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This work investigates the performance of a laser-powered unmanned aerial vehicle (UAV) based hybrid wireless network consisting of a UAV-mounted base station (UAV-BS), cellular user, a low-power IoT user, and a secondary IoT network consisting of a group of multiple IoT devices. Communication among these devices takes place in two different phases. In the first phase of transmission, UAV-BS fulfills its power requirements by harvesting power from a distributed laser charging-based laser power transfer and uses non-orthogonal multiple access (NOMA) signaling to transmit the information to both the users. Further, in the second phase of transmission, the IoT user harvests power using power-splitting (PS) protocol and uses it to communicate with the selected IoT device, selected using a signal to interference-plus-noise ratio based selection strategy from the secondary IoT network, while the cellular user transmits uplink information to UAV-BS. We discuss the effect of non-linear energy harvesting on the performance of secondary IoT network and UAV-BS. Next, we analyze the performance of the proposed system by deriving the closed-form expressions of the outage probabilities, throughput, and ergodic capacity of both the users, the secondary IoT network, and UAV-BS. Furthermore, we find the optimal values of power coefficient and target rates that maximize the throughput of the IoT user while attaining a desired throughput for the cellular user. We also demonstrate that a judicious choice of the power allocation coefficient is essential in order to maximize the sum throughput of the system and hence the energy efficiency. Simulation results verify the accuracy of derived expressions and validate the effectiveness of proposed algorithms.

We focus on the rate-optimal design of Wireless Powered Relay Networks (WPRNs) and propose a new cooperative communication scheme. Our scheme employs multiple wireless powered Amplify and Forward (AF) relays and relay selection and combines Time Splitting (TS), with Antenna Switching (AS) and Self Energy Recycling (SER). It consists of an initial Wireless Power Transfer (WPT) subframe, followed by a cooperative transmission subframe, during which one antenna is used for Energy Harvesting (EH) and SER and the remaining ones are used for data reception and data forwarding. For this scheme, we present solutions to the problems of 1) rate-optimal beamforming (BF) design, 2) rate-optimal, joint Harvesting Antenna Selection (HAS), BF design, and WPT subframe duration determination. Our solutions build on a generic piecewise linear EH model, which allows us to closely approximate the characteristics of different non linear EH measurements and models, by selecting the number of piecewise linear components and their parameters. In addition, we consider a realistic power consumption model at the relays that accounts for both transmit and circuit power consumption. Moreover, our BF solution is optimal and requires solving a set of simple optimization problems, where the solution of each one of them can be found in a simple closed form. Thus, it is characterized by low implementation complexity, and avoids sophisticated iterative optimization methods. To the best of our knowledge, this work is the first one to introduce a scheme, which combines TS, AS, and SER principles and exploits realistic EH and power consumption models at the relays. Finally, we assess the performance of our scheme over fading channels and find that it outperforms existing solutions that use the same hardware. [ABSTRACT FROM AUTHOR]

In this article, we investigate a multi-user multiple-input-single-output full-duplex system with simultaneous wireless information and power transfer under the non-linear energy harvesting model, where channel state information is imperfect. Since the channel estimation error is considered in our proposed system, the self-interference cannot be canceled perfectly. For such a system, a robust optimization problem that maximizes the minimum average total harvested power by jointly optimizing the uplink and downlink beamforming matrices is formulated. As the problem is non-linear and non-convex under channel estimation errors, a novel Newton method based iterative optimization algorithm is proposed to solve it efficiently. In each iteration, the semidefinite relaxation technique and S-Procedure method are applied to obtain the optimal beamforming vectors, which are proved to be optimal solutions with rank-one. Simulation results reveal that the proposed robust design can achieve better system performance than the non-robust scheme, both of which are based on the non-linear energy harvesting model.

