Power Splitting Factor Research Articles

NOMA Visible Light Communications with Distinct Optical Beam Configurations

Visible light communication (VLC) has been viewed as one promising candidate to mitigate the challenging spectrum crisis and radio frequency interference in future 6G mobile communications and networking. Due to the relatively limited baseband modulation bandwidth of VLC light sources—typically, light-emitting diodes—non-orthogonal multiple access (NOMA) techniques have been proposed and explored to enhance the spectral efficiency (SE) of VLC systems. However, almost all reported NOMA VLC schemes focus on well-discussed applications employing a Lambertian light beam configuration and ignore the potential applications with distinct non-Lambertian optical beam configurations. To address this issue, in this work, the performance of non-Lambertian optical beam configuration-based NOMA VLC is comparatively investigated for future 6G mobile networks. The numerical results demonstrate that, for a fundamental two-user application scenario with the far user located at the corner position, a maximum sum rate gain of about 15.6 Mbps could be provided by the investigated distinct non-Lambertian beam-based NOMA VLC, compared with the maximum sum rate of about 93.3 Mbps for the conventional Lambertian configuration with the same power splitting factor.

Secure IRS-assisted energy scavenging NOMA impaired by realistic factors

Intelligent reflective surface (IRS)-assisted energy scavenging (ES) non-orthogonal multiple access (NOMA) with jamming (sIEnoma) is promising for high spectral efficiency, energy efficiency, information security, and communication reliability. Nonetheless, practical imperfections, such as channel state information imperfection (CSIi), hardware imperfection (HWi), fading severity, and nonlinear energy scavenging (nlES) impact scavenged energy, information security, and communication reliability of sIEnoma. Accordingly, this paper proposes performance analysis for sIEnoma under these imperfections to quickly assess its potentials without time-consuming simulations. Results show that imperfections (HWi, CSIi, fading severity, nlES) and specifications (IRS, NOMA) significantly impact performance of sIEnoma. Nevertheless, proper adoption of power splitting factor, desired data rate, HWi level, and time switching coefficient can hinder complete outage in sIEnoma. Additionally, optimal metrics are achieved by configuring system parameters properly. Moreover, the proposed sIEnoma outperforms its baseline (IRS-assisted ES orthogonal multiple access with jamming).

Sum-Rate Maximization for a Hybrid Precoding-Based Massive MIMO NOMA System with Simultaneous Wireless Information and Power Transmission

Non-orthogonal multiple access (NOMA) has emerged as a key enabling technology in the realm of millimeter-wave (mmWave) massive MIMO (mMIMO) systems for enhancing spectral efficiency (SE). Furthermore, it is believed that simultaneous wireless information and power transmission (SWIPT) will allow for the system’s energy efficiency (EE) to be maximised. The effectiveness of the mmWave mMIMO-NOMA system along with SWIPT has been examined in this article under multi-user (MU) scenarios. This paper’s major goal is to construct a low-complexity hybrid-precoder (HP) while taking into account the sub-connected (SC) architecture. The linear precoder is a computationally demanding technique as a result of the matrix inversion. The authors of this paper have suggested a symmetric sequential over-relaxation (SSOR) complex regularised zero-forcing (CRZF) linear precoder. The power distribution for the mmWave mMIMO-NOMA system and power splitting factors for SWIPT are jointly tuned to maximize the sum rate along with the suggested SSOR-CRZF precoder. In regards to complexity, SE, and EE, the SSOR-CRZF-HP surpasses conventional linear precoders.

Resource allocation algorithm for downlink secure transmission in wireless EH cooperative networks with idle relay-assisted jamming

