Simultaneous Wireless Information Research Articles

A Simultaneous Wireless Information and Power Transfer-Based Multi-Hop Uneven Clustering Routing Protocol for EH-Cognitive Radio Sensor Networks

Clustering protocols and simultaneous wireless information and power transfer (SWIPT) technology can solve the issue of imbalanced energy consumption among nodes in energy harvesting-cognitive radio sensor networks (EH-CRSNs). However, dynamic energy changes caused by EH/SWIPT and dynamic spectrum availability prevent existing clustering routing protocols from fully leveraging the advantages of EH and SWIPT. Therefore, a multi-hop uneven clustering routing protocol is proposed for EH-CRSNs utilizing SWIPT technology in this paper. Specifically, an EH-based energy state function is proposed to accurately track the dynamic energy variations in nodes. Utilizing this function, dynamic spectrum availability, neighbor count, and other information are integrated to design the criteria for selecting high-quality cluster heads (CHs) and relays, thereby facilitating effective data transfer to the sink. Intra-cluster and inter-cluster SWIPT mechanisms are incorporated to allow for the immediate energy replenishment for CHs or relays with insufficient energy while transmitting data, thereby preventing data transmission failures due to energy depletion. An energy status control mechanism is introduced to avoid the energy waste caused by excessive activation of the SWIPT mechanism. Simulation results indicate that the proposed protocol markedly improves the balance of energy consumption among nodes and enhances network surveillance capabilities when compared to existing clustering routing protocols.

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.

Energy-efficient trajectory design for secure SWIPT systems assisted by UAV-IRS

Due to its controllable maneuverability, wide coverage, and low cost, unmanned aerial vehicle (UAV) has great potential in post-disaster rescue, cargo transport and emergency communication. Considering its limited onboard energy, energy-efficient UAV communication is a challenge. This research examines the security of simultaneous wireless information and power transfer (SWIPT) systems assisted by intelligent reflecting surfaces (IRS) and UAVs while considering the flight energy of rotary-wing UAVs. Specifically, an IRS is mounted on a UAV to enhance the quality of legitimate transmission, and artificial noise (AN) is introduced into the base station (BS) to reduce eavesdropping quality. The power splitting (PS) technology is adopted at ground devices (GDs) to simultaneously decode information and harvest energy. First, we jointly design the BS transmit beamforming, UAV-IRS phase shifts and trajectory/velocity as well as GDs PS ratio with the aim of maximizing the sum secrecy rate of all GDs. Then, an iterative algorithm is developed to address the formulated problem. In particular, additional variables are introduced to handle this complicated objective function, and the original problem is decoupled into multiple sub-problems, which can be solved alternately by invoking the successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques. Finally, numerical results demonstrate that the proposed scheme exhibits a substantial performance in the security rate of SWIPT systems assisted by UAV-IRS, and its performance is improved by at least 12% compared to benchmark schemes at the flight energy budget ethr=5KJ and the number of reflecting elements Nr=25.

Simultaneous Wireless Information and Power Transfer in IoT-based Scenarios: Architectures, Challenges, and Prototype Validation

Simultaneous Wireless Information and Power Transfer in IoT-based Scenarios: Architectures, Challenges, and Prototype Validation

An Isolated Gate Driver Enabled by Simultaneous Wireless Information and Power Transfer

An Isolated Gate Driver Enabled by Simultaneous Wireless Information and Power Transfer

Research and Design of an Optimal Management Strategy for Simultaneous Wireless Power and Information Transmission for Highway Vehicles

Research and Design of an Optimal Management Strategy for Simultaneous Wireless Power and Information Transmission for Highway Vehicles

A Robust Simultaneous Wireless Power and Information Transfer System for Charging Battery with Wide Charging Region

A Robust Simultaneous Wireless Power and Information Transfer System for Charging Battery with Wide Charging Region

WiLO-OFDM Transmission Scheme for Simultaneous Wireless Information and Power Transfer

WiLO-OFDM Transmission Scheme for Simultaneous Wireless Information and Power Transfer

Intelligent Reflecting Surface Aided Simultaneous Wireless Information and Energy Transfer to IoT Users Under Spatial Correlation

Intelligent Reflecting Surface Aided Simultaneous Wireless Information and Energy Transfer to IoT Users Under Spatial Correlation

Biased-FSK Modulation for Simultaneous Wireless Information and Power Transfer

Biased-FSK Modulation for Simultaneous Wireless Information and Power Transfer

Semantic Communications for Simultaneous Wireless Information and Power Transfer

Semantic Communications for Simultaneous Wireless Information and Power Transfer

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.

