Simultaneous Wireless Information Research Articles

SWIPT-Enabled Multiple Access Channel: Effects of Decoding Cost and Non-Linear EH Model

We studied power splitting-based simultaneous wireless information and power transfer (PS-SWIPT) in multiple access channels (MACs), considering the decoding cost and non-linear energy harvesting (EH) constraints at the receiving nodes to study practical limitations of an EH communication system. Under these restrictions, we formulated and analyzed the achievable rate and maximum departure regions in two well-studied scenarios, i.e., a classical PS-SWIPT MAC and a PS-SWIPT MAC with user cooperation. In the classical PS-SWIPT MAC setting, closed-form expressions for the optimal values of the PS factors are derived for two fundamental decoding schemes: simultaneous decoding and successive interference cancellation. In the PS-SWIPT MAC with user cooperation, the joint optimal power allocation for users as well as the optimal PS factor are derived. This reveals that one decoding scheme outperforms the other in the classical PS-SWIPT MAC, depending on the function type of the decoding cost. Finally, it is shown that the cooperation between users can potentially boost the performance of a PS-SWIPT MAC under decoding cost and non-linear EH constraints. Moreover, effects of the decoding cost functions, non-linear EH model and channel quality between the users are studied, and performance characteristics of the system are discussed.

A Pricing-Based Approach for Energy-Efficiency Maximization in RIS-Aided Multi-User MIMO SWIPT-Enabled Wireless Networks

In this work, we investigate the performance of a reconfigurable intelligent surface (RIS)-aided multi-user simultaneous wireless information and power transfer (SWIPT) network, where a multiple-input multiple-output (MIMO) base station (BS) serves multiple MIMO information receivers (IRs) while ensuring a minimum harvested power at multiple MIMO energy receivers (ERs). In order to improve the energy efficiency (EE) of the network, we consider a pricing-based performance metric called network utility. We then establish an optimization framework to jointly optimize the transmit precoding matrix (TPM) and phase shift matrix (PSM) to maximize the network utility function with constraints on the available transmit power at BS, minimum harvested power required at each ER, and unit modulus phase shift condition at RIS. Due to the non-convex nature of this problem, we divide it into two sub-problems where a sub-optimal solution of TPM and PSM are obtained separately using successive convex approximation and bisection search-based algorithms. Further, we propose an EE maximization (EEM) algorithm based on the block coordinate descent method to achieve the optimal solution of the master problem by iteratively obtaining the sub-optimal TPM, PSM, and network price using their respective algorithms. Moreover, we also prove that the solution obtained for each problem using their respective algorithm converges to the Karush-Kuhn-Tucker (KKT) optimum point of that problem. We also show the efficacy of the proposed algorithm using simulation results. In particular, we highlight the importance of using RIS in a multi-user MIMO SWIPT network and demonstrate the effect of various parameters on the network’s EE performance.

Rate-Energy Tradeoff Analysis in RIS-SWIPT Systems With Hardware Impairments and Phase-Based Amplitude Response

This paper investigates the reconfigurable intelligent surface (RIS)-empowered dynamic power splitting designs for simultaneous wireless information and power transfer (SWIPT) systems while adopting various practical hardware issues. Specifically, we adopt the physical size of the RIS and the placement of the RIS plane to phase-align the reflected signals towards the desired direction. The analytical phase shift model for the reflecting elements is presented to characterize an intertwined relationship between amplitude and phase responses, which captures the amplitude variations depending on phase in RIS elements. Furthermore, an additive distortion noise incorporates the residual transceiver hardware impairments (RTHIs). The stringent signal-to-interference-plus-noise ratio requirement is facilitated using both the direct and indirect, i.e., RIS cascaded, links. To made complicated analysis become tractable, we exploit the statistical properties of the effective channel power which follows a Gamma distribution. The tight bounds for the achievable rates and residual energy are derived and the tradeoffs between the achievable rate and residual energy for the time switching and static power splitting designs are characterized. Finally, the numerical results confirm the accuracy of the developed framework and demonstrate the selection of the system parameters.

