Joint Sensing Times Detection Thresholds and Users Association Optimization in Multi-Channel Multi-Antenna Cognitive Radio Networks

Publish Year: 1402
نوع سند: مقاله ژورنالی
زبان: English
View: 71

This Paper With 16 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

JR_IJE-36-9_015

تاریخ نمایه سازی: 13 مرداد 1402

Abstract:

Energy consumption and throughput optimization in cognitive radio networks (CRNs) are two critical issues that have attracted more attention in recent years. In this paper, we consider maximization of the energy efficiency and improvement of the throughput as optimization metrics for jointly optimizing sensing times and energy detection thresholds in each sub-channel and selecting the spectrum sensing (SS) and data transmitting multi-antenna secondary users (SUs) in multi-channel multi-antenna CRN under constraints on the probabilities of false alarm and detection. The considered problem is solved based on the convex optimization method and the algorithm having less computational complexity compared to baseline approaches is proposed to achieve the optimal parameters and goals of the problem. The performance of the proposed scheme is evaluated by simulations and compared with the other methods. The results indicate that the proposed approach can achieve less energy consumption while the minimum required throughput is guaranteed.

Authors

M. Sadeghian Kerdabadi

Department of Mechanic Engineering, Malek-e ashtar, University of Technology, Isfahan, Iran

R. Ghazizadeh

Department of Electrical and Computer Engineering, University of Birjand, Birjand, Iran

H. Farrokhi

Department of Electrical and Computer Engineering, University of Birjand, Birjand, Iran

M. Najimi

Faculty of Electrical, University of Science and Technology of Mazandaran (USTM), Behshahr, Mazandaran, Iran

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :