The incorporation of reconfigurable intelligent surfaces (RISs) and unmanned aerial vehicles (UAVs) presents considerable potential for improving the functionality of ground-based terrestrial Internet of Things (IoT) networks. This paper introduces a novel UAV deployment and aerial RIS partitioning mechanism for the uplink non-orthogonal multiple access (NOMA)-based IoT networks under practical hardware constraints. The low-cost hardware of IoT devices results in imperfect successive interference cancellation (SIC) and distortion noise due to transceiver hardware impairments (T-HIs). Specifically, we have optimized the aerial RIS partitioning and its deployment to maximize the minimum rate under the impact of imperfect SIC and T-HIs. The numerical results show that the proposed scheme outperforms the benchmark. Through extensive simulations, we prove that the proposed UAV-based aerial RIS-aided uplink NOMA network significantly enhances the max-min fair rate.

This work investigates simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) in multiple-access (MA) bidirectional network architecture. The proposed optimization framework incorporates two practical operational protocols of STAR-RIS to optimize the channel gains for users and obviate the necessity for uplink power control while adhering to specified quality of service (QoS) constraints. The proposed approach undergoes thorough evaluation under key optimization problems: QoS feasible region, and energy efficiency. The closed-form solutions are validated through simulations, showcasing the notable advantages that STAR-RIS can provide to the considered multiple-access networks. Simulation findings revealed that in the context of the proposed system model, the mode switching approach can attain a superior QoS threshold rate compared to the energy splitting mode. The proposed framework has demonstrated its ability to meet bidirectional communication needs with a high degree of accuracy and precision.

The temporal nature of data in Internet of Things (IoT) networks necessitates periodic updates of cached content at edge devices, while multicasting dynamic content can enhance network efficiency. This paper addresses the challenge of joint cache updating and multicast scheduling in a cache-enabled, queue-equipped small base station (SBS) with limited cache capacity, which accesses a macro base station (MBS) to download (update) uncached (cached) content and serves requests through multicasting. We formulate a two-stage optimization problem to minimize the average age of information (AAoI) per request, subject to constrained average queueing delay and access rate. The first stage employs the Lyapunov drift-plus-penalty method at the SBS to schedule multicasting and downloading (updating) uncached (cached) content. The second stage, implemented at the MBS, leverages deep reinforcement learning (DRL) to determine the content replacement policy. Simulation results show that the DRL-based cache replacement policy yields up to 50%, 59%, and 60% improvements in AAoI compared to the maximum age, least-recently-used, and least-frequently-used baseline policies, respectively.

In this work, we examine the potential of reconfigurable intelligent surfaces (RISs) to facilitate and enhance uplink (UL) transmissions in grant-free non-orthogonal multiple access (GF-NOMA) networks. The proposed RIS-assisted GF-NOMA approach employs virtual partitioning of RIS, with each partition tailored to optimize channel conditions for individual NOMA user equipment (UE). The resulting channel gain disparity bolsters the NOMA gain and obviates the necessity for UL power control of the grant-based NOMA schemes. Our approach is evaluated under three practical operational regimes: 1) quality-of-service (QoS) sufficient regime, 2) efficient RIS usage regime, and 3) max-min fair regime, all subject to UL-QoS constraints. We derive closed-form solutions to elucidate how optimal RIS partitioning can fulfill UL-QoS requirements across all three operational regimes. Comprehensive simulations are conducted to validate the precision of our analytical findings, demonstrating that the proposed approach substantially improves wireless communication system performance while mitigating signaling overhead and computational complexity.