In this paper, a novel intelligent reflecting surface (IRS)-assisted wireless powered communication network (WPCN) architecture is proposed for power-constrained Internet-of-Things (IoT) smart devices, where IRS is exploited to improve the performance of WPCN under imperfect channel state information (CSI). We formulate a hybrid access point (HAP) transmit energy minimization problem by jointly optimizing time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, IRS energy reflection coefficient and information reflection coefficient under the imperfect CSI and non-linear energy harvesting model. On account of the high coupling of optimization variables, the formulated problem is a non-convex optimization problem that is difficult to solve directly. To address the above-mentioned challenging problem, alternating optimization (AO) technique is applied to decouple the optimization variables to solve the problem. Specifically, through AO, time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, IRS energy reflection coefficient and information reflection coefficient are divided into three sub-problems to be solved alternately. The difference-of-convex (DC) programming is used to solve the non-convex rank-one constraint in solving IRS energy reflection coefficient and information reflection coefficient. Numerical simulations verify the superiority of the proposed optimization algorithm in decreasing HAP transmit energy compared with other benchmark schemes. [ABSTRACT FROM AUTHOR]

A reconfigurable intelligent surface (RIS)-assisted wireless communication system with non-linear energy harvesting (EH) and ultra-reliable low-latency constraints is considered for its possible applications in industrial automation. A distant data-center (DC) communicates with the multiple destination machines with the help of a full-duplex (FD) server machine (SM) and RIS. Assuming the deficiency of enough transmission power at the FD-SM, the SM is considered in the near vicinity of the destinations in the industry to forward the data received from the distant DC. The reception at SM is assisted by the RIS and a non-linear hybrid power-time splitting (PTS) based EH receiver architecture is adopted to extend the lifespan of SM, thus increasing network lifetime. The scheduling of multiple destinations is done by SM based on the considered selection criteria namely, random (RND) scheduling, absolute (ABS) channel-power-based (CPB) scheduling and normalized (NRM) CPB scheduling. The end-to-end performance of the considered FD RIS-assisted network is analyzed, and the expressions for the block error rate (BLER) for all scheduling schemes are derived. Moreover, the effects of number of RIS elements, packet size, channel uses on the system performance are analyzed for the considered ultra-reliable and low-latency communication (URLLC) network. The scheduling fairness of all the scheduling schemes is also analyzed to study the performance-fairness trade-off. The derived analytical results are verified through Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

Wireless power transfer (WPT) is an effective way to prolong the lifetime of the energy-constraint networks. In this paper, we investigate a wireless powered cooperative non-orthogonal multiple access (WP-CNOMA) system, consisting of a power beacon (PB), an information transmitter (S), multiple relays (R) and two information receiving devices with near device D1 and far device D2. We assume both S and R are energy-constraint and there is no direct link between S and D2. With the help of PB, S and R can harvest energy from it to restart the communication for WP-CNOMA network. For such a system, low-complexity but effective relay and antenna selection schemes are applied. To characterize the performance, outage probabilities and average throughput are derived for linear and non-linear energy harvesting (EH) models, respectively. Moreover, to maximize the average throughput, invoking the unimodal feature for average throughput with respect to the EH time, we find the optimal EH time via Golden section search method. Simulation results validate the accuracy of analytical results, and reveal the performance gain for our system over the benchmark schemes. Also, it can be seen that the non-linear EH model shows different outage behaviors from the linear one. On the other hand, considering the practical application and to improve the performance, the optimization for a simple WP-CNOMA system with single-antenna PB and single relay is also investigated, in which we aim to maximize the minimum throughput by jointly optimizing EH time and power allocation. A low-complexity analytical method is developed to find the max-min rate. Numerical results show that through optimization, the system performance can be improved significantly.

