Simultaneous Wireless Information And Power Transfer Research Articles

Downlink MIMO-NOMA System for 6G Internet of Things

This paper proposes a system of 6G Internet of Things (IoT) based on downlink non-orthogonal multiple access (NOMA) technology, where the base station (BS) allows signals of the same frequency to serve users at different distances. In particular, we study a cooperative MIMO-NOMA system based on downlink simultaneous wireless information and power transfer (SWIPT) assistance. To improve the overall performance, we employ machine learning to optimize user-pairing and radio resource allocation. At the end of the paper, the simulation results are obtained, which fully prove that the MIMO-NOMA system constructed in this paper is correct in theory and can be realized in practice.

Performance evaluation of cooperative‐nonorthogonal multiple access‐based improved hybrid simultaneous wireless information and power transfer protocol

AbstractThe integration of cooperative nonorthogonal multiple access (CNOMA) and the improved hybrid simultaneous wireless information and power transfer (SWIPT) (IHS) protocol (termed the CNOMA‐IHS scheme) is proposed in this article. The proposed CNOMA‐IHS scheme performs the energy harvesting to energize the cooperative relay operation from cell center user to cell edge user and also convey information to the users as well. Moreover, the proposed scheme also conveys multiple different symbols to the users to improve the user channel capacities, ergodic sum capacity (ESC), and energy efficiency (EE). Finally, the analytical and simulation results illustrated the proposed scheme outperforms the existing CNOMA based SWIPT schemes as well as orthogonal multiple access based IHS scheme in terms of ESC and EE.

LF-SWIPT: Outage Analysis for SWIPT Relaying Networks Using Lossy Forwarding With QoS Guaranteed

We analyze the outage performance of a lossy forwarding (LF) relaying system with the simultaneous wireless information and power transfer (SWIPT) capability. In the system of LF with SWIPT (LF-SWIPT), a source broadcasts its message to both a relay and a destination. A relay node with SWIPT functionality harvests energy and decodes information from the source signal. The energy is split into two parts for information processing and message forwarding, respectively. For information processing, the relay attempts to decode the incoming source signal and forms an estimate. Unlike the existing decode-and-forward SWIPT system (DF-SWIPT), the estimate is always forwarded using the harvested energy. The destination performs joint decoding to recover the message with the signals received from both the source node and the relay node. We derive the outage probability for the LF-SWIPT system based on the theorem of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">source coding with side information</i> . The simulation results demonstrate that the proposed system achieves significant gains (around 1–2 dB) compared to the DF-SWIPT system. We further evaluate the impact of the distance and the power splitting (PS) strategy on the system performance using simulations. Finally, we build an optimization algorithm on the PS ratio by maximizing the admissible region from the theoretical perspective.

Bi-Objective Optimization of Information Rate and Harvested Power in RIS-Aided SWIPT Systems

The problem of simultaneously optimizing the information rate and the harvested power in a reconfigurable intelligent surface (RIS)-aided multiple-input single-output downlink multiuser wireless network with simultaneous wireless information and power transfer (SWIPT) is addressed. The beamforming vectors, RIS reflection coefficients, and power split ratios are jointly optimized subject to maximum power constraints, minimum harvested power constraints, and realistic constraints on the RIS reflection coefficients. A practical algorithm is developed through an interplay of alternating optimization, sequential optimization, and pricing-based methods. Numerical results show that the deployment of RISs jointly improves the information rate and the amount of harvested power.

Robust resource allocation algorithm in SWIPT-based D2D networks

To improve the operation lifetime of devices and the anti-interference capability of complex electromagnetic environments in device-to-device (D2D) networks, an energy-efficient maximization resource allocation algorithm was proposed for simultaneous wireless information and power transfer (SWIPT)-based D2D networks. Considering the constraints of users' minimum rate, minimum harvested energy, power splitting, and channel allocation, a robust energy-efficient resource allocation model was formulated by jointly optimizing the transmit power, subchannel coefficients, and the power splitting factor. The original NP-hard problem was converted into a deterministic and convex problem by using Dinkelbach's method and the worst-case approach, where the closed-form solutions were obtained by using the matching theory and Lagrange dual theory. Simulation results demonstrated that the proposed algorithm exhibited better robustness and higher energy efficiency.

