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Published on: February 6, 2014
Joint Quality-Reliability Analysis of IRS-Assisted Communications in Presence of Inverse Power Lomax Fading Channel
Aleksey S Gvozdarev1, Roman Yu Manakhov1
1Department of Intelligent Radiophysical Information Systems (IRIS), P.G. Demidov Yaroslavl State University, Yaroslavl 150003, Russia.
Abstract:
In this work, we study the joint performance of the quality and reliability in terms of quality-reliability (JQR) performance of an intelligent reflecting surface (IRS)-assisted wireless communication system under severe multipath fading and shadowing. The wireless channel model is given by the Inverse Power Lomax (IPL) fading model, representing a heavy-tailed fading channel, which can describe the hyper-Rayleigh fading and is verified using two different experimentally obtained measurement scenarios, namely, the LTE-case for high-frequency, long-range cellular communications and the device-to-device (D2D) case for lower-frequency short-range communications. For the considered channel model and communication scheme, analytical expressions for the outage probability (a metric related to the reliability) and the average bit error rate for both coherent and non-coherent modulation schemes (metrics associated with the quality of the communication system) are provided. By combining the aforementioned expressions, a unified JQR curve, together with its asymptotic forms in the high signal-to-noise ratio regime and asymptotically large number of IRS elements, is derived. It is proved analytically that the use of IRS with infinite elements can remove fading, while for a finite number of IRS elements, a closed-form signal-to-noise ratio (SNR) penalty factor is presented. The numerical analysis demonstrates that coherent modulations outperform non-coherent ones, higher-order quadrature amplitude modulation (QAM) systems are highly sensitive to the multipath fading, and the LTE-case exhibits better performance compared to the D2D-case for equal settings. Moreover, the joint quality-reliability approach highlights the existence of regions where quality is more preferable than reliability, allowing the allocation of resources based on these regions. All expressions have been verified using Monte Carlo simulations with excellent agreement.
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