been proposed. Compared with conventional SPRT, the WSPRT improves correct sensing probability at the cost of increasing sampling overhead. In the present study, weighted majority rule is introduced and combined with the WSPRT to improve trustworthiness of collaborative spectrum sensing in the presence of SSDF attackers. Furthermore, to avoid increasing the sampling overhead, Roulette Wheel Selection (RWS) algorithm is used to collaborative node selection. The proposed method is called Developed WSPRT (DWSPRT). Simulation results show that the DWSPRT is an effective data fusion approach against SSDF attacks, especially for CR networks located in hostile environments.

کلیدواژه ها

Cognitive radio, Bonab Branch, en, Collaborative Spectrum Sensing, Islamic Azad University, SSDF Attack, Bonab, Data Fusion, Iran

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.