Terahertz (THz) communication with a Tbps transmission rate requires novel channel propagation models and designs for antennas and RF components to address the challenges in THz bands, including molecular absorption effects, high penetration loss, and frequent blockages. An extreme data rate, ultra-low latency, and cm-level localization in the THz band will accelerate a massive deployment of IoT devices, where device nodes may re-transmit other users’ messages. In this work, we study a THz cooperative network with an N-relay decode-and-forward relay selection scheme, where users are equipped with a fluid antenna system (FAS) receiver technology. FAS offers paramount flexibility and numerous advantages, especially for biomedical applications. Moreover, the proposed system considers non-ideal transceiver hardware that emits residual transceiver hardware impairments (RTHI) noise that notably deteriorates the performance of high-rate networks. Existing research often focuses on ideal transceiver hardware, overlooking the impact of RTHI noise. As a result, we introduce a rapidly converging semi-infinite expression for the coverage probability (CP), validated through extensive Monte Carlo simulations. The results highlight a substantial degradation in the CP performance with each distance meter. Thus, deploying devices for relaying messages and employing FAS receivers significantly enhance the CP performance.

This study delves into the capabilities of reconfigurable intelligent surfaces (RISs) in enhancing bidirectional non-orthogonal multiple access (NOMA) networks. The proposed approach partitions RIS to optimize the channel conditions for NOMA users, improving NOMA gain and eliminating the requirement for uplink (UL) power control. The proposed approach is rigorously evaluated under four practical operational regimes; 1) Quality-of-Service (QoS) sufficient regime, 2) RIS and power efficient regime, 3) max-min fair regime, and 4) maximum throughput regime, each subject to both UL and downlink (DL) QoS constraints. By leveraging decoupled nature of RIS portions and base station (BS) transmit power, closed-form solutions are derived to show how optimal RIS partitioning can meet UL-QoS requirements while optimal BS power control can ensure DL-QoS compliance. Analytical findings are validated by simulations, highlighting the significant benefits that RISs can bring to the NOMA networks in the aforementioned operational scenarios.

The integration of reconfigurable intelligent surfaces (RISs) and grant-free non-orthogonal multiple access (GF-NOMA) has emerged as a promising solution for enhancing spectral efficiency and massive connectivity in future wireless networks. This paper proposes a GF-NOMA communication network enabled by simultaneously transmitting and reflecting RISs (STAR-RIS). In the proposed GF-NOMA, all user equipments (UEs) have instantaneous access to resource blocks (RBs) without the need for grant acquisition and power control as in the traditional grant-based NOMA schemes. Specifically, we have considered two regimes of interest: 1) the max-min fair (MMF) regime and 2) the max-sum throughput (MST) regime. To achieve the required power disparity, a two-level power control mechanism is proposed; initially, the UEs are clustered according to their channel gains. Additionally, we introduce a multi-level GF-NOMA (MGF-NOMA) scheme that adjusts the transmit power levels for each UE in the cluster. The second level of power disparity is achieved through the assignment of STAR-RISs to the clusters and optimal partitioning of STAR-RIS to support each of the cluster members. Specifically, we have also derived the closed-form equations for the optimal partitioning of STAR-RIS within the clusters for both regimes of interest. Simulation results demonstrate that the proposed STAR-RIS-aided MGF-NOMA yields a gain of 60% and 20% in the MST regime with active and passive RIS realization, respectively. Furthermore, the active and passive RIS-based MGF-NOMA achieve nearly the equivalent fairness that can be obtained through optimal power control in the MMF regime. The finding emphasizes the potential of integrating STAR-RIS with GF-NOMA as a robust and promising solution for future wireless communication systems.

The integration of reconfigurable intelligent surfaces (RISs) and grant-free non-orthogonal multiple access (GF-NOMA) has emerged as a promising solution for enhancing spec-tral efficiency (SE) and massive connectivity in future wireless networks. This paper proposes a novel virtual RIS partitioning mechanism for GF-NOMA, where all user equipments (UEs) within a specific NOMA cluster have instantaneous access to resource blocks (RBs) without the need for grant acquisition and power control as in the traditional grant-based NOMA schemes. To achieve the required power disparity, RIS portions are allocated to the UEs in a manner that increases the reception power disparity. We derive closed-form equations for optimal RIS portions in two regimes of interest: 1) max-min fair regime and 2) maximum throughput regime. Simulation results demonstrate that the proposed RIS-assisted GF-NOMA yields a gain of 28% and 15% in terms of max-sum rate and max-min rate, respectively, outperforming existing grant-based approaches. The study highlights the potential of combining RIS with GF-NOMA as a powerful solution for future wireless communication systems.

