Aug 2026· Bulletin of Electrical Engineering and Informatics· 0 citations· 37 references
TL;DR
This paper enhances the proposed system cell-edge user performance and derives analytical frameworks for outage probability, throughput, and ergodic capacity of PR, SR, respectively and determines the optimal power allocation scheme to enhance the performance of PR/SR signals.
Abstract
With the increasing demand for efficient wireless communication services, researchers are actively seeking innovative solutions to optimize spectrum utilization. Two promising technologies, cognitive radio and non-orthogonal multiple access (CR-NOMA), have emerged as key enablers for next-generation wireless communication. By harnessing the available radio frequency spectrum, devices can cooperatively connect and communicate more efficiently, while also gathering energy to support green communication.
This study investigates the uplink simultaneous wireless power and information transfer (SWIPT) using a CR-NOMA system over Rayleigh fading channel, focusing on energy harvesting at the secondary transmitter (ST) as a cooperation node. Here, primary/secondary receivers (PR/SR) communicate with the ST, during first phase, which then utilizes the harvested power to transmit the primary data to the primary transmitter. This paper enhances the proposed system cell-edge user performance and derives analytical frameworks for outage probability, throughput, and ergodic capacity of PR, SR, respectively. Additionally, our results determine the optimal power allocation scheme to enhance the performance of PR/SR signals.
In this paper, the joint radio resource management issues in a cognitive radio network driven by radio frequency energy harvesting (CRN- RF-EH) functionalities are investigated. For the CRN-RF-EH, the cognitive radio (CR) node first harvests its required energy directly from the transmitter of spectrum licensed user for its data communication and consequently transmits its data on the licensed frequency of the legacy user using the underlay accessing technique. Thus, RF-EH is an exciting innovation for energizing low-powered next- generation wireless networks (NGWNs). Consequently, due to CRN-RFEH’d low power limitations, the resource allocation for CRN-RF-EH has to be optimized considering the trade-off among spectral efficiency, energy efficiency, and RF energy supply. Equal allocation of transmission time and/or transmission power may not be efficient for CRN-RF-EH with limited transmission time and power resources. A joint optimal time and power allocation (OTPA) strategy for CRN-RF-EH is proposed to maximise the total spectral efficiency of the CRN- RF-EH. The coupled variables in the formulated joint resource allocation problems create a non-convex optimization problem formulation. For analytical tractability, the non-convex optimization formulation is initially converted to its equivalent standard convex optimization formulation using proper variables and next, it is then solved using the convex optimization technique. The CONOPT solver, a powerful optimization-solving tool for solving convex optimization problems, is utilized to resolve the equivalent standard convex optimization problem formulation. When compared with the baseline biased random time optimum power allocation (BRTOPA) scheme, numerical simulation results show that the OTPA strategy dramatically improves the total spectral efficiency performance. In a severe radio propagation environment with a path loss exponent (PLE) equal to 3.5 such as in urban areas and less severe radio propagation environment with a path loss exponent (PLE) equal to 2.0, such as in rural areas, the OTPA outperformed the BROTPA with a mean performance improvement of approximately 23. 96% and 42.94% , respectively.
E. Obayiuwana, O. Ipinnimo, P. Ayodele et al.· Nigerian Journal of Technolo...· 1 citation
Simulation results demonstrate that the APS NOMA scheme outperforms both the FPS NOMA and Orthogonal Multiple Access schemes, reducing OP significantly across a range of SNRs, making it highly effective for reliable and energy-efficient communication in future wireless networks.
S. Ajibowu, O. Adeleke, M. Asafa et al.· Nigerian Journal of Technolo...· 0 citations
A more superior hybrid M/T-NOMA cognitive communication scheme is proposed, in which the system will adaptively select the one with higher system throughput between M-NOMA and T-NOMA as the final transmission scheme.
Yafang Zhang, Ye Tian, Haixia Li et al.· Scientific Reports· 0 citations
This paper studies a cooperative wireless system in which a single-antenna base station (BS) communicates with a destination user (U) via a half-duplex energy-harvesting amplify-and-forward relay, while the direct BS–U link is unavailable. The destination (U) is equipped with a fluid antenna system (FAS) comprising multiple closely spaced receive ports, enabling spatial reconfigurability through instantaneous port selection. A power-splitting architecture is adopted at the relay to support simultaneous energy harvesting and information forwarding. All wireless links are modeled as flat Rayleigh fading, and the spatial correlation among the FAS ports is explicitly incorporated. To analytically characterize the impact of correlated port selection, a Gaussian copula framework is employed to model the joint distribution of the FAS-channel power gains. Exact integral expressions for the cumulative distribution function of the end-to-end signal-to-noise ratio are derived, from which the outage probability is obtained. For the special case of uncorrelated FAS ports, closed-form expressions are further developed using order statistics and special functions. In addition, asymptotic analysis is carried out to provide further insight into system performance in the high-signal-to-noise-ratio region. Numerical and Monte Carlo simulation results validate the analytical derivations and demonstrate that FAS-based receiver selection yields significant gains in outage performance, even in the presence of strong spatial correlation and energy-harvesting constraints.
The review finds that Massive MIMO improves spectrum efficiency, system capacity, and link reliability through large antenna arrays, beamforming, and spatial multiplexing, while NOMA increases access density and edge-user fairness through power-domain multiplexing and successive interference cancellation.
Yijiao Liu· Applied and Computational En...· 0 citations
In this paper, we investigate the downlink performance of multi-cell RSMA-enabled ISAC networks in which base stations (BSs), communication users, and sensing targets are spatially distributed according to independent Poisson point processes (PPPs). Each BS simultaneously serves multiple users using RSMA while exploiting the common stream as a dual-functional communication and sensing waveform. The users are equipped with FAS that selects the best antenna port to maximize the received signal quality. Closed-form analytical expressions are derived for the ergodic sum-rates by combining stochastic geometry, order statistics, and Laplace-transform-based interference analysis. Furthermore, a tractable approximation for the average radar SINR is developed by characterizing the statistical properties of the common precoder. Leveraging the derived analytical expressions, a low-complexity analytical resource allocation framework is proposed to jointly optimize the RSMA power allocation, the communication-sensing beam tradeoff, and the number of scheduled users while sat- isfying the sensing quality-of-service constraint. Compared with conventional iterative optimization approaches, the proposed analytical design significantly reduces computational complexity while achieving nearly identical communication performance. Simulation results verify the accuracy of the developed analytical expressions and demonstrate substantial improvements in both RSMA sum-rate and sensing performance over conventional transmission schemes.
Abdelhamid Salem, Hana Shamata, Salma M. Elkawafi et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
