# Best Relay Selection Strategy in Cooperative Spectrum Sharing Framework with Mobile-Based End User
The performance of a full duplex (FD) bidirectional machine type communication (MTC) system was studied in [54], considering a passive intelligent reflecting surface (IRS) to achieve a reliable communication. Tight-form expressions of OP and BER were derived and verified using Monte Carlo simulations for the considered system model with a continuous phase shifter. Moreover, non-ideal cases of the discrete phase shifter at IRS were investigated in the perspectives of OP and BER. The obtained results showed a noticed improvement in the outage performance for the considered system by using FD mode compared to half duplex (HD) mode. In addition, locating the IRS near the source can improve the performance instead of locating it between the two nodes of the bidirectional FD-MTC system. On the other hand, the authors in [55] investigated the same system model using AF relays. In this work, there was no direct link between the source and destination. On the other hand, an enhanced CRN model with a direct link between the source and destination was considered in [56]. Specifically, a SC scheme was deployed at the destination to select the best path for communication. For both scenarios, the OPs were derived and the obtained results demonstrated that using SC scheme achieved better performance compared to the conventional AF relaying transmission [57]. The BRS scheme was used to investigate the performance of a dual-hop CRN under power constraints from the PU in [58]. In this work, the OPs were obtained for several scenarios where all nodes were stationary and all links were modeled using Nakagami-\(m\) distribution. The obtainedresults showed that better performance can be achieved using a cooperative communication technique accompanied with the spectrum-sharing networks. To the best of the authors' knowledge, most of the previous works in the literature studied the performance of cognitive cooperative networks under a given fading model with stationary environments (i.e., stationary SU destination). On the other hand, with the heavy use of smart phones, tablets, and the other mobile devices, which exchange the data over geographical and time boundaries, it is necessary not only to study the performance of such networks under mixed fading models with mobile environments (i.e., mobile SU destination), but also to investigate the impact of several parameters, which are considered critical in the network design for any network provider, thereby being the key motivations of this work. In this context, the best relay selection strategy is exploited to improve the performance of cognitive relay networks with the mobile end user. This concept is considered a key approach to enhance the performance of mobile networks where cooperative communication and cognitive radio techniques are merged together achieving better performance and acting as a virtual MIMO system. Specifically, several relays are deployed between the SU source and SU destination and the most effective relay is selected for transmission based on the highest received SNR at the destination. Interestingly, combining spectrum sharing networks with a cooperative communication technique, using the best relay selection strategy for transmission with mobile-based end user under mixed fading channels, and studying the effect of various parameters on the CRN performance are the key novelties of this work. All links connected between the stationary nodes (i.e., SU source, SU relays, PU) are assumed to follow Rayleigh distribution, being considered an appropriate modelling for such channels [59]. On the other hand, all links connected to the mobile end user (i.e., SU destination) are assumed to follow Nakagami-\(m\) (\(m<1\)), being considered the most appropriate modelling for such channels where the fading becomes more severe due to the mobility of the end user [60]. The following list summarises the main contributions of this work. 1. The best relay selection strategy is exploited to enhance the performance of underlay cognitive relay networks deploying a mobile-based end user.