In wireless Energy Harvesting (EH) cooperative networks, we investigate the problem of secure energy-saving resource allocation for downlink physical layer security transmission. Initially, we establish a model for a multi-relay cooperative network incorporating wireless energy harvesting, spectrum sharing, and system power constraints, focusing on physical layer security transmission in the presence of eavesdropping nodes. In this model, the source node transmits signals while injecting Artificial Noise (AN) to mitigate eavesdropping risks, and an idle relay can act as a jamming node to assist in this process. Based on this model, we formulate an optimization problem for maximizing system secure harvesting energy efficiency, this problem integrates constraints on total power, bandwidth, and AN allocation. We proceed by conducting a mathematical analysis of the optimization problem, deriving optimal solutions for secure energy-saving resource allocation, this includes strategies for power allocation at the source and relay nodes, bandwidth allocation among relays, and power splitting for the energy harvesting node. Thus, we propose a secure resource allocation algorithm designed to maximize secure harvesting energy efficiency. Finally, We validate the correctness of the theoretical derivation through Monte Carlo simulations, discussing the impact of parameters such as legitimate channel gain, power splitting factor, and the number of relays on secure harvesting energy efficiency of the system. The simulation results show that the proposed secure energy-saving resource allocation algorithm effectively enhances the security performance of the system.

Kinerja Sistem Hybrid Radio Frequency Energy Harvesting Pada Sistem Komunikasi V2V

This article investigates the impact of hybrid Radio Frequency Energy Harvesting (RF-EH) techniques on cooperative Vehicle-to-Vehicle (V2V) communications systems. The energy harvesting (EH) process is carried out in the vehicle or vehicle transmitter as a source using the Time Switching (TS) protocol and in the vehicle or relay vehicle using the Power Splitting (PS) protocol. The transmitter or source vehicle obtains the RF signal for the EH process from the base station (BS), while the relay vehicle obtains the RF signal from the transmitter or source vehicle. System performance is presented with Outage Probability (OP) values ​​for different EH parameters, namely, time switching factor, α and power splitting factor â. From the simulation results, all parameters influence the OP value. The higher the value of the RF-EH parameters (α and â) results in a lower OP value. For noise power, N_0 = -100 dBm, the best OP value for α = 0.7 is 0.1214 and the best OP value for â = 0.8 is 0.1557.

Optimization of multi-user fairness in RIS-enhanced UAV secure transmission systems

This paper proposes a reconfigurable intelligent surface (RIS)-enhanced unmanned aerial vehicle (UAV) secure communicating scheme with multiple mutually-untrusted ground users (GUs). To resist eavesdropping, a pre-defined artificial noise (AN) is added to the intended signal at UAV for scheduled GUs in each time slot. The GU scheduling schemes, UAV trajectories and transmit power allocations in different time slots are jointly designed to ensure communication security for all GUs. To boost secrecy rate of the system while ensuring secure fairness among GUs, we conduct a joint optimization process, involving optimizing UAV trajectories, RIS phase shifts, GU scheduling schemes, and UAV transmit power splitting factors, adhering to the constraints of UAV mobility, RIS phase shifts and other related constraints. To solve this non-convex optimization, we utilize the block coordinate descent (BCD) method for problem decomposition, coupled with an iterative algorithm to optimize the resulting sub-problems. To further solve the non-convex sub-problems, we employ the variable substitution to convexify the transmit power allocation, the semi-deterministic relaxation (SDR) to convexify the RIS passive beamforming and successive convex approximation (SCA) to convexify UAV mobility constraints. Simulation results show the convergence and effectiveness of the proposed scheme, compared to the benchmark schemes, the average worst-case secrecy rate increases by 32.33%, 60.38% and 80.09‘% respectively.

Joint Beam-Forming Optimization for Active-RIS-Assisted Internet-of-Things Networks with SWIPT

Network energy resources are limited in communication systems, which may cause energy shortages in mobile devices at the user end. Active Reconfigurable Intelligent Surfaces (A-RIS) not only have phase modulation properties but also enhance the signal strength; thus, they are expected to solve the energy shortage problem experience at the user end in 6G communications. In this paper, a resource allocation algorithm for maximizing the sum of harvested energy is proposed for an active RIS-assisted Simultaneous Wireless Information and Power Transfer (SWIPT) system to solve the problem of low performance of harvested energy for users due to multiplicative fading. First, in the active RIS-assisted SWIPT system using a power splitting architecture to achieve information and energy co-transmission, the joint resource allocation problem is constructed with the objective function of maximizing the sum of the collected energy of all users, under the constraints of signal-to-noise ratio, active RIS and base station transmit power, and power splitting factors. Second, the considered non-convex problem can be turned into a standard convex problem by using alternating optimization, semi-definite relaxation, successive convex approximation, penalty function, etc., and then an alternating iterative algorithm for harvesting energy is proposed. The proposed algorithm splits the problem into two sub-problems and then performs iterative optimization separately, and then the whole is alternately optimized to obtain the optimal solution. Simulation results show that the proposed algorithm improves the performance by 45.2% and 103.7% compared to the passive RIS algorithm and the traditional without-RIS algorithm, respectively, at the maximum permissible transmitting power of 45 dBm at the base station.