Exploiting SWIPT-Enabled IoT-Based Cognitive Nonorthogonal Multiple Access With Coordinated Direct and Relay Transmission

This article proposes a simultaneous wireless information and power transfer (SWIPT)-enabled Internet of Things (IoT)-based cognitive nonorthogonal multiple access (NOMA) with coordinated direct and relay transmission (CDRT) system. It incorporates overlay cognitive radio (CR) and time switching (TS)-based SWIPT technology to enhance spectrum utilization and energy efficiency (EE). The proposed system comprises a primary network having a primary transmitter and its intended NOMA receivers (UE1 and UE2), accompanied by an energy-constrained secondary transmitter (ST) and its designated receiver (IoT-U). The primary transmitter communicates directly with its strong user UE1 and exploits the ST as an IoT relay to communicate with a weak user UE2. The IoT-relay node employs a TS-based receiver architecture and a decode-and-forward (DF) protocol to convey the weak user’s information along with its own information by following the NOMA principle. We evaluate the performance of the proposed system by considering both the perfect and imperfect successive interference cancellation (SIC) at the legitimate users over Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${m}$ </tex-math></inline-formula> fading in terms of outage probability (OP), system throughput, and EE. Moreover, we propose an iterative algorithm to minimize the OP by optimizing the TS factor. Furthermore, the impact of key parameters is also highlighted, which lays the guidelines for the practical design of energy-efficient and spectrum-efficient futuristic wireless communication networks.

Optimal power allocation for maximizing the energy efficiency of NOMA enabled full-duplex coordinated direct and relay transmission (CDRT) system with SWIPT

In this paper, we investigate the energy efficiency (EE) performance of non-orthogonal multiple access (NOMA) enabled full-duplex (FD) coordinated direct and relay transmission (CDRT) system (i.e., NOMA-FD-CDRT system). Firstly, we consider a two-user scenario, where the base station (BS) can directly communicate with the near user, while it requires the help of a dedicated FD relay node to communicate with the far user. In the second part, we consider that there are two near users and two far users in the system. To improve the EE, we consider integrating the simultaneous wireless information and power transfer (SWIPT) technique at the FD relay. We formulate an analytical expression for the overall EE of the SWIPT-assisted NOMA-FD-CDRT system. We determine optimal power allocation (OPA) for the downlink users at the BS that maximizes the EE. An iterative algorithm based on Dinkelbach method is proposed to determine the OPA vector. With the help of detailed numerical and simulation investigations, it is demonstrated that the proposed OPA can provide significant enhancement of EE of the considered SWIPT-assisted NOMA-FD-CDRT system.

Research on Multi-Terminal’s AC Offloading Scheme and Multi-Server’s AC Selection Scheme in IoT

Mobile Edge Computing (MEC) technology and Simultaneous Wireless Information and Power Transfer (SWIPT) technology are important ones to improve the computing rate and the sustainability of devices in the Internet of things (IoT). However, the system models of most relevant papers only considered multi-terminal, excluding multi-server. Therefore, this paper aims at the scenario of IoT with multi-terminal, multi-server and multi-relay, in which can optimize the computing rate and computing cost by using deep reinforcement learning (DRL) algorithm. Firstly, the formulas of computing rate and computing cost in proposed scenario are derived. Secondly, by introducing the modified Actor-Critic (AC) algorithm and convex optimization algorithm, we get the offloading scheme and time allocation that maximize the computing rate. Finally, the selection scheme of minimizing the computing cost is obtained by AC algorithm. The simulation results verify the theoretical analysis. The algorithm proposed in this paper not only achieves a near-optimal computing rate and computing cost while significantly reducing the program execution delay, but also makes full use of the energy collected by the SWIPT technology to improve energy utilization.

Unified Simultaneous Wireless Information and Power Transfer for IoT: Signaling and Architecture With Deep Learning Adaptive Control

In this article, we propose a unified simultaneous wireless information and power transfer (SWIPT) signaling and architecture to take advantage of both single tone and multitone signaling by adjusting only the power allocation ratio of a unified signal. Toward this, we design a unified and integrated receiver architecture for the proposed unified SWIPT signaling via an envelope detection with low power consumption. To lower the computational complexity of the receiver, we propose an adaptive control algorithm where the transmitter adjusts the communication mode through temporal convolutional network (TCN)-based <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">asymmetric processing</i> . To this end, the transmitter optimizes the modulation index and power allocation ratio in short-term scale while updating the mode switching threshold in long-term scale. We demonstrate that the proposed unified SWIPT system improves the achievable rate under the self-powering condition at low-power Internet of Things (IoT) devices. Consequently we will facilitate the effective deployment of low-power IoT networks that concurrently supply both information and energy <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">wirelessly</i> to the devices by using the proposed unified SWIPT and adaptive control algorithm at the transmitter side.