In this article, we investigate the performance of a piece-wise linear model of energy harvesting-based multiuser overlay spectrum sharing system. Herein, an energy-constrained secondary node acts as a cooperative relay to assist the information transmission between a primary transmitter and multiple primary receivers. In return for the cooperation, the secondary node enjoys access to the primary user's spectrum for its own information transfer. Specifically, by employing a time-switching based receiver, the secondary node harvests energy from the received radio-frequency signal of primary transmitter during a dedicated energy harvesting phase. In the subsequent information transfer phase, the secondary node splits the harvested power to forward the primary data as well as its own information intended for another secondary user. We analyze the impact of decoding primary's information at the secondary receiver on the performance of secondary network. Importantly, we propose an improved energy harvesting-based relaying scheme which makes an efficient use of available degrees of freedom and thereby enhances the performance of both primary and secondary networks significantly. For this analytical framework, we derive the expressions of outage probability for primary and secondary networks. Numerical and simulation results are obtained to extract various useful insights and to validate our theoretical developments.

This paper considers a max-min rate optimization problem with practical non-linear energy harvesting (NLEH) in which a multi-antenna hybrid access point transfers power to the devices via energy beamforming (BF), followed by the devices sending their data simultaneously by consuming the harvested energy. Using a sigmoid NLEH model with sensitivity, we tackle the joint energy BF and time allocation problem in two steps by solving the NLEH-aware energy BF problem for given time allocation and then solving the convex time allocation problem formulated with the aforementioned energy BF solution. We propose several iterative methods to solve the non-convex energy BF problem with and without approximation of the NLEH function. In addition, we present an asymptotic energy BF problem for a large-antenna system that can be solved at low complexity. The results show that the algorithms developed with a simple NLEH approximation provide almost the same performance with the algorithms developed with the exact NLEH function. Furthermore, the sensitivity region of the NLEH should be considered more carefully than the saturation region in the max-min rate optimization problem.

This paper investigates the relationship among the traffic throughput, statistical data latency requirement and system configurations in a wireless powered multimedia communication system. Firstly, a system model is built up with considerations of two operation modes and practical non-linear energy harvesting process. Based on the system model, the effective capacity of the considered system is derived based on the wireless charging parameter and fix data transmission rate. Then, the latency violation provability is studied by jointly taking effective capacity, traffic arrival and maximum tolerable data latency into account. Thereafter, the traffic maximization problem is transformed to the effective capacity maximization problem. Furthermore, We propose an optimal solution and a near-optimal solution to find out the system configurations of wireless charging time and transmission rate. Simulation results verify the accuracy of the near-optimal solution and also shed light on the operation mode selection in the considered system.

Mobile-edge computing (MEC) and wireless power transfer are technologies that can assist in the implementation of next generation wireless networks, which will deploy a large number of computational and energy limited devices. In this letter, we consider a point-to-point MEC system, where the device harvests energy from the access point’s (AP’s) transmitted signal to power the offloading and/or the local computation of a task. By taking into account the non-linearities of energy harvesting, we provide analytical expressions for the probability of successful computation and for the average number of successfully computed bits. Our results show that a hybrid scheme of partial offloading and local computation is not always efficient. In particular, the decision to offload and/or compute locally, depends on the system’s parameters such as the distance to the AP and the number of bits that need to be computed. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel hybrid user pairing (HUP) scheme in multiuser multiple-input single-output non-orthogonal multiple access networks with simultaneous wireless information and power transfer. In this system, two information users with distinct channel conditions are optimally paired while energy users perform energy harvesting (EH) under non-linearity of the EH circuits. We consider the problem of jointly optimizing user pairing and power allocation to maximize the overall spectral efficiency (SE) and energy efficiency (EE) subject to user-specific quality-of-service and harvested power requirements. A new paradigm for the EE-EH trade-off is then proposed to achieve a good balance of network power consumption. Such design problems are formulated as the maximization of non-concave functions subject to the class of mixed-integer non-convex constraints, which are very challenging to solve optimally. To address these challenges, we first relax binary pairing variables to be continuous and transform the design problems into equivalent non-convex ones, but with more tractable forms. We then develop low-complexity iterative algorithms to improve the objectives and converge to a local optimum by means of the inner approximation framework. Simulation results show the convergence of proposed algorithms and the SE and EE improvements of the proposed HUP scheme over state-of-the-art designs. In addition, the effects of key parameters such as the number of antennas and dynamic power at the BS, target data rates, and energy threshold, on the system performance are evaluated to show the effectiveness of the proposed schemes in balancing resource utilization. [ABSTRACT FROM AUTHOR]

