In this work, a cognitive relay network (CRN) with interference constraint from the primary user (PU) with a mobile end user is studied. The proposed system model employs a half-duplex transmission between a single PU and a single secondary user (SU). In addition, an amplify and forward (AF) relaying technique is employed between the SU source and SU destination. In this context, the mobile end user (SU destination) is assumed to move at high vehicular speeds, whereas other nodes (SU Source, SU relays and PU) are assumed to be stationary. The proposed scheme dynamically determines the best relay for transmission based on the highest signal-to-noise (SNR) ratio by deploying selection combiner at the SU destination, thereby achieving diversity. All channels connected with the stationary nodes are modelled using Rayleigh distribution, whereas all other links connected with the mobile end user are modelled using Nakagami-m fading distribution ($m<1$). The outage probabilities (OPs) are obtained considering several scenarios and Monte Carlo simulation is used to verify the numerical results. The obtained results show that a variety of factors, including the number of SU relays, the severity of the fading channels, the position of the PU, the fading model, and the mobile end user speed, might influence the CRN’s performance.

In this paper, a dual-hop underlay cognitive relay network (CRN) with a best-relay selection (BRS) scheme under spectrum-sharing constraints from the primary user (PU) is investigated. The system model in this work consists of one PU, one secondary user (SU) and a few SU relays. Both users exchange the information using a half-duplex mode through amplify-and-forward (AF) SU relays. Moreover, all channels are modelled using the Nakagami-m fading model. In this work, the outage probabilities (OPs) are derived for the proposed system model under several scenarios to investigate the network performance under interference power constraint $I_p$ at the PU receiver. In addition, the impacts of the number of relays and the channel fading severity parameters are investigated as well. Furthermore, the system performance is investigated for several PU locations. The various numerical results are verified using a Monte Carlo simulation. Overall, the obtained results show that several factors such as the number of relays, channel fading severity parameters and PU location have a major impact on the outage performance of the SU. The simulation and analytical results are perfectly matched, confirming the accuracy of the analytical derivations.

Long Term Evolution-Licensed Assisted Access (LTE-LAA) has been pointed out as a key solution to cope with the increasing amounts of data traffic and the scarcity of the licensed spectrum. The 3rd Generation Partnership Project (3GPP) has standardised LAA to operate over the 5 GHz unlicensed spectrum which is mainly occupied by Wi-Fi. It is a challenging problem to ensure a fair coexistence between these technologies. Several studies have been proposed in the literature to allow a fair LAA/Wi-Fi coexistence. In this work, various methods are proposed to adapt/select the waiting times for LAA based on the activity statistics of the existing Wi-Fi network. The main novelty is that the knowledge of the existing Wi-Fi activities is exploited to tune the boundaries of the Contention Window (CW) for LAA and to select fixed waiting times for LAA. Moreover, a dynamic method is proposed to adapt the Transmission Opportunity (TxOP) times for LAA based on the Hybrid Automatic Repeat Request (HARQ) feedbacks. The methods are evaluated using ns-3 network simulator based on the 3GPP fairness definition. We show that selecting fixed waiting times for LAA based on the existing Wi-Fi activities is more friendly to the existing Wi-Fi and provides better total aggregated throughputs for both coexisting networks compared to the 3GPP Category 4 Listen Before Talk (Cat 4 LBT) algorithm. Moreover, the proposed dynamic TxOP method is more friendly to the existing Wi-Fi and provides better total aggregated throughputs compared to the fixed TxOP period approach of the 3GPP Cat 4 LBT scheme.

Ultra-Reliable and Low-Latency Communication (URLLC) is considered one of the key use cases in the current 5G and future 6G mobile communication networks. In this work, a hybrid transmission scheme is proposed to improve reliability in Terahertz (THz) bands employing adaptive diversity combining at the destination. The proposed scheme combines two links, the first link is a THz link (offering higher capacity but less reliable connectivity) as the main link, and the second link is a millimetre wave (mmWave) link (offering lower capacity but more reliable connectivity) as the backup link. The proposed scheme utilises both links dynamically exploiting the benefits of transmitting over both frequency bands by changing between the main link only and joint main/backup links based on the instantaneous quality of the channel for the main link. The received signals are combined at the destination using Selection Combining (SC) and Maximal Ratio Combining (MRC). The performance of the proposed scheme is evaluated analytically considering the Fluctuating Two-Ray (FTR) and $\alpha -\mu $ models for the mmWave and THz links, respectively. The obtained results show that the proposed hybrid transmission scheme achieves the same reliability provided by the continuous dual-link transmission scheme, where both links (THz and mmWave links) are used continuously for transmission, thus making the proposed scheme an appropriate solution to provide URLLC applications in a resource-efficient manner.

This study addresses the challenge of fair spectrum sharing in unlicensed bands for Licensed Assisted Access (LAA) and Wi-Fi coexistence. Existing methods, particularly the 3GPP Category 4 Listen Before Talk (Cat 4 LBT) algorithm, fail to fully meet the fairness criteria due to limitations in dynamic Contention Window (CW) adjustments. To improve spectrum efficiency, we propose an Enhanced Fixed Waiting Time (Enhanced FWT) approach, which leverages a theoretical model of Wi-Fi ON periods to determine fixed waiting times for LAA networks. By employing the β distribution to represent Wi-Fi activity more accurately, this model avoids the need for dynamic CW adjustments. Simulation results demonstrate that Enhanced FWT method significantly enhances throughput compared to both the Cat 4 LBT and traditional empirical FWT methods, especially in dense network conditions. This approach, compliant with 3GPP fairness standards, shows promise for robust spectrum sharing, promoting fair LAA/Wi-Fi coexistence in unlicensed bands.

The performance analysis of digital communication systems over fading channels focuses on the derivation of analytical results for relevant performance metrics but usually pays little attention to the computational complexity of the obtained analytical results. Many analytical results in the existing literature require long computation times that usually exceed the limits of what is practically feasible or reasonable. In this context, this work addresses this issue by looking at fading models from a computational efficiency point of view. By considering the fluctuating two-ray model as a particular case study, this work explores several strategies to obtain computationally efficient versions of the model and proposes a framework to evaluate the computational cost of fading models. The obtained results show a reduction of the required computation time by several orders of magnitude and a high accuracy of the proposed framework in predicting the actual computational costs of fading models.