Reconfigurability and innovative design approaches to radio frequency components and network infrastructure are critical for the development of future communication networks, particularly beyond 5G (B5G), which aim to support the proliferation of Internet of Things (IoT) devices. Leveraging its favorable performance characteristics and potentially low cost, the fluid antenna system (FAS) has emerged as a compelling solution, garnering significant interest due to its reconfigurability, small form factor, flexibility, and transparency. This paper presents a comprehensive analysis of FAS in the context of B5G networks, with a focus on its theoretical performance and practical implementations. By deriving formulas for the semi-infinite outage probability and ergodic capacity of FAS receivers in equally correlated Nakagami-m channels, we showcase the remarkable diversity performance exhibited by FAS receivers, even with a half-wavelength antenna size. Monte Carlo simulations are employed to validate our theoretical findings in terms of the number of antenna ports and transmission power.

Millimeter-wave networks have already been successfully rolled out in many countries and now the research direction heads toward new technologies and standards to enable Tbps rates for future sixth-generation (6G) wireless communication systems. This work studies a point-to-point terahertz (THz) communication network exploiting the concept of a fluid antenna system (FAS) over correlated alpha-mu fading channels, nicely fitting the THz communication. Furthermore, the considered system is expanded to the selection-combining-FAS (SC-FAS) and maximum-gain-combining-FAS (MGC-FAS) diversity variates at the receiver side. The proposed FAS and its diversity configuration techniques are aimed to combat the high path loss, blockages, and molecular absorption effect related to the THz band. Our contribution includes comprehensive outage probability (OP) performance analysis for the THz band given the non-diversity and diversity FAS receivers. Moreover, the derived outage probability formulas are verified via Monte Carlo simulations. Numerical results have confirmed the superior performance of the MGC-FAS scheme in terms of OP. Finally, this work justifies that a higher number of antenna ports dramatically improves the system performance, even in the presence of correlation.

A millimeter-wave antenna with enhanced gain and efficiency is presented in this work. A decagonal-shaped patch antenna for the desired 28 GHz frequency is initially utilized, the gain of which is enhanced by the Fabry-Perot cavity technique. The metasurface used in the Fabry-Pérot cavity was placed at different points. The antenna gain and efficiency were initially measured as 4.45 dBi and 0.69, respectively. However, introducing a metasurface at a distance of 5.4 mm enhanced the gain and efficiency to 5.16 dBi and 0.24, respectively. As a result, the total maximum gain and efficiency achieved are 9.61 dBi and 0.93. A bandwidth of 1.45 GHz is also attained, which covers the 28 GHz frequency band. The antenna and metasurface are successfully fabricated and tested. The results validate that the proposed antenna can be used in 5G applications.

A systematic optimization of parameters related with Artificial Neural Network (ANN) is absolutely necessary to extract the best possible optimized ANN, therefore gaining traction for the development of behavioral models for advanced Radio Frequency (RF) and microwave components in the wireless industry. This paper develops and demonstrates a hybrid Slime Mould Algorithm (SMA)-ANN based modelling approach for fully printed Vanadium Dioxide (VO2) RF switches, which constitute a pivotal part for next-generation reconfigurable components. At first, ANN using cascade-forward neural network architecture is exploited to develop behavioral model for VO2switch. Thereafter, parameters of ANN are tuned with SMA optimization algorithm. Finally, both ANN and hybrid SMA-ANN approaches are compared with conventional regression-based metrics namely mean squared error, mean absolute error, coefficient of determination, simulation time, parameters' tuning time, complexity of the models and ability of the models to predict on untrained data to establish the pros and cons of each approach.