Outage analysis of two‐way relaying in SWIPT‐enabled CCRN with co‐channel interference

SummaryThis work investigates the dual impacts of co‐channel interference (CCI) on radio frequency (RF) energy harvesting (EH)‐enabled cooperative cognitive radio network (CCRN). CCRN is considered to be worked following overlay mode of spectrum sharing technique. One pair of cellular nodes are considered as primary users (PUs), and a pair of Internet‐of‐Things devices (IoDs) are considered as secondary users (SUs) of CCRN. IoDs are used to help the communication between cellular node and in benefit of that the devices can access the cellular spectrum. In one hand, the effect of CCI from different sources may deteriorate the received signal‐to‐noise ratio (SNR) at IoDs, and on the other hand, scavenge of energy at IoDs from RF signal of CCI may improve the transmission of information from IoDs. Hybrid power time switching (HPTS) technique is adopted in the proposed model for harvesting energy from RF signals at IoDs following simultaneous wireless information and power transfer (SWIPT) principle. The closed form expressions of both PU and SU outage are derived to analyse the performance of two different networks. The joint effects of both power splitting and time switching factors on both PU and SU outage are shown in simulation results. The outage performances of both PU and SU networks with respect to different interference‐to‐noise (INR) level and transmission power are also shown in the results. The performance of the proposed system is found as better than the previous work on similar network architecture.

Simultaneous wireless information and power transfer in resonant beam charging

SummaryFSO links have attracted a significant amount of interest in the recent years driven by the paramount importance of their license‐free spectrum and ease of deployment in wireless networks. Besides, the energy harvesting (EH) paradigm allows recharging terminals via ambient and/or external sources and prolongs battery lifetime operation. Thereby, facilitating free space optical (FSO) in EH networks creates potential scenarios for the future sixth‐generation (6G) communication systems. In this study, an EH system performing simultaneous wireless information and power transfer (SWIPT) while adopting FSO and resonant beam charging (RBC), RBC–SWIPT system is thoroughly analyzed. The performance of RBC‐SWIPT system is analyzed through Monte Carlo simulations, where average bit error ratio (ABER) and energy efficiency (EE) are studied and evaluated. In addition, channel capacity is derived along with the mutual information and studied over indoor line of sight (LOS) optical channel. Monte Carlo simulation results corroborate the accuracy of the derived formulas.

Superposition of rectangular power pulses and CP-OFDM signal for SWIPT

Simultaneous wireless information and power transfer (SWIPT) has recently attracted researchers and may help to satisfy future technology demands. SWIPT allows wireless power transfer (WPT) and wireless information transfer (WIT) to coexist based on shared resources. Recent studies have shown that, due to the nonlinearity of the rectifiers, high-PAPR (peak to average power ratio) waveforms provide better performance in terms of energy harvesting, making the design of power signals essential. In addition, these power signals should consume the smallest amount of resources for the WIT. In this paper, a new waveform design is proposed where the information and power signals are superposed using the same frequency and time resources. The power signal is composed of a high peak modulated rectangular wave sent during the cyclic prefix of the orthogonal frequency-division multiplexing (CP-OFDM) system, which is discarded at the information receiver, such that it does not interfere with the OFDM data symbol. Although the pulse is restricted to be within the cyclic prefix, there might be a small amount of interference caused by channel dispersion. Simulations and measurements show that a good choice of signal parameters can minimize interference on the information symbols and simultaneously provide good performance in terms of energy harvesting.

Simultaneous Wireless Information and Power Transfer Assisted Federated Learning via Nonorthogonal Multiple Access