Wirelessly-powered sensor networks (WPSNs) are becoming increasingly important in different monitoring applications. We consider a WPSN where a multiple-antenna base station, which is dedicated for energy transmission, sends pilot signals to estimate the channel state information and consequently shapes the energy beams toward the sensor nodes. Given a fixed energy budget at the base station, in this paper, we investigate the novel problem of optimally allocating the power for the channel estimation and for the energy transmission. We formulate this non-convex optimization problem for general channel estimation and beamforming schemes that satisfy some qualification conditions. We provide a new solution approach and a performance analysis in terms of optimality and complexity. We also present a closed-form solution for the case where the channels are estimated based on a least square channel estimation and a maximum ratio transmit beamforming scheme. The analysis and simulations indicate a significant gain in terms of the network sensing rate, compared to the fixed power allocation, and the importance of improving the channel estimation efficiency. [ABSTRACT FROM AUTHOR]

This paper considers a cognitive small cell network, where one cognitive base station (CBS) transmits information to the cognitive user and energy to the energy harvesting receivers (EHRs). The Markov channel model is exploited to characterize the state change of the macrocell base station. The spectrum sensing time, the spectrum sensing interval, and the beamforming matrixes of the CBS are jointly optimized to achieve three goals: the maximization of the CBS throughput, the minimization of the energy cost of the CBS, and the minimization of the interferences to the macrocell users (MUEs). These objectives are optimized subject to the interference constraints of the MUEs, the secrecy rate constraint, the transmit power constraint of the CBS, and the energy harvesting constraints of the EHRs. The formulated problems are challenging non-convex and difficult to solve. A 1-D line search method and semidefinite relaxation-based algorithm is proposed to solve these problems. It is proved that the optimal solution can be obtained under some conditions. If the conditions are not satisfied, Gaussian randomization procedure is used to obtain the suboptimal solutions. Simulation results verify our theoretical findings and demonstrate the effectiveness of the proposed resource allocation scheme.

The design of energy harvesting (EH) scheme is one of important issues in energy-constrained relaying networks. Since most of the existing EH schemes assume a linear EH model, which cannot capture the properties of EH circuits, the EH schemes dedicated for a practical EH model should be redesigned. Based on the time switching (TS) and power splitting (PS) receiver architectures, we study two EH schemes, namely, PS scheme and TS scheme, in an amplify-and-forward (AF) energy-constrained relaying network under a non-linear EH model. Two problems are formulated to maximize the achievable throughput based on the instantaneous channel state information by optimizing the PS ratio and TS ratio, respectively. The solutions for both EH schemes are obtained. Numerical results are presented to show that the designed EH schemes based on the non-linear EH model are able to achieve a higher throughput than those based on the existing linear model. It is found that employing a non-linear energy harvester instead of the linear one into AF relaying network, and the PS scheme still outperforms the TS scheme in general.

In wireless power transfer (WPT)-assisted relaying systems, spectral efficiency (SE) of source-relay link plays a dominant role in system SE performance due to the limited transmission power at the WPT-aided relay. In this paper, we propose a novel protocol for a downlink orthogonal frequency division multiple access (OFDMA) system with a WPT-aided relay operating in full-duplex (FD) decode-and-forward (DF) mode, where the time slot durations of the source-relay and relay-users hops are designed to be dynamic, to enhance the utilization of degrees of freedom and hence the system SE. In particular, a multiple-input and signal-output (MISO) source-relay channel is considered to satisfy the stringent sensitivity of the energy harvesting (EH) circuit at the relay, while a single-input and single-output (SISO) relay-user channel is considered to alleviate the power consumption at the relay node. Taking into account the non-linearity of EH efficiency, a near-optimal iteration-based dynamic WPT-aided FD relaying (A-FR) algorithm is developed by jointly optimizing the time slot durations, subcarriers, and transmission power at the source and the relay. Furthermore, self-interference generated at the relay is utilized as a vital energy source rather than being canceled, which increases substantially the total energy harvested at the FD relay. We also reveal some implicit characteristics of the considered WPT-aided FD relaying system through intensive discussions. Simulation results confirm that the proposed A-FR achieves a significant enhancement in terms of SE with different relay's locations and the number of users, compared to the conventional symmetric WPT-aided FD relaying (S-FR) and the time-switching-based WPT-aided FD relaying (TS-FR) benchmarks. [ABSTRACT FROM AUTHOR]