Autonomous Wireless Sensors Network for the Implementation of a Cyber-Physical System Monitoring Reinforced Concrete Civil Engineering Structures

This paper presents an autonomous Wireless Sensors Network as the hardware basis for implementing a Cyber-Physical System. The Wireless Sensors Network is composed of Sensing Nodes and Communicating Nodes. The Sensing Nodes can wirelessly transmit data measured in reinforced concrete using Non-Destructive Testing methods over several tens of meters. These are battery-free, and are powered and controlled wirelessly and remotely by a radiative electromagnetic Wireless Power Transfer system tuned by the Communicating Nodes. Each Communicating Node covers a volume of at least 11 meters in all directions for the Wireless Power Transfer. The Wireless Sensors Network meets the requirements of the Simultaneous Wireless Information and Power Transmission paradigm by using a single antenna in the Sensing Nodes (concurrently for power harvesting and data transmission). The proposed system is designed for the Structural Health Monitoring of reinforced concrete civil engineering structures, but can be adapted to other applications, especially in harsh environments.

Optimization of Different Deployments and Resolution of Antenna Arrays in SWIPT

In this paper, three different deployment antenna arrays with circular, triangular and rectangular shapes were used to optimize the simultaneous wireless information and power transfer (SWIPT) system for the Internet of Things (IoT). Ray-tracing was employed to channel the model for a real environment. Self-adaptive dynamic differential evolution (SADDE) was used to optimize the harvesting power ratio with bit error rate constrained by the two different resolutions of feed length (high resolution and low resolution). Numerical results show that those three antenna arrays can achieve the goal for information quality in both resolutions. The harvesting power ratio for the circular array is the best and the harvesting power ratio for the rectangular array is the worst. The harvesting power ratio for the low-resolution case is 25% lower than the high-resolution case. However, the circular antenna array is the best deployment in those three different arrays for both high and low resolutions.

Reconfigurable intelligent surface aided coordinated multipoint transmission for the simultaneous wireless information and power transfer non‐orthogonal multiple access network

AbstractWe consider a reconfigurable intelligent surface (RIS) aided coordinated multipoint (CoMP) transmission to enhance the achievable rates of the cell edge users (CEUs) in a downlink non‐orthogonal multiple access (NOMA) network enabled with simultaneous wireless information and power transfer (SWIPT). The RIS‐enabled SWIPT‐CoMP‐NOMA network improves the spectral efficiency and counterbalances the rate trade‐off introduced by SWIPT. The distribution model of the effective channel gain plays a vital role in ergodic capacity and outage probability analysis. In this article, we approximate the effective channel gains of the CEUs using the inverse Gaussian (IG) function and validate its accuracy using the well‐known Kolmogorov–Smirnov distance (KSD) test. Using the proposed channel gain model, we derive closed‐form expressions for the ergodic rates and outage probabilities of the CEUs. Using Monte‐Carlo simulations, we confirm the accuracy of the derived analytical expressions and show that the proposed IG function is more accurate than the Gamma function in estimating the outage probability. We also found that the proposed system always offers a higher ergodic rate than the SWIPT‐CoMP‐NOMA system.

SWIPT-Based Nonorthogonal Multiple Access under Arbitrary Nakagami-m Fading with Direct Links

This paper studies the joint impact of simultaneous wireless information and power transfer (SWIPT) and nonorthogonal multiple access (NOMA) to the cooperative relay (CoR) network where direct links exist. Over Nakagami-m fading environments, the near users employ decode-and-forward (DF) and energy harvesting (EH) to assist the transmission from the source to the far users. Exploiting the time-switching protocol (TSP) and power-splitting protocol (PSP) to the CoR-based NOMA system, analytical results for the outage probability are derived, and the corresponding throughput is obtained. Comparative results show that the PSP outperforms the TSP at low transmit power, while at high-transmit-power regime, the TSP provides similar performance as the PSP.

Joint User Selection and Transceiver Design for Cell-Free With Network-Assisted Full Duplexing

In this paper, we investigate the problem of sum rate maximization by guaranteeing the quality of service (QoS) of both uplink and downlink in cell-free with network-assisted full Duplexing (NAFD), where the users operate in half-duplex mode and access points (APs) operate in either full-duplex mode or half-duplex mode. In the considered network, the central processor unit (CPU) sends the compressed beamformed signals to the transmit-APs (T-APs) over the downlink fronthaul, and the T-APs forward the signals to downlink users. At the same time, the receive-APs (R-APs) compress the signals transmitted by uplink users and forward them to the CPU via uplink fronthaul. We aim to maximize the spectral efficiency and the number of users that should be admitted by the network, where users’ requirements of both downlink and uplink signal-to-interference-plus-noise (SINR) constraints, fronthaul capacity constraints, energy harvesting constraints and simultaneous wireless information and power transfer (SWIPT) ratio design are considered. A successive convex approximation-based algorithm is proposed to solve the highly coupled problem, which is guaranteed to converge to the Karush-Kuhn-Tucker (KKT) conditions. We conduct a comprehensive comparison between the NAFD scheme and the traditional co-frequency co-time full duplex (CCFD) scheme and time division duplex (TDD) scheme and offer some valuable opinions about the system design.