Federated learning (FL) has been considered as a promising approach for enabling distributed learning without sacrificing edge-devices’ (EDs’) data privacy. However, training machine learning (ML) model distributively is challenging to the EDs with limited energy supply. In this work, we consider that the central parameter-server (which is co-located with the cellular base station, BS) exploits simultaneous wireless information and power transfer (SWIPT) to simultaneously send the aggregated model to all EDs and also transfer energy to them. With the collected energy from the BS, each ED firstly trains its local model, and then all EDs form a non-orthogonal multiple access (NOMA) cluster for sending their local models to the central parameter-server (i.e., the BS). To minimize the total energy consumption, we formulate a joint optimization of the BS’s SWIPT duration, each ED’s power-splitting ratio, the EDs’ NOMA uploading duration as well as the EDs’ and BS’s processing-rates. To address the non-convexity of the joint optimization problem, we decompose it into two subproblems, both of which are efficiently solved. We then propose an enhanced block coordinate descent (EBCD) algorithm, which iteratively solves the two subproblems in sequence and exploits the idea of simulated annealing to avoid being trapped by some local optimum, to approach to the optimal solution of the original joint optimization problem. By using our EBCD-Algorithm, we further investigate how to properly select the EDs to participate in the FL process, with the objective of minimizing all participants’ total energy consumption. A cross-entropy based algorithm, which exploits our EBCD-Algorithm as a subroutine, is proposed to determine the optimal ED-selection. Numerical results are provided to validate our proposed algorithms and demonstrate the performance advantage of the proposed SWIPT assisted FL via NOMA in comparison with some conventional FL schemes.

Reinforcement-Learning-Based Resource Allocation for Energy-Harvesting-Aided D2D Communications in IoT Networks

This article proposes a novel approach to improve the energy efficiency (EE) of an energy-harvesting (EH)-enabled IoT network supported by simultaneous wireless information and power transfer (SWIPT). More specifically, the device-to-device (D2D) users harvest ambient energy throughout their communication with the time switching (TS) technique, while the Internet of Things (IoT) users harvest energy from the base station (BS) based on the power splitting (PS) method. We study the EE optimization problem that takes into account transmit power feasibility conditions for D2D users and IoT users, the minimum data rate requirements for D2D and IoT users, joint spectrum sharing block, and time allocation for the D2D links. The underlying problem is a highly nonconvex mixed-integer nonlinear problem (MINLP) and the global optimal solution is intractable. To handle it, we decompose the original problem into three subproblems: 1) joint subchannel allocation and PS; 2) power control; and 3) time allocation. Since it is difficult to find an exact state model approach in a dynamic environment with a large state space, we exploit a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -learning method based on reinforcement learning (RL) to solve the first subproblem. To solve the second subproblem, we apply a conventional convex optimization technique based on the majorization–minimization (MM) approach and Dinkelbach method. Simulation results not only demonstrate the superiority of our proposed algorithm as compared to other methods in the literature but also confirm impressive EE gains through spectrum sharing and harvested energy from D2D and IoT users.

Outage Analysis in SWIPT Enabled Cooperative AF/DF Relay Assisted Two-Way Spectrum Sharing Communication

This paper reports a relative performance analysis of decode-and-forward (DF) and amplify-and-forward (AF) relaying in a multi-antenna cooperative cognitive radio network (CCRN) that supports device-to-device (D2D) communications using spectrum sharing technique in cellular network. The system model considers cellular system as primary users (PUs) while Internet of Things Devices (IoDs), involved in D2D communications, as secondary system. The devices access the licensed spectrum by means of the cooperation in two-way primary communications. Furthermore, IoDs are energized through energy harvesting (EH) of PU radio frequency (RF) signals, using simultaneous wireless information and power transfer (SWIPT) protocol. Closed form expressions of the outage probability for both cellular and D2D communications are derived and the impact of various design parameters for both AF and DF relaying techniques are studied. Based on the simulation results, it is found that the proposed spectrum sharing protocol outperforms by 209% and 49% for DF relaying and AF relaying schemes, respectively. It is also observed that DF relaying performs better in term of peak energy efficiency (EE) at low transmit power while AF relaying at high transmit power.

Physical-layer security with frequency diverse array for DF multi-antenna relaying SWIPT system

ABSTRACT In this letter, we establish physical-layer security based on frequency diverse array (FDA) together with directional modulation (DM) for decode and forward (DF) relaying simultaneous wireless information and power transfer (SWIPT) system. The analytical expressions of the ergodic system secrecy capacity under the time switching (TS) protocol are derived. Moreover, the impacts of system parameters on secure performance are analysed. Numerical results reveal that the proposed method achieves better security performance than conventional PA solutions, especially in the range dimension.

