Wireless Powered Communication System Research Articles

Enhancing Throughput in IoT Networks: The Impact of Active RIS on Wireless Powered Communication Systems

This paper investigates the potential of active reconfigurable intelligent surfaces (RIS) to enhance wireless-powered communication networks (WPCNs), addressing the evolving connectivity needs of the internet of things (IoT). Active RIS, capable of amplifying and reflecting signals, offers a solution to surpass the limitations of passive RIS, such as double-fading attenuation, aiming to significantly improve network throughput and coverage. Our research focuses on exploiting the amplification capabilities of active RIS to boost the overall network sum throughput, engaging in a comprehensive optimization of critical network parameters, including time allocation, reflection coefficients, and phase shift matrices specific to active RIS. The formulated problem is non-convex and highly complex due to the coupling of optimization variables. We employed a successive convex approximation algorithm to solve the throughput maximization problem by converting the non-convex constraints into approximated convex constraints and solving them iteratively. Through extensive simulations, we demonstrate that our active RIS-assisted network substantially outperforms networks facilitated by passive RIS, marking a significant advancement in WPCN performance. These findings underscore the potential of active RIS technology in realizing the full capabilities of IoT connectivity.

Ergodic Secrecy Capacity Analysis for RIS-Aided Wireless Powered Communication System Under Different Phase Shifting

Ergodic Secrecy Capacity Analysis for RIS-Aided Wireless Powered Communication System Under Different Phase Shifting

Physical-Layer Security for Intelligent-Reflecting-Surface-Aided Wireless-Powered Communication Systems

Physical-Layer Security for Intelligent-Reflecting-Surface-Aided Wireless-Powered Communication Systems

On the Deployment of Clustered Power Beacons in Random Wireless Powered Communication

Wireless powered communication (WPC) is able to provide wireless devices (WDs) practically infinite energy by using the radio frequency energy harvesting technique. The electricity of WDs for the wireless information transmission (WIT) is converted from the received electromagnetic signals of wireless energy transfer (WET). Power beacon (PB) is usually deployed as the dedicated energy source in WPC networks and the performance of WET is sensitive to the path-loss effect. Thus, both WET and WIT are significantly influenced by the locations of the PBs. To enable efficient transmission in WPC, this paper analytically investigates the impact of the PB deployment strategies on the WPC performance when WDs are clustered around the access points (APs). Specifically, we propose the PB deployment strategy based on the truncated Poisson cluster process (PCP) model. The distribution of PBs is correlated to the locations of WDs by choosing APs as their common parent points. Then, we derive the semi-closed form expressions for the energy outage probability and the transmission success probability. We further present the expressions of the meta distributions of WET and WIT, and investigate the proportion of the WDs in one cluster that achieves successful transmission while satisfying the reliability constraint. Moreover, the distance distribution between the WD and the intra-cluster PBs is analytically derived for the proposed correlated PCP model. By comparing the performance with other deployment strategies, it is shown that the preference of the PB deployment strategy depends on the PB density. The analytical and numerical results can provide insightful guidelines for designing practical WPC systems.

Performance of Wireless Powered Communication Systems Over Beaulieu-Xie Channels With Nonlinear Energy Harvesters

Performance of wireless powered wireless systems is analyzed. The wireless devices in such systems scavenge energy from sources in downlinks and use the energy to communicate in uplinks. We introduce two new models for these energy harvesters to consider their nonlinear circuitry and their functioning over multiple line-of-sight and non-line-of-sight channels. The newly proposed Beaulieu-Xie fading model is used to characterize this manifold of channels. Performance analyses of average harvested energy and transmission outage probability show good fit between the proposed models and measured data.

Performance Analysis of Beacon-Assisted Wireless Powered Communications With Spatially Random Sensors

In this work, we