Performance Optimization for Hybrid Two-Way Cognitive Cooperative Radio Networks With Imperfect Spectrum Sensing | Zendy

Thi My Chinh Chu | Zendy; Hans-Jurgen Zepernick | Zendy

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Performance Optimization for Hybrid Two-Way Cognitive Cooperative Radio Networks With Imperfect Spectrum Sensing

Author(s) -

Thi My Chinh Chu,

Hans-Jurgen Zepernick

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2879901

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In this paper, we consider a two-way cognitive cooperative radio network (TW-CCRN) with hybrid interweave-underlay spectrum access in the presence of imperfect spectrum sensing. Power allocation strategies are proposed that maximize the sum-rate and minimize the outage probability of the hybrid TW-CCRN. Specifically, based on the state of the primary network (PN), fading conditions, and system parameters, suitable power allocation strategies subject to the interference power constraint of the PN are derived for each transmission scenario of the hybrid TW-CCRN. Given the proposed power allocation strategies, we analyze the sum-rate and outage probability of the hybrid TW-CCRN over Rayleigh fading taking imperfect spectrum sensing into account. Numerical results are presented to illustrate the effect of the arrival rate, interference power threshold, transmit power of the PN, imperfect spectrum sensing, and maximum total transmit power on the sum-rate and outage probability of the hybrid TW-CCRN.

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