The accuracy and convergence of Artificial Neural Network (ANN) based models are contingent on initial weights as they employ backpropagation algorithm. To address these issues, this paper investigates and develops accurate Global Optimization (GO) assisted ANN based small-signal behavioral models for Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT). Two potent explorer-exploiter frameworks-based optimization algorithms namely Grey Wolf Optimization-Particle Swarm Optimization (GWO-PSO) and Whale Optimization Algorithm (WOA) are utilized to fine-tune the initial weights of ANN. Thereafter, ANN, GWO-PSO- and WOA-assisted ANN based behavioral models are thoroughly examined and evaluated for various regression metrics. A strong correlation between the predicted and measured scattering parameters across the entire frequency spectrum is observed. We found both GO assisted ANN based models produced accurate models. However, GWO-PSO-ANN based models have shown better convergence behavior and at the same time the most accurate among all the tested models in this paper.

An intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) massive multiple input multiple output (MIMO) system with transmit antenna selection (TAS) using orthogonal space-time block codes (OSTBC) scheme is proposed in this paper. This system combines TAS and IRS with hybrid analog-digital beamforming (HBF) for 60 GHz mmWave communications in order to exploit the benefits of TAS, OSTBC, analog beamforming (ABF), and transmit digital precoding techniques. The proposed system, however, benefits from the transmit diversity gain of OSTBC scheme as well as from the signal-to-noise ratio (SNR) gains of both the beamformer and the IRS technology. The simulation results show that TAS-OSTBC system with zero-forcing precoding outperforms the conventional TAS-OSTBC scheme. Furthermore, the bit error rate (BER) performance significantly improves as the number of antenna array elements increases due to providing a beamforming gain. In addition, increasing the number of reflecting elements further enhances the BER performance. It is also found from the simulation results that the TAS-OSTBC system with hybrid precoding has better performance than that of TAS-OSTBC with ABF, and IRS-assisted systems significantly outperform the conventional systems without the IRS technology. This makes the proposed IRS-assisted system an appealing solution for internet-of-things (IoT) networks.

Intelligent reflecting surface (IRS)-assisted beamspace millimeter-wave (mmWave) multiuser massive multiple input multiple output (MIMO) with interference-aware (IA) beam selection scheme is proposed in this paper. This proposed scheme is capable of intelligently reconfiguring the radio environment and utilizing the beam selection for the sake of reducing the number of required radio frequency $( R$F) chains without any noticeable performance degradation. To ensure a fair comparison, the achievable sum-rate and energy efficiency (EE) performance metrics of the proposed scheme are evaluated and compared to that of IRS-assisted fully-digital systems with zero-forcing $(Z$F) precoding and the conventional systems without the IRS technology. Simulation results demonstrate that the proposed IRS-assisted beamspace mmWave massive MIMO system with IA beam selection algorithm outperforms the conventional system without IRS. It is also shown that the performance improves when the number of reflecting elements is more than the total number of mobile users. Moreover, the proposed scheme can potentially offer higher EE than the conventional schemes. Therefore, this shows that the proposed system can be considered as an alternative solution for the future generation of wireless systems.

Quantum Annealing (QA) uses quantum fluctuations to search for a global minimum of an optimization-type problem faster than classical computer. To meet the demand for future internet traffic and mitigate the spectrum scarcity, this work presents the QA-aided maximum likelihood (ML) decoder for multi-user non-orthogonal multiple access (NOMA) networks as an alternative to the successive interference cancellation (SIC) method. The practical system parameters such as channel randomness and possible transmit power levels are taken into account for all individual signals of all involved users. The brute force (BF) and SIC signal detection methods are taken as benchmarks in the analysis. The QA-assisted ML decoder results in the same BER performance as the BF method outperforming the SIC technique, but the execution of QA takes more time than BF and SIC. The parallelization technique can be a potential aid to fasten the execution process. This will pave the way to fully realize the potential of QA decoders in NOMA systems.

Intelligent surfaces have recently been presented as a revolutionary technique and recognized as one of the candidates for beyond fifth-generation wireless networks. This paper investigates the physical layer security of a large intelligent surface (LIS) aided wireless system over Nakagami-m channels. We propose a phase-based adaptive modulation scheme, where LIS’s phase-shift optimization process is effectively utilized to enhance the system’s security. Moreover, the effect of the Nakagami-m fading parameter (m), correlation parameter ($\rho$), and a number of passive LIS elements (M) on the system performance are examined. The significant improvement in confidentiality is shown while evaluating the bit error rate performance of the proposed scheme.