High-Efficiency Power Optimization Based on Reconfigurable Intelligent Surface for Nonlinear SWIPT System

This paper presents an investigation of the transmitting power consumption of a base station (BS) in a simultaneous wireless information and power transfer (SWIPT) system enhanced by a reconfigurable intelligent surface (RIS). The aim is to optimize the total transmitting power consumption when sending information signals and energy from the BS to ground sensors. To this end, the transmitting power consumption of the BS is optimized by satisfying the sensor’s minimum signal-to-interference-plus-noise ratio (SINR), the phase shift constraints of the RIS, and each sensor’s power-splitting (PS) ratio. In order to decouple the optimization variables, we use the technique of block coordinate descent (BCD) to transform the total problem into subproblems. In the second subproblem, the unit modulus constraints are approximated using the successive convex approximation (SCA) method, allowing the optimal solutions to be obtained by solving subproblems in an iterative manner. Our numerical simulation results show that transmitting power consumption can be significantly decreased by adding RIS to an SPWIT system, even in nonlinear harvest models of real application scenarios.

Secure transmission of simultaneous wireless information and power transfer system for Internet of things

Abstract Due to the excellent broadcasting characteristics of radio signals, simultaneous wireless information and power transfer (SWIPT) can transmit both information and energy, and provide users with stable power supply. Wireless channel has the characteristics of openness, which will lead to the leakage of information in the SWIPT system. It is one of the research hotspots in the industry to ensure the secure transmission of information in SWIPT system where there are differences in the transmission of energy and information. This paper proposes an ‘information-energy’ dynamic switching opportunistic secure transmission scheme. First, a model considering three factors of multi-cell, multi-user and multiple eavesdropper is established which assumes that the user adopts a time-domain switching receiver that collects energy in a nonlinear model. Then, combined with the time-varying wireless channel, a dynamic information energy switching transmission scheme based on signal-to-interference noise ratio threshold is proposed. Finally, the energy and information transmission performance of the scheme are comprehensively analysed.

Wireless powered cognitive radio networks with multiple antenna sources and hardware impairments

In this paper, a radio-frequency (RF) energy harvesting enabled cognitive radio network (CRN) is considered in the presence of transceiver hardware impairments (HIs). Herein, one of the secondary nodes (SNs) exploits simultaneous wireless information and power transfer (SWIPT) technology to harvest energy from the primary signal and provides relay assistance for the primary transmission. We consider multiple antennas at the primary nodes (PNs) to ensure better link reliability and spectrum sharing to mitigate the spectrum scarcity. In the first phase, relaying SN uses non-linear energy harvester circuit to harvest energy from the RF signals received from PN using the power splitting approach. In the second phase, the same SN adds its own signal intended for the other SN along with the primary signal and broadcasts the combined signal. Assuming the network to operate in a Nakagami-m fading environment, the performance of the considered CRN is evaluated in terms of outage probability and system throughput. Also, we formulate two optimization problems to minimize the OP and maximize the system throughput. The Karush–Kuhn–Tucker conditions are used to obtain the closed-form solution of the constrained convex optimization. Numerical results are provided to examine the performance impact concerning different system and channel parameters.

Energy-Efficient beyond 5G Multiple Access Technique with Simultaneous Wireless Information and Power Transfer for the Factory of the Future

In the Industrial Internet of Things (IIoT), non-orthogonal multiple access (NOMA) has emerged as a viable multiple access method due to its superior efficiency. In this paper, a new power allocation technique for NOMA-enabled IIoT devices is presented with trade-offs between increasing energy efficiency and decreasing power consumption. We present a joint optimization of transmission rate and energy harvesting in simultaneous wireless information and power transfer (SWIPT) NOMA-enabled IIoT devices. With the power splitting (PS) approach, we examine how to improve overall transmission rate and harvested energy, simultaneously, while fulfilling the minimum rate and harvested energy needs of each IIoT device in a SWIPT-enabled NOMA system. An objective function is established by adding transmission rates obtained from information decoding and the transformed throughput from energy harvesting. The combination of management approaches with Industry 4.0 technology provides a viable strategy to decrease industrial production’s energy use. Several performance metrics may be utilized to study manufacturing process optimization. The efficiency of production equipment may be measured by looking at the overall effectiveness (OE) of the equipment in use. We divide the non-convex optimization problem into two sub-problems, based on the Lagrangian duality method, and solve them to find the optimal solution for the non-convex problem. The approach is validated based on physical layer parameter settings that represent potential factory of the future scenarios. Simulation results confirm the effectiveness of the presented method in a SWIPT-enabled NOMA system, provide considerable performance gains over the classic rate maximization strategy, and demonstrate the energy efficiency of the presented method compared with the conventional system. The results show huge potential of our solutions to reduce the future huge energy demand related to factory automation.