A novel resource allocation scheme for full-duplex NOMA systems with power splitting-based SWIPT

This paper introduces novel resource allocation (RA) algorithms for optimizing wireless network performance, focusing on a full-duplex (FD) base station (BS) employing non-orthogonal multiple access (NOMA) technology. Motivated by the intriguing trade-off introduced by the simultaneous wireless information and power transfer (SWIPT) scheme, in which achievable data rates are sacrificed to enhance harvested energy, this study aims to quantify the delicate equilibrium between two vital aspects meticulously: the overall achievable data rate facilitated by NOMA and FD technologies and the energy harvested via the SWIPT approach. Specifically, our focus is on jointly optimizing the enhancement of both data rate and harvested energy for downlink (DL) users where a multi-objective optimization approach is developed in the proposed RA algorithm to study the existing trade-off between these conflicting objective functions. This problem optimizes the power allocation for both the BS and the users, allocating subcarriers, and optimizing the power splitting factor for SWIPT scheme. We developed efficient iterative solutions for the intended RA problems because they involve complex mixed-integer nonlinear optimization challenges that are generally difficult to solve. The effectiveness of the proposed RA framework is demonstrated using simulation results. These results investigate whether FD MC-NOMA systems, enabled by the proposed RA algorithms, provide a significant increase in system throughput compared to both conventional half-duplex (HD) multicarrier orthogonal multiple access (MC-OMA) systems and HD MC-NOMA systems, as well as other baseline methods. The results also demonstrate that our proposed scheme allows for a greater power harvest than the OMA-FD configuration and other baseline schemes.

Dynamic User-Scheduling and Power Allocation for SWIPT Aided Federated Learning: A Deep Learning Approach

Federated learning (FL) has been considered as a promising paradigm for enabling distributed machine learning (ML) in wireless networks. To address the limited energy capacity of wireless devices, we propose a simultaneous wireless information and power transfer (SWIPT) aided FL, in which one FL server (FLS) co-located at a cellular base station (BS) uses SWIPT to simultaneously broadcast the global model to wireless user-devices (UDs) and provide wireless power transfer to them. The UDs then use the harvested energy to train their local models and further transmit the local models to the FLS for aggregation. To improve the spectrum efficiency, we consider that the UDs form a non-orthogonal multiple access (NOMA) group for simultaneously sending their local models over the same spectrum channel. Taking the UDs' time-varying available energy and channel conditions into account, we propose a dynamic optimization of the UDs-scheduling, the BS's transmit-power allocation, and the UDs' power-splitting factors for SWIPT, with the objective of minimizing the long-term energy consumption while ensuring the FL convergence. The optimization problem, however, is challenging to solve since it is a finite-horizon dynamic programming problem but with an unknown stopping time, and moreover, the action space covers both discrete and continuous variables. To address these difficulties, we first execute a series of equivalent transformations to reduce the number of decision variables and then formulate the problem as a stochastic shortest path problem, based on which we propose an actor-critic deep reinforcement learning algorithm with the proximal policy optimization to efficiently learn the policy that dynamically adjusts the UDs-scheduling for FL as well as the BS's transmit-power for SWIPT. Numerical results validate the effectiveness and performance of our proposed algorithm. The results demonstrate that our proposed algorithm can effectively reduce the long-term energy consumption in comparison with two baseline algorithms.

