Title: Self-diagnosis of cognitive relay on the joint impact of hardware impairment and channel estimation error

Authors: Vijayakumar Ponnusamy; S. Malarvizhi

Addresses: ECE Department, SRM University, Kattankulathur, Chennai, Tamil Nadu, India ' ECE Department, SRM University, Kattankulathur, Chennai, Tamil Nadu, India

Abstract: Self-diagnosis and repair are the essential requirements of cognitive radio for the next generation of wireless communication. This work presents the self-diagnosis of the joint impact of the hardware impairment and channel estimation error on the cognitive relay system and derives the closed form solution for the outage probability in the presence of hardware impairment and channel estimation error. The presence of hardware impairment in the transceiver of the cognitive relay will degrade the performance which results in the system outage. The impact of the impairment in channel estimation on least square (LS) channel estimation algorithm and minimum mean square error (MMSE) algorithm is analysed. Simulated results show that the presence of hardware impairment increases channel estimation error and makes the system almost 40% outage even for the SNR of 40 dB. After self-diagnosis, a correction factor is given as a repair component which is used to mitigate the impact of impairment in channel estimation process.

Keywords: cognitive relay; channel estimation error; hardware impairment; outage probability; self-diagnosis and repair; cognitive radio; overlay relay; least square channel estimation; MMSE algorithm; decode and forward; signal to interference noise ratio; SINR.

DOI: 10.1504/IJSCC.2017.087155

International Journal of Systems, Control and Communications, 2017 Vol.8 No.4, pp.335 - 347

Received: 08 Jun 2016
Accepted: 29 Mar 2017
Published online: 06 Oct 2017 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article