Multi-Objective Optimization for IRS-Aidded Multi-user MIMO SWIPT Systems

In this paper, we investigate an intelligent reflecting surface (IRS) assisted simultaneous wireless information and power transfer (SWIPT) system in which users equipped with multiple antennas exploit power-splitting (PS) strategies for simultaneously information decoding (ID) and energy harvesting (EH). Different from the majority of previous studies which focused on single objective optimization problems (SOOPs) and assumed the linearity of EH models, in this paper, we aim at studying the multi-objective optimization problem (MOOP) of the sum rate (SR) and the totalharvested energy (HE) subject to the maximum transmit power (TP) constraint, the user quality of service (QoS), and HE requirements at each user with taking a practical non-linear EH (NLEH) model into consideration. To investigate insightful tradeoffs between the achievable SR and total HE, we adopt the modified weighted Tchebycheff method to transform the MOOP into a SOOP. However, solving the SOOPs and modified SOOP is mathematically difficult due to the non-convexity of the object functions and the constraints of the coupled variables of the base station (BS) transmit precoding matrices (TPMs), the user PS ratios (PSRs), and the IRS phase shift matrix (PSM). To address these challenges, an alternating optimization (AO) framework is used to decompose the formulated design problem into sub-problems. In addition, we apply the majorization-minimization (MM) approach to transform the sub-problems into convex optimization ones. Finally, numerical simulation results are conducted to verify the tradeoffs between the SR and the total amount of HE. The numerical results also indicate that the considered system using the IRS with optimal phase shifts provides considerable performance improvement in terms of the achievable SR and HE as compared to the counterparts without using the IRS or with the IRS of fixed phase shifts.

A Survey on Challenges of Millimeter Wave Communications for Fifth-Generation Wireless Networks

Abstract-Cellular networks rely heavily on downlink beamforming; however, calculating beamformers that maximize the weighted sum rate (WSR) under power constraints is an NP-hard problem. A weighted minimum mean square error (WMMSE) algorithm variant is suggested for a MU-MISO downlink channel in order to address this trade-off between complexity and performance. This variation avoids bisection searches, eigendata compositions, and matrix inversions—all of which are challenging to implement as conventional network layers. With a reduced complexity, the suggested network architecture outperforms the WMMSE algorithm truncated to the same number of iterations and adapts well to variations in the channel distribution. Many use cases for vehicles that demand high capacity, extremely low latency, and high reliability can be made possible by 5G. To facilitate this, 5G For a MU-MISO downlink channel, a variation of the weighted minimum mean square error (WMMSE) algorithm is proposed to address this trade-off between complexity and performance. This variation avoids complex network layer implementations such as matrix inversions, eigendata compositions, and bisection searches. The suggested network architecture generalizes well to changes in the channel distribution and performs comparably to the WMMSE algorithm truncated to the same number of iterations, but at a lower complexity. Numerous automotive use cases requiring high capacity, extremely low latency, and high reliability can be made possible by 5G. 5G suggests using highly directed mm Wave system deployment and dense small cell technology to support this. To reduce the cost of signaling, however, enabling vehicular communication necessitates strong mobility management strategies. KEYWORD: Millimetre wave communications, propagation, channel measurements, channel models, MIMO, hybrid precoding, non-orthogonal multiple access (NOMA), multiple access techniques, simultaneous wireless information and power transfer (SWIPT), RF energy harvesting.

AoI‐driven SWIPT‐enabled UAV trajectory optimization for two‐way relaying

AbstractMotivated by the timely need for fresh updates in time‐critical applications, this paper investigates the AoI‐driven UAV trajectory optimization for a two‐way relay network. The non‐linear simultaneous wireless information and power transfer (SWIPT) power‐splitting (PS) technique is used to provide the energy required for UAV communication considering hardware impairments. Amalgamating derived outage probability, AoI expression is obtained to evaluate data timeliness and its performance trade‐offs. Then, we optimize the trajectory of the UAV while minimizing the AoI performance within the given discretized time slot. The impact of the system parameters, that is, size of the status update, PS factor, outage probability, and UAV's position, on the AoI performance are extensively investigated.

A DDPG-based energy efficient federated learning algorithm with SWIPT and MC-NOMA

Federated learning (FL) has emerged as a promising distributed machine learning technique. It has the potential to play a key role in future Internet of Things (IoT) networks by ensuring the security and privacy of user data combined with efficient utilization of communication resources. This paper addresses the challenge of maximizing energy efficiency in FL systems. We employed simultaneous wireless information and power transfer (SWIPT) and multi-carrier non-orthogonal multiple access (MC-NOMA) techniques. Also, we jointly optimized power allocation and central processing unit (CPU) resource allocation to minimize latency-constrained energy consumption. We formulated an optimization problem using a Markov decision process (MDP) and utilized a deep deterministic policy gradient (DDPG) reinforcement learning algorithm to solve our MDP problem. We tested the proposed algorithm through extensive simulations and confirmed it converges in a stable manner and provides enhanced energy efficiency compared to conventional schemes.