Reconfigurable intelligent surfaces (RISs) have sparked a renewed interest in the research community envisioning future wireless communication networks. In this study, we analyzed the performance of RIS-enabled non-orthogonal multiple access (NOMA) based device-to-device (D2D) wireless communication system, where the RIS is partitioned to serve a pair of D2D users. Specifically, closed-form expressions are derived for the upper and lower limits of spectral efficiency (SE) and energy efficiency (EE). In addition, the performance of the proposed NOMA-based system is also compared with its orthogonal counter-part. Extensive simulation is done to corroborate the analytical findings. The results demonstrate that RIS highly enhances the performance of a NOMA-based D2D network.

Vehicle-to-everything (V2X) connectivity in 5G-andbeyond communication networks supports the futuristic intelligent transportation system (ITS) by allowing vehicles to intelligently connect with everything. The advent of reconfigurable intelligent surfaces (RISs) has led to realizing the true potential of V2X communication. In this work, we propose a dual RIS-based vehicle-to-infrastructure (V2I) communication scheme. Following that, the performance of the proposed communication scheme is evaluated in terms of deriving the closed-form expressions for outage probability, spectral efficiency and energy efficiency. Finally, the analytical findings are corroborated with simulations which illustrate the superiority of the RIS-assisted vehicular networks.

Fluid antenna systems (FAS) enable mechanically flexible antennas that offer adaptability and flexibility for modern communication devices. In this work, we present a conceptual model for a single-antenna N-port (SANP) FAS over spatially correlated Nakagami-m fading channels and compare it with the traditional diversity schemes in terms of outage probability. The proposed FAS model switches to the best antenna port and resembles the operation of a selection combining (SC) diversity. FAS improves the quality of service (QoS) of the network through antenna port selection. The advantage of FAS is the ability to fit hundreds of antenna ports into a half-wavelength antenna size at the cost of spatial channel correlation. Simulation results demonstrate the superior outage probability performance of FAS at several tens of antenna ports compared to the traditional diversity schemes such as maximum ratio combining, equal gain combining, and SC. Moreover, the novel probability and cumulative density functions for the land mobile correlated Nakagami-m random variates are evaluated in this paper.

In this paper, we investigate a non-orthogonal multiple access (NOMA) assisted cognitive satellite-terrestrial network under practical system conditions, such as transceiver hard-ware impairments, channel state information mismatch, imperfect successive interference cancellation and interference noises. Generalized coverage probability formulas for NOMA users in both primary and secondary networks are derived considering the impact of interference temperature constraint. Moreover, the numerical results demonstrate superior outperformance compared to the ones obtained for an orthogonal multiple access scheme. Finally, the derived analytical findings are fully supported by thorough Monte Carlo simulations.

This paper develops and presents a CAD deployability of small-signal model of Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT). First, a Gaussian Process Regression (GPR), a non-parametric probability-based method, is utilized to develop a small-signal model to effectively describe the behavior of the device. The model is developed to captures the bias and frequency dependence of GaN HEMT. The performance of the model is supplemented by advanced preprocessing and tuning of the hyperparameters of GPR approach. The tuning is done using 10-fold cross-validation error loss function. To examine the model's generalization ability the Mean squared error (MSE) metrics is used for both training and testing sets. Thereafter, the developed GPR based model is incorporated into CAD environment. Then the performance of the model is evaluated for stability and is also investigated for the usefulness of the model in class-F power amplifier design. The amplifier achieves excellent maximum available gain and small-signal voltage gain.

In this paper, we study a cognitive hybrid satellite-terrestrial relay network with imposed practical limitations, such as channel state information mismatch and transceiver-induced hardware impairments. Moreover, it is assumed that the network undergoes multiple independent and non-identically distributed interference noises arising from neighboring transmitters. Generalized closed-form expressions of the outage probability for a terrestrial user are obtained while taking into account the effect of an interference temperature constraint. Finally, analytical derivations are verified through Monte Carlo simulation and the impact of impairments is examined.

