Performance Evaluation of Cognitive Cooperative Radio Network under Joint Constraints
Pham Huu Tung1, Quach Xuan Truong2, Vu Le Quynh Giang3

1Pham Huu Tung, M.SC. Department of Information Technology, NUCE, Giai Phong Road, Ha Noi Vietnam.
2Quach Xuan Truong, M.SC. Department of Information Technology, ICTU, Thai Nguyen University, Quyet Thang Precinct, Thai Nguyen Vietnam.
3Vu Le Quynh Giang, M.SC. Department of Information Technology, NIEM, Phan Dinh Giot, Thanh Xuan, Ha Noi Vietnam.
Manuscript received on 17 August 2015 | Revised Manuscript received on 25 August 2015 | Manuscript Published on 30 August 2015 | PP: 6-9 | Volume-5 Issue-3, August 2015 | Retrieval Number: C2163085315/15©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this paper, we investigate outage performance of a cognitive cooperative underlay network in which secondary transmitter (SU-Tx) sends signals to the secondary receiver (SU-Rx) through the help of a single relay (SR). Here, we assume that the relay is equipped with multiple antennas and operates in the decode-and-forward mode. Furthermore, the relay uses the selection combining (SC)/transmit antenna selection (TAS) technique to process the signal. Given this setting, an adaptive transmit power allocation policy for the SU-Tx and SR are derived. Accordingly, simulations for the outage probability of the considered system is executed. Our numerical results will show the impact of different channel mean power gains between primary user and secondary user on the outage performance. Also, the impact of massive antennas at the SR on the performance of the considered system model is addressed.
Keywords: Cognitive Cooperative Radio Networks, Outage Constraint, Peak Transmit Power, Device-to-Device Communication.

Scope of the Article: Cognitive Radio Networks