This paper studies joint source and relay beamforming for a wireless powered downlink multirelay multiuser network. Considering nonlinear energy harvesting and imperfect channel state information, we aim to minimize the total transmit power at the base station by jointly optimizing the source beamforming and the relay beamforming weights under the energy causality constraints at the relays and the signal-to-noise ratio constraints at the users. The formulated problem is highly nonconvex, and thus, it is difficult to solve. To solve the problem, we first transform it into a worst-case optimization, and then, an iterative algorithm is developed to solve this worst-case optimization. Numerical results show the advantage of the proposed robust scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal power minimization design of simultaneous wireless information and power transfer systems under non-linear energy harvesting (EH) model, where a multi-antenna hybrid access point (H-AP) simultaneously transmits information and power to multiple heterogeneous users, such as information-energy receivers (IERs), information receivers (IRs), and ERs. Power splitting (PS) receiver architecture is adopted at all IERs. In order to achieve green system design, an optimization problem is formulated to minimize the transmit power of H-AP subject to the required signal-to-interference-plusnoise ratios (SINRs) constraints at IERs and IRs, and the harvested energy constrains at IERs and ERs, by jointly optimizing the beamforming vector at H-AP and the PS ratios at IERs. Since the problem is nonconvex and the employ of the non-linear EH model makes it more difficult to solve, the semidefinite relaxation and variable substitutions are used to handle it. For some cases, we theoretically prove that the globe optimal solution can be guaranteed by using our method, and for rest cases, we discuss its optimality via simulations. Numerical results show that although the traditional linear EH model is feasible for the practical EH circuits in some cases, the corresponding system consumes more transmit power than that under the non-linear model EH. Moreover, the effects of the numbers of users, the required SINRs, and the harvested energy on the system transmit power are also discussed.

In this letter, a cooperative cognitive radio network, in presence of an eavesdropper, is considered that operates in a frame structure comprising of energy harvesting, spectrum sensing and cooperation or opportunistic data transmission. The objective is to maximize the sum secondary throughput under the constraints of sensing reliability, harvesting energy causality, primary user cooperation data rate, secondary data outage, sum and individual secondary secrecy outage. Results show a gain in sum throughput ~25.43% over the existing work. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) and non-orthogonal multiple access (NOMA) have been deemed two promising technologies due to their potential to achieve high spectral efficiency and massive connectivity. This paper studies a multiple-input single-output NOMA CR network relying on simultaneous wireless information and power transfer conceived for supporting a massive population of power limited battery-driven devices. In contrast to most of the existing works, which use an ideally linear energy harvesting model, this study applies a more practical non-linear energy harvesting model. In order to improve the security of the primary network, an artificial-noise-aided cooperative jamming scheme is proposed. The artificial-noise-aided beamforming design problems are investigated subject to the practical secrecy rate and energy harvesting constraints. Specifically, the transmission power minimization problems are formulated under both perfect channel state information (CSI) and the bounded CSI error model. The problems formulated are non-convex, hence they are challenging to solve. A pair of algorithms either using semidefinite relaxation (SDR) or a cost function are proposed for solving these problems. Our simulation results show that the proposed cooperative jamming scheme succeeds in establishing secure communications and NOMA is capable of outperforming the conventional orthogonal multiple access in terms of its power efficiency. Finally, we demonstrate that the cost function algorithm outperforms the SDR-based algorithm. [ABSTRACT FROM AUTHOR]