In this paper, we analyze the system performance of a large intelligent surface (LIS) enabled wireless system over Nakagami-m channels. We derive closed-form expressions of the outage probability, ergodic capacity, and average bit error rate using different approximation methods, namely, central limit theorem (CLT), Gamma and generalized-K$(K_{\mathrm{G}})$. The effects of a number of passive LIS pixels$(N)$and fading parameters on the system performance are examined. Results show that the Gamma and$K_{\mathrm{G}}$approximations are precise given different values of$N$, while the CLT approximation's accuracy depends on the number of LIS elements implemented. Finally, analytical findings are validated by thorough Monte Carlo simulations.

In this paper, the outage probability (OP) of the two-hop cooperative non-orthogonal multiple access network with an energy-constrained cooperative agent is evaluated over generalized α-µ and κ-µ fading models. The power splitting relaying protocol is implemented at the cooperative agent, acting as a relay in amplify-and-forward mode. The effect of hardware impairments (HIs) at the radio frequency front-ends of transceivers are incorporated during the performance evaluation. The results based on the derived analytical expressions suggest the importance of considering HIs for given network architecture and allow one to evaluate the OP over various statistical models.

This paper investigates a non-orthogonal multiple access (NOMA) assisted cognitive satellite-terrestrial network which is practically limited by interference noises, transceiver hardware impairments, imperfect successive interference cancellation, and channel state information mismatch. Generalized outage probability expressions for NOMA users in both primary and secondary networks are derived considering the impact of interference temperature constraint. Finally, obtained results are corroborated by Monte Carlo simulations and compared with the orthogonal multiple access to show the superior performance of the proposed network model.

This paper provides a performance evaluation of two-hop non-orthogonal multiple access (NOMA) architecture with energy harvesting (EH) cooperative agent and channel gains following the k-m fading, through analysis of ergodic capacity with respect to hardware impairments and channel conditions. The performance results of the distant user over two EH protocols, namely power splitting and time-switching relaying, are obtained and compared with simulation outcomes. The developed framework allows to evaluate the network under a range of external conditions and infers the importance of considering the hardware impairments.

The physical-layer security (PLS) of wireless networks has witnessed significant attention in next-generation communication systems due to its potential toward enabling protection at the signal level in dense network environments. The growing trends toward smart mobility via sensor-enabled vehicles are transforming today's traffic environment into Internet of Vehicles (IoVs). Enabling PLS for IoVs would be a significant development considering the dense vehicular network environment in the near future. In this context, this article presents a PLS framework for a vehicular network consisting a legitimate receiver and an eavesdropper, both under the effect of interfering vehicles. The double-Rayleigh fading channel is used to capture the effect of mobility within the communication channel. The performance is analyzed in terms of the average secrecy capacity (ASC) and secrecy outage probability (SOP). We present the standard expressions for the ASC and SOP in alternative forms, to facilitate analysis in terms of the respective moment generating function (MGF) and characteristic function of the joint fading and interferer statistics. Closed-form expressions for the MGFs and characteristic functions were obtained and Monte Carlo simulations were provided to validate the results. Approximate expressions for the ASC and SOP were also provided, for easier analysis and insight into the effect of the network parameters. The results attest that the performance of the considered system was affected by the number of interfering vehicles as well as their distances. It was also demonstrated that the system performance closely correlates with the uncertainty in the eavesdropper's vehicle location.

This paper studies the physical layer security of a vehicular communication network in the presence of interference constraints by analysing its secrecy capacity. The system considers a legitimate receiver node and an eavesdropper node, within a shared network, both under the effect of interference from other users. The double-Rayleigh fading channel is used to capture the effects of the wireless communication channel for the vehicular network. We present the standard logarithmic expression for the system capacity in an alternate form, to facilitate analysis in terms of the joint moment generating functions (MGF) of the random variables representing the channel fading and interference. Closed-form expressions for the MGFs are obtained and Monte-Carlo simulations are provided throughout to validate the results. The results show that performance of the system in terms of the secrecy capacity is affected by the number of interferers and their distances. The results further demonstrate the effect of the uncertainty in eavesdropper location on the analysis.