Multi-Objective Optimization in Solar and Wireless Energy Harvesting the IoT Relay Communication System

In this article, a solar and wireless energy harvesting (SWEH) Internet of Things network is presented. To address energy efficiency problems, we consider an amplify-and-forward relay node that harvests solar and wireless energy using the power splitting protocol to accomplish SWIPT. For the communication model under consideration, we derive the mathematical expressions for throughput and energy efficiency. We investigate the impact of both power transmitted by the source and power-splitting factor on the system’s achievable energy efficiency and the energy harvested. To maximize the contradictory objectives of energy efficiency and energy harvested simultaneously, we propose to use the Pareto-based multi-objective ant lion optimization algorithm (MOALO) and jointly optimize the transmitted power and power-splitting factor. In-depth simulation is used to determine the Pareto optimal values for transmitted power and power-splitting factor and to assess how the proposed algorithm performs in comparison to leading-edge algorithms such as NSGA-II, MOPSO, MOWOA, and MOMVO. The results unambiguously show that the suggested MOALO offers the best Pareto front within a reasonable amount of time. Finally, the results corroborate that the proposed SWEH system outperforms in terms of harvested energy and attainable energy efficiency.

Sum Rate Maximization for Intelligent Reflecting Surface-Assisted UAV-Enabled NOMA Network

In the next-generation network, intelligent reflecting surface (IRS), non-orthogonal multiple access (NOMA), and simultaneous wireless information and power transfer (SWIPT) are promising wireless communication techniques to effectively improve system sum rates. In traditional unmanned aerial vehicles (UAV) communication systems, the sum rate and coverage are greatly affected when there is an occlusion on the direct transmission link. To solve this problem, the IRS technology is introduced to improve the poor channel conditions. However, most of the previous research on IRS-assisted UAV to optimize system sum rate only considers frameworks that utilize the partially joint-combining techniques of IRS, NOMA, and SWIPT. In this paper, in order to further improve the sum rate of the system, we simultaneously integrate IRS, NOMA, and SWIPT technologies and establish a sum rate maximization optimization problem when the direct link is blocked. Then, an alternative optimization (AO) algorithm based on the maximizing system sum rate is proposed to solve the non-convex optimization problem, in which the IRS location and phase, the reflecting amplitude coefficient, UAV forwarding altitude, and power splitting factor are considered. To let the non-convex and non-linear function be transformed into a convex one, we first use an iterative approach to optimize the position of the IRS. After that, an optimization problem is constructed to maximize the system sum rate with the constraints of the IRS phase shifts, successful successive interference cancellation (SIC), maximum transmit power of base station (BS), and UAV. Numerical results show that the proposed algorithm outperforms the traditional orthogonal multiple access (OMA) and algorithms without IRS-assisted links in terms of the system sum rate.

Cooperative encryption over backscatter: Secure green communication for two-way energy harvesting relay networks

This paper focuses on the design of a novel cooperative jamming strategy and resource allocation scheme in two-way energy harvesting (EH) relay networks. For solving the security vulnerability challenges, a backscatter jamming strategy is proposed by leveraging the information signals as the carrier, which can degrade the eavesdropping link without extra energy consumption, delay and strict synchronization requirement. Based on the above design, we formulate the secure energy efficiency (SEE) maximization problem by jointly optimizing the transmission powers of two sources, two different power splitting (PS) factors and time allocation factor. Although the resulting optimization problem is highly non-convex due to fractional objective function and multivariate coupling, an iterative algorithm is developed to convert the original problem into a tractable version and obtain the resource allocation solutions. Simulation results show that the achievable SEE of the proposed scheme is better than other conventional schemes.

Joint Resource Allocation in a Two-Way Relaying Simultaneous Wireless Information and Power Transfer System

Simultaneous wireless information and power transfer (SWIPT) technology provides an efficient solution to energy-limited communication terminals in a wireless network. However, in the current application scenario of SWIPT technology, relays use all the collected energy forwarding to assist communication between source nodes, while ignoring the fact that relays can accumulate and store energy. This is of great practical significance in collaborative communication. By using a transmission scheme of a time-division broadcast for the direct transmission link, improvement of the system diversity gain through combining the technology at the receiver can be realized. Based on the above, we propose a two-way relay energy accumulation communication system, which is extended from a single relay system to a multi-relay system. The instantaneous transmission rate of the system link and the system equivalent profit are optimized by jointly optimizing the relay selection, time slot allocation factor, power splitting factor and relay transmit power. Compared with the comparison algorithm, the proposed algorithm shows a significant improvement in the performance of the system.