Hybrid Energy Resource Allocation for Simultaneous Wireless Information and Power Transfer for Green Communications

In this paper, we consider a simultaneous wireless information and hybrid power transfer system for cellular green networks. The small cells (SCs) use hybrid power of on-grid power and green energy harvested from environments, whilst the user equipments (UEs) are enabled by a power-splitting receiver. A quality-of-service (QoS) constrained problem is designed to maximize energy efficiency (EE) considering joint strategies of hybrid power allocation, resource block assignment, and power splitting ratio adjustment. We propose a joint wireless charging and hybrid power based resource allocation (J-WHA) algorithm by transforming the non-concave EE problem into a solvable one based on proved concavity property and Karush-Kuhn-Tucker (KKT) conditions. Moreover, a separated wireless charging and hybrid power based resource allocation (S-WHA) algorithm is proposed to obtain sub-optimal solutions with lower computational complexity. Simulation results demonstrate the convergence of both proposed algorithms in relation to transmission power utilization, wireless charging amount, and system EE. It is shown that the proposed J-WHA and S-WHA algorithms outperform existing schemes in terms of EE performance.

Smart and Reconfigurable Wireless Communications: From IRS Modeling to Algorithm Design

Intelligent reflecting surfaces (IRSs) have been introduced into wireless communications systems due to their great potential to smartly customize and reconfigure radio propagation environments in a cost-effective manner. Despite the promising advantages of IRSs, academic research on IRSs is still in its infancy. In particular, the design and analysis of IRS-assisted wireless communication systems critically depend on accurate and tractable modeling of the IRS. In this article, we first present and compare three IRS models, namely the conventional independent diffusive scatterer-based model, physics-based model, and impedance network-based model, in terms of their accuracy, tractability, and implementation simplicity. Furthermore, a new framework based on partitioning the IRS into tiles and employing codebooks of transmission modes is introduced to enable scalable IRS optimization. Then we investigate the impact of the three considered IRS models on system design, where several crucial technical challenges for the efficient design of IRS-assisted wireless systems are identified and the corresponding solutions are unraveled. Furthermore, to illustrate the properties of the considered models and the efficiency of the proposed solution concepts, IRS-assisted secure wireless systems and simultaneous wireless information and power transfer systems are studied in more detail. Finally, several promising future research directions for IRS-assisted wireless systems are highlighted.

Robust Active and Passive Beamformer Design for IRS-Aided Downlink MISO PS-SWIPT With a Nonlinear Energy Harvesting Model

This paper optimizes the energy consumption of the downlink of a multiple-antenna base station (BS) transmitting to several single-antenna users. The BS utilizes simultaneous wireless information and power transfer (SWIPT) while receivers apply power-splitting (PS) with a nonlinear energy harvesting model leading to PS-SWIPT. We use an intelligent reflecting surface (IRS) and propose a joint design to optimize the active data and the BS’s energy beamformers, IRS’s passive beamformers, and the receivers’ PS ratios under perfect and imperfect CSI availability. In particular, the total BS transmit power is minimized while guaranteeing a minimum rate and harvested energy for each receiver. We apply the block coordinate descent (BCD) method to optimize active and passive beamformers iteratively. We enforce the rank-one constraint and solve the corresponding optimization problem via successive convex approximation (SCA) for accurate semidefinite relaxations. Furthermore, we propose a worst-case robust design for the imperfect CSI case and reformulate this problem with infinitely many constraints. With the BCD method, the problem is iteratively solved via semidefinite programming (SDP) and a second sub-problem with a linear objective and quadratic matrix inequalities, which is also solved via SCA. Numerical results show significant improvements (e.g., 30% decrease in transmit power) than those of no-IRS and IRS with random phase shifts.