Non-orthogonal multiple access (NOMA) is considered to be one of the promising multiple access techniques for 5G networks. This paper studies a decode-and-forward cooperative underlay cognitive radio NOMA network. Closed-form expressions for the outage probability of two NOMA secondary destination users (D1and D2) are evaluated. Furthermore, optimal power allocation factors for different distances of D1are found to satisfy the outage probability (OP) fairness for both users. Moreover, the OP for NOMA compared to that of conventional multiple access. Finally, the obtained analytical expressions are corroborated by Monte Carlo simulation.

The broadcast nature of wireless networks makes them vulnerable to eavesdropping attacks; therefore, physical layer security (PLS) becomes essential to protect the signal at the physical layer. In this paper, we investigate PLS aspects in terms of the secrecy capacity (SC) in hybrid radio frequency (RF)/visible light communication (VLC) networks. First, we design RF-and VLC-based beamforming vectors to maximize the achievable SC. Moreover, using these vectors, we solve the power minimization problem satisfying the required SC. The results provide useful insights into how the eavesdropper's location affects the power consumption profile. Finally, the results reveal that the performance of the VLC network in terms of the consumed power per bits/s/Hz is more efficient than the RF one.

In this paper, we investigate the performance of spectrally and energy efficient orthogonal frequency-division multiplexing (SEE-OFDM) based visible light communications (VLC) systems. We propose to apply non-orthogonal multiple access (NOMA) for the downlink in SEE- OFDM based VLC network. Moreover, we provide a novel approach in decoding the composite NOMA signal. Next, based on the considered channel conditions, we analyze the impact of power-allocating coefficients on the bit-error rate (BER) performance. Finally, satisfying the target BER, we estimate the data rate regions achievable by the receivers under the derived system parameters and then compare the results with the ones obtainable for orthogonal multiple access.

Wireless power transfer and energy harvesting have attracted a significant research attention in terms of their application in cooperative relaying systems. Most of existing works in this field focus on the half-duplex (HD) relaying mechanism over certain fading channels, however, in contrast, this paper considers a dual-hop full-duplex (FD) relaying system over a generalized independent but not identically distributed α-μ fading channel, where the relay node is energy-constrained and entirely depends on the energy signal from the source node. Three special cases of the α-μ model are investigated, namely, Rayleigh, Nakagami- m and Weibull fading. As the system performance, we investigate the outage probability (OP) for which we derive exact unified closed-form expressions. The provided Monte Carlo simulations validate the accuracy of our analysis. Moreover, the results obtained for the FD scenario are compared to the ones related to the HD. The results demonstrate that the decode-and-forward relaying outperforms the amplify-and-forward relaying for both HD and FD scenarios. It is also shown that the FD scenario performs better than the HD relaying systems. Finally, we analyzed the impact of the fading parameters α and μ on the achievable OP.

In this paper, a two-hop decode-and-forward wireless powered relaying cognitive radio network with interference alignment over Rayleigh fading channels is investigated. The energy-constrained secondary relay node harvests energy from both the information and interference signals. Then, the harvested energy is used by the relay to forward the information signal from the source to the destination node. By applying beamforming matrices to primary and secondary networks, the performance metrics, such as outage probability, capacity, and bit error rate are studied under perfect and imperfect channel state information scenarios for both power-splitting relaying (PSR) and time-switching relaying (TSR) protocols. In addition, the optimal network performance is achieved by calculating the optimal energy harvesting time-switching and power-splitting coefficients. Finally, closed-form expressions for the outage probability of primary and secondary users are derived. Monte Carlo simulation results corroborate the analytical ones and show that the PSR technique outperforms TSR in the considered system model.