RIS-Assisted Cooperative NOMA With SWIPT

This letter proposes a two-stage reconfigurable intelligent surface (RIS)-assisted transmission scheme for cooperative non-orthogonal multiple access networks with simultaneous wireless information and power transfer. We focus on improving the achievable rate of the strong user with guaranteed weak user’s quality of service by jointly optimizing power splitting factors, beamforming coefficients, and RIS reflection coefficients in two transmission stages. To tackle this challenging problem, we first use the alternating optimization framework to transform it into three subproblems, and then apply the penalty-based arithmetic-geometric mean approximation algorithm and the successive convex approximation-based method to solve them. Numerical results verify the superiority of the proposed algorithm over the baseline schemes.

A Bidirectional Relay-Assisted Underlay Device-to-Device Communication in Cellular Networks: An IoT Application for FinTech

The device-to-device (D2D) networks bear a close resemblance to future Internet-of-Things (IoT) networks. IoT plays a significant role in the FinTech industry, especially in data security and context-aware applications. D2D communication in cellular networks has emerged as a competent technology for the upcoming future cellular networks. To improve spectral efficiency and data secrecy, we propose a two-phase network coding-based two-way decode-and-forward (DF) relaying policy for D2D communication. First, a suitable relay node is selected considering the end-to-end signal-to-interference-plus-noise ratio (SINR). Then, an XOR-based DF operation is performed when the signal transmitted by both the D2D users (DUEs) is successfully decoded at the relay node. In order to analyze the performance of the proposed two-way communication system, we derive the outage probability expression as a function of various system parameters, such as the SINR, position of both the relays and DUEs, power splitting factor, number of relays, and data rate. Furthermore, we also derive an expression for the error probability and average throughput of the D2D link to evaluate a fair comparison of the proposed approach with the traditional methods. The analytical results are also validated with the simulation results to justify the efficacy of the proposed method.

On Performance of a SWIPT Enabled FD CRN With HIs and Imperfect SIC Over α–μ Fading Channel

This paper investigates the performance of overlay full-duplex cooperative cognitive radio network in the presence of imperfect self interference cancellation over generalized <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha -\mu $ </tex-math></inline-formula> fading channels effected by nonlinearity of the propagation medium. In practice, physical transceivers create distortion which degrades the performance, hence, the impact of transceiver hardware impairments (HIs) is considered. To overcome the energy constraint problem, a hybrid simultaneous wireless information and power transfer receiver is adopted that includes both the time switching and the power splitting protocols. To improve reliability of the communication link, we employ a hybrid relaying protocol that combines both the decode-and-forward and amplify-and-forward relaying protocols. The closed-form expressions of outage probability and asymptotic outage probability are derived for both the primary and the secondary networks over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha -\mu $ </tex-math></inline-formula> fading channels. The diversity order, throughput, and energy efficiency of the considered network are derived. Optimal values of time switching factor is obtained for which the considered network exhibits optimum outage probability, maximum throughput and energy efficiency. Further, optimal value of power splitting factor is obtained for which the considered network shows maximum throughput and energy efficiency. Finally, the Monte-Carlo simulations validate correctness of the derived closed-form expressions.

On Outage Analysis in Overlay CCRN with RF Energy Harvesting and Co-channel Interference

This paper studies the effect of co-channel interference (CCI) on energy harvesting (EH) from radio frequency (RF) signal and the performance of reliable communication. An overlay mode of cooperative cognitive radio network (CCRN) model is considered that may support one-way communication between primary users (PUs) and two-way communications between secondary users (SUs). Closed form PU and SU outage expressions are derived in presence of CCI at two SU nodes and multiple antennas at PU transmitter. The absolute impact of CCI on the performance of the proposed system is analysed with respect to various parameters like, transmission power, interference-to-noise-ratio (INR), power splitting factor, number of CCI sources and number of antennas. About 20% and 15% improvements are achieved for PU and SU outage using two antennas compared to single antenna system model.