High-Power Simultaneous Wireless Information and Power Transfer System Based on an Injection-Locked Magnetron Phased Array

We built a phased array system for high-power simultaneous wireless information and power transfer (SWIPT) using four 5.8-GHz injection-locked magnetrons. In the magnetron injection-locked state, the transmission efficiency was measured at different modulation rates. The fluctuation in the transmission efficiency was not more than 0.5%. We observed that dynamic beamforming does not affect communication quality. Using the magnetron phased array system, SWIPT experiments revealed that a frequency modulated (FM) signal that carries a video camera signal is transmitted and decoded during dynamic beamforming. In this SWIPT system, the main lobe transfers power, and information can be demodulated in front of the magnetron phased array from −90° to 90°. The maximum transmitted microwave power of the proposed system is 1637 W.

Evolution of SWIPT for the IoT World: Near- and Far-Field Solutions for Simultaneous Wireless Information and Power Transfer

In the past few years, many interesting approaches have been studied and designed to advance the practical implementation of wireless information and power transfer (WIPT) <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> and simultaneous WIPT (SWIPT) <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> in the contexts of everyday life, academic research, and industry. The ever-growing array of Internet of Things (IoT) technologies presents a tangible answer to the need for modern, densely populated networks of wirelessly connected devices. In this context, node maintenance is a challenging task, given both the enormous size of the networks and the location of the devices, which can be spread across difficult-to-reach areas. In particular, the SWIPT paradigm <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> is being investigated in a wide range of systems for industrial applications combined with emerging technologies typical of the industrial IoT, namely wireless sensor networks (WSNs) that enable unlimited and uninterrupted connectivity in generic commercial environments. The main goal is to continuously monitor key components by using smart sensors that are able to track, in almost real time, rotation, position, speed, temperature, acceleration, and all the other vital parameters of the devices that have to be observed <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref> .

Energy Efficiency Maximization with Optimal Beamforming in Secure MISO CRNs with SWIPT

In this paper, the optimal beamforming problem of multi-input single-output (MISO) cognitive radio (CR) downlink networks with simultaneous wireless information and power transfer is studied. Due to the nonconvexity of the objective function, the considered nonconvex optimization problem is firstly transformed to an equivalent subtraction problem and then an approximated convex optimization problem is obtained by using the successive convex approximation (SCA). When the instantaneous channel state information (CSI) of the eavesdropping link is unknown to the legitimate transmitter, another interruption-constrained energy efficiency optimization problem is proposed and the Bernstein-type inequality (BTI) is used to conservatively approximate the probability constraint. The paper proposes a two-level iterative algorithm based on Dinkelbach to find the optimal solution of the EE maximization problem. Numerical results validate the effectiveness and convergence of the proposed algorithm.

Energy-Efficient Optimal Power Allocation for SWIPT Based IoT-Enabled Smart Meter.

This paper presents an internet of things (IoTs) enabled smart meter with energy-efficient simultaneous wireless information and power transfer (SWIPT) for the wireless powered smart grid communication network. The SWIPT technique with energy harvesting (EH) is an attractive solution for prolonging the battery life of ultra-low power devices. The motivation for energy efficiency (EE) maximization is to increase the efficient use of energy and improve the battery life of the IoT devices embedded in smart meter. In the system model, the smart meter is equipped with an IoT device, which implements the SWIPT technique in power splitting (PS) mode. This paper aims at the EE maximization and considers the orthogonal frequency division multiplexing distributed antenna system (OFDM-DAS) for the smart meters in the downlink with IoT enabled PS-SWIPT system. The EE maximization is a nonlinear and non-convex optimization problem. We propose an optimal power allocation algorithm for the non-convex EE maximization problem by the Lagrange method and proportional fairness to optimal power allocation among smart meters. The proposed algorithm shows a clear advantage, where total power consumption is considered in the EE maximization with energy constraints. Furthermore, EE vs. spectral efficiency (SE) tradeoff is investigated. The results of our algorithm reveal that EE improves with EH requirements.

An automatic polarization switching antenna structure for batteryless IoT devices

Microwave power transmission (MPT) has many advantages. However, previous studies have indicated that MPT interferes with wireless data communication. In this paper, an adaptive polarization switchable rectenna architecture is proposed for simultaneous wireless information and power transfer. When the rectenna is activated by a wireless energy transmitter, the antenna automatically switches to another quadrature polarization state for wireless data communication. The experimental results show that the adaptive switching characteristic provides a wireless channel isolation of more than 23 dB between wireless power transfer and data communication. In a practical indoor environment, the measurement of packet error rate of the communication link shows that the power level of MPT could be increased by 16 dB and still keep the wireless connectivity. Thus, the proposed design is suitable for devices powered by MPT and for simultaneous wireless information and power transfer applications.