Multi-objective optimization for energy efficient cooperative communication in energy-constrained overlay Cognitive Radio Networks

With the rapid proliferation of wireless devices, energy efficiency and addressing spectrum scarcity have become critical global concerns. To address these challenges, this paper explores radio-frequency energy harvesting in Cognitive Radio Networks (CRNs) as a solution which can significantly extend the battery life of mobile devices. In this setup, energy-constrained secondary users (SUs) use Simultaneous Wireless Information and Power Transfer (SWIPT) technology to harvest energy from primary signals and aid primary transmission. We propose a joint time-switching and power-splitting technique to maximize energy harvesting, achieving a 97.7% accurate sub-optimal solution compared to the optimal (benchmark) result. Furthermore, we investigate optimal power allocation during cooperative communication and secondary transmission, resulting in a near-optimal solution with 98.5% accuracy. We also introduce a cooperative communication framework using the Hedonic game concept, enabling SUs to establish preferred partnerships with suitable primary users (PUs). Numerical results indicate that this cooperative framework enhances the secondary network’s overall utility, average SU satisfaction, and SU participation when compared to the non-cooperative approach.

A New Simultaneous Wireless Power and Information Transfer System With Integrated Signal Magnetic Coupler

For a reliable and controllable wireless power transfer (WPT) system, the simultaneous wireless power and information transfer (SWPIT) technology has recently attracted special consideration to achieve real-time information exchange between the transmitter and receiver. In this article, a novel SWPIT system with an integrated signal magnetic coupler is proposed for wireless charging applications. The signal detection coil integrated with the receiver coil is designed to utilize the existing ferrite cores of the magnetic coupler, reducing the overall cost and obtaining a more compact design. Meanwhile, the deviation frequency enlargement effect (DFEE) principle and the frequency shift keying (FSK) technology are used to realize SWPIT in a wireless charger. The equivalent circuit of the proposed system is modeled and analyzed considering the cross-couplings between the integrated signal coil and the main coils. The finite element analysis (FEA) is presented through Ansys Maxwell software to select the optimal ferrite core structure and eliminate these unwanted cross-couplings. Finally, a 70- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$W$</tex-math></inline-formula> power experimental prototype is established, and comprehensive experimental results are given to verify the feasibility and effectiveness of the proposed SWPIT system. Furthermore, the experimental results demonstrate that the measured output power fluctuation is below 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> during information transmission, the transmission rate is up to 9.6 kbps, and the system efficiency can be maintained at 88.76 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

Optimum Performance Analysis and Receiver Design for OFDM-Based Frequency-Splitting SWIPT With Strong Nonlinear Effects

Multicarrier based frequency splitting simultaneous wireless information and power transmission (FS-SWIPT) signals are very prone to nonlinear effects due to the combination of high-power energy harvesting (EH) subcarriers with low-power data subcarriers. In this paper, we study the impact of nonlinear effects in FS-SWIPT signals, as well as ways to minimize these effects on the data transmission performance. We start by analytically characterizing the impact of nonlinear devices on the signals, showing that the nonlinear effects on data subcarriers are exacerbated by a factor close to the ratio between the power spectral densities of EH and data terms. This suggests that conventional receivers, that treat nonlinear distortion as an additional noise term, can have very poor performance. Then, we present an iterative receiver that iteratively estimates and cancels nonlinear distortion, and is able to have a performance close to the linear case. Finally, we study the optimum performance of FS-SWIPT signals with strong nonlinear distortion levels, showing that, by using optimum receivers, the nonlinear distortion term can be used to improve the performance of FS-SWIPT, even outperforming the linear case.

Practical Waveform-to-Energy Harvesting Model and Transmit Waveform Optimization for RF Wireless Power Transfer Systems

The received radio-frequency (RF) power in far-field RF wireless power transfer (WPT)—with or without simultaneous information transfer—is minuscule due to large propagation loss in wireless media. In such scenarios, adapting to the receiver characteristics by transmit waveform optimization is essential for maximizing the harvested direct current (dc) and, thus, the end-to-end efficiency of an RF WPT system. The receiver efficiency in RF WPT is governed by the RF-to-dc efficiency of the rectifier as well as the impedance mismatch at the antenna and load. In this article, we study the receiver efficiency for any fixed load and, subsequently, present a novel rectifier model that relates the average harvested dc power to the distribution, that is, the histogram, of the instantaneous power levels of the RF signal’s envelope over time. The proposed waveform-to-energy harvesting (EH) model enables us to anticipate the average harvested dc power for any waveform, including communication signals as well, given the knowledge of the power-level distribution. Consequently, we conduct rigorous waveform optimization to maximize the average harvested dc power and determine the digital baseband signal at the transmitter that does so, namely prove that a pulsed tone at appropriate frequency is optimal for RF WPT. We present a multiband test-bed for determining the receiver efficiency for any digital baseband waveform. The efficacy of the proposed model is corroborated through experiments as well as simulations, which confirm that it is operational as well as accurate in practice and that single-sine pulses yield higher efficiency than basic multisine waveforms, while a pulsed phase shift keying (PSK) is preferable for simultaneous wireless information and power transfer (SWIPT).