Physical Layer Security Enhancement via Intelligent Omni-Surfaces and UAV-Friendly Jamming

Intelligent reflecting surfaces (IRS) are considered one of the prominent technologies to be adopted in 6G and beyond networks. However, one of the main IRS limitations is restricting the communication to the reflective dimension, which means that users located behind the IRS surface cannot benefit from it. In this paper, we make use of intelligent omni-surfaces (IOS), as an alternative to IRS, in addition to unmanned aerial vehicles (UAV) to achieve secure communication in an Internet-of-Things (IoT) communication system. Specifically, we propose IOS-UAV assisted communication wherein an access point (AP) tries to send confidential information to a legitimate IoT device in presence of an eavesdropper. The UAV serves two fold; it acts as a friendly jammer that is trying to degrade the signal quality at the eavesdropper and as a source of energy to power up the IoT device via simultaneous wireless information and power transfer (SWIPT) to address the limited power available to it. We formulate an average secrecy rate maximization problem, which jointly optimizes the AP and UAV transmission powers, the UAV trajectory, IOS phase shifts and power splitting factor. The formulated problem is non-convex, therefore we exploit successive convex approximation (SCA) to tackle this issue. Simulation results show that the iterative SCA solution converges rapidly. Besides, the proposed scheme outperforms the traditional system without IOS by a gap of 140% in terms of the secrecy capacity.

Modified User Grouping and Hybrid Precoding for Information Decoding and Energy Harvesting in Hardware Impaired Point-To-Point MM-Wave Massive MIMO NOMA

The fifth generation (5G) and beyond 5G race covers both spectral-efficient and energy-efficient mechanisms such as simultaneous wireless information decoding and energy harvesting (SWIDEH). Structured as full or sub-connection of hybrid-precoded mm-wave massive multiple-input multiple-output non-orthogonal multiple access (NOMA) systems. However, the more practical hardware-impaired (HI) functionality yet to be considered for point-to-point (p-to-p) MIMO is conceived from an existing system. A hardware impairment-based power splitting is proposed for energy harvesting. The energy of the HI signal is harnessed through the joint optimization of power allocation (PA) for information decoding (ID) and the power splitting (PS) factor for energy harvesting (EH) using zero-forcing (ZF) precoding and minimum mean square error (MMSE) downlink (DL) detection. Based on the simulation results, an adaptive cluster head selection (CHS) criterion is proposed for analog precoding to mitigate intracluster interferences at a high signal-to-noise ratio (SINR). A successive interference cancellation (SIC) is carried out to enable dynamic channel overhead estimation and user signal detection. An investigation is done by simulating the system performance at varied numbers of users, the number of radio-frequency (RF) chains, and channel characteristics for modelling the user group threshold coupled with channel size reduction via an antenna selection scheme. Observing the execution time and some graphical plots shows that the spectral and energy efficiency can be improved by a random (R) or maximum norm average (MNA) channel vector formation from each user’s channel matrix combined with the best adaptive correlation threshold during CHS and a regularized ZF (RZF) precoder.

IRS-Enabled Backscattering in a Downlink Non-Orthogonal Multiple Access System

Intelligent reflecting surface (IRS)-enabled backscatter communications can be enabled by an access point (AP) that splits its transmit signal into modulated and unmodulated parts. This letter integrates non-orthogonal multiple access (NOMA) with this method to create a two-user primary system and a secondary system of IRS data. Considering the decoding order, we maximize the rate of the strongest primary user by jointly optimizing the IRS phase shifts, power splitting (PS) factor at the AP, and NOMA power coefficients while guaranteeing the quality of service (QoS) for both weak user and IRS data in the primary and secondary systems, respectively. The resulting optimization problem is non-convex. Thus, we split it into three parts and develop an alternating optimization (AO) algorithm. The advantage is that we derive closed-form solutions for the PS factor and NOMA power coefficients in the first two parts. In the third part, we optimize the phase shifts by exploiting semi-definite relaxation (SDR) and penalty techniques to handle the unit-modulus constraints. This algorithm achieves substantial gains (e.g., 40–68%) compared to relevant baseline schemes.