Outage Analysis of the Power Splitting Based Underlay Cooperative Cognitive Radio Networks.

In the present paper, we investigate the performance of the simultaneous wireless information and power transfer (SWIPT) based cooperative cognitive radio networks (CCRNs). In particular, the outage probability is derived in the closed-form expressions under the opportunistic partial relay selection. Different from the conventional CRNs in which the transmit power of the secondary transmitters count merely on the aggregate interference measured on the primary networks, the transmit power of the SWIPT-enabled transmitters is also constrained by the harvested energy. As a result, the mathematical framework involves more correlated random variables and, thus, is of higher complexity. Monte Carlo simulations are given to corroborate the accuracy of the mathematical analysis and to shed light on the behavior of the OP with respect to several important parameters, e.g., the transmit power and the number of relays. Our findings illustrate that increasing the transmit power and/or the number of relays is beneficial for the outage probability.

Simultaneous Wireless Information and Power Transfer in a Network of On-body and Implantable Sensors With Temperature Constraint and Intelligent Channel Prediction

The wireless body area network (WBAN) is one of the applications of the Internet of things (IoT) for healthcare, which monitors human physiological parameters. In this paper, a two-objective optimization problem is designed to maximize the sum-throughput and wireless transferred energy simultaneously. The designed one-tier network includes body surface sensors, an implantable sensor, and one coordinator. All of these sensors can harvest energy from the body and radio frequency (RF) signals. A temperature constraint is considered for the implanted sensor due to the sensitivity of internal tissues. Each sensor transmits physiological data to the coordinator in the uplink according to the scheduled time slots obtained by solving the optimization problem. At the beginning of each frame in the downlink, the coordinator transmits a pilot signal to transfer wireless energy and for channel estimation at the sensors. We have used a Recurrent Neural Network (RNN) architecture to predict one time step ahead of the channel. Then by interpolation, the channel gains of all time slots of a frame are estimated and the time scheduling of the sensor access to the channel is improved. The simulation results show that the objective function and time scheduling are improved by the proposed algorithms.

Nonlinear Metamaterial Lenses for Inductive Power Transmission Systems Using Duffing-Resonator Based Unit Cells

Metamaterials (MTMs) based on a periodic array of resonant coils have been shown to behave as μ-negative (MNG), enabling the focusing of magnetic flux. The phenomenon has been deployed by designers to boost the efficiency of many inductively coupled systems, such as magnetic resonance imaging, underwater and underground communications, and charging base stations (CBS) for consumer electronics and implanted devices. However, due to their dependency on high-Q unit cells, linear MNG-like MTMs have limited bandwidth, restricting their use in many applications, notably in near-field simultaneous wireless information and power transmission (NF-SWIPT) systems. To improve the tight constraints of the amplitude-bandwidth trade-off of artificial magnetic lenses, this paper presents a theoretical analysis of nonlinear MTMs based on a lattice of Duffing resonators (DRs). Additionally, it introduces a criterium for the quantification and evaluation of the amplitude-bandwidth enhancement. The analytical results are based on a circuit model and further verified by numerical simulations using commercial software. The preliminary findings in this paper open up possibilities for nonlinear MTM lenses and can be applied to enhance the linear amplitude-bandwidth limit.

Protecting Multi-Function Wireless Systems From Jammers With Backscatter Assistance: An Intelligent Strategy

In this paper, we present a novel unified framework to protect multi-function wireless systems from jamming attacks. Examples of such multi-function system include joint radar and communication (JRC) systems and simultaneous wireless information and power transfer (SWIPT) systems. By abstracting the system functionalities as a joint optimization problem of multiple queues, we achieve effective resistance against jammers for the multi-functions simultaneously. We incorporate different anti-jamming techniques into one framework. Deception mechanism is adopted to lure the jammer to attack and make its actions more predictable, and ambient backscatter technology is used to leverage the jamming signals. Since conventional Markov decision process (MDP) has only one decision epoch at every time slot, it cannot be used to model the deception strategy which needs two decision epochs to leverage the jamming signals. We therefore formulate the problem using an advanced two-step MDP. After that, a deep reinforcement learning algorithm with a prioritized double deep Q-Learning architecture is proposed to learn optimal strategies in different system states. We show that by jointly considering the multi-functions of the system with potential jamming attacks during design phase, significant improvement can be achieved for both of the system functionalities.