In this paper, a two-hop decode-and-forward cognitive radio system with deployed interference alignment is considered. The relay node is energy- constrained and scavenges the energy from the interference signals. In the literature, there are two main energy harvesting protocols, namely, time-switching relaying and power-splitting relaying. We first demonstrate how to design the beamforming matrices for the considered primary and secondary networks. Then, the system capacity under perfect and imperfect channel state information scenarios, considering different portions of time-switching and power-splitting protocols, is estimated.

In this paper, we consider a two-hop amplify-and- forward (AF) relaying system, where the relay node is energy-constrained and harvests energy from the source node. In the literature, there are three main energy-harvesting (EH) protocols, namely, time-switching relaying (TSR), power-splitting (PS) relaying (PSR) and ideal relaying receiver (IRR). Unlike the existing studies, in this paper, we consider α-μ fading channels. In this respect, we derive accurate unified analytical expressions for the ergodic capacity for the aforementioned protocols over independent but not identically distributed (i.n.i.d) α-μ fading channels. Three special cases of the α-μ model, namely, Rayleigh, Nakagami-m and Weibull fading channels were investigated. Our analysis is verified through numerical and simulation results. It is shown that finding the optimal value of the PS factor for the PSR protocol and the EH time fraction for the TSR protocol is a crucial step in achieving the best network performance.

This paper studies a two-hop decode-and-forward underlay cognitive radio system with interference alignment technique. An energy-constrained relay node harvests the energy from the interference signals through a power-splitting (PS) relaying protocol. Firstly, the beamforming matrices design for the primary and secondary networks is demonstrated. Then, a bit error rate (BER) performance of the system under perfect and imperfect channel state information (CSI) scenarios for PS protocol is calculated. Finally, the impact of the CSI mismatch parameters on the BER performance is simulated.

Interference alignment is an effective capacity achieving technique in wireless networks. We propose a method of achieving maximum degrees of freedom for a considered three-cell compounded MIMO network. We first define the compounded MIMO network as a combination of IC and X-channel, and then design transmit beamforming matrices to mitigate interference under the considered MIMO network scenario. Finally, we analyse the degrees of freedom region of the proposed interference alignment scheme and present results derived for the three-cell MIMO network scenario.

Interference alignment is an effective technique for reducing interference in wireless networks. This paper proposes a generalized interference alignment and cancellation scheme for a cellular network with multiple-input multiple-output users under a Gaussian interfering broadcast channel scenario. We first focus on a three-cell network scenario to demonstrate the basic principle of how to design the transmit beamforming matrix using a non-iterative closed-form approach. We further analytically define the degree of freedom region and numerically confirm the validity of the proposed scheme. Finally, we generalize the proposed method to the L -cell case and consider the impact of different antenna configurations to maintain the proposed scheme.

Interference Alignment is an effective technique to reduce interference in a wireless system. This paper proposes an alignment based interference cancellation scheme for a multi-cell network with multiple-input multiple-output users under Gaussian Interference Broadcast Channel scenario. We focus the description on a three cell network scenario and design transmit beamforming matrix using a non-iterative closed-form approach. This approach utilizes the possibility to split up the role of the transmit beamforming matrix according to the type of interference caused by a base station. Simulation results confirm the theoretical findings and demonstrate that the proposed scheme can achieve the (L-1) degrees of freedom for each user.

This paper proposes an alignment based interference cancellation scheme for a multi-cell network with multiple-input multiple-output users under a Gaussian Interference compounded broadcast channel scenario. The basic idea is to split up the role of the transmit beamforming matrix according to the type of interference caused by each base station. It will be shown that, for a network of L base stations, the proposed method would result in achieving (L - 1) degrees of freedom per user and convert the multi-cell multi-user MIMO channel into a set of single-cell single-user MIMO channels. Finally, we derive the relationship between all the relevant network elements as Nt= (L - ds+ 1)K'Nr+ 1, where Ntand Nrare the numbers of transmit and receive antennas, respectively, L and dsdenote the number of cells and the number of data streams transmitted from each base station, and K' is the number of users per cell defined under the proposed system model. Hence, we show that the proposed scheme makes it possible to implement interference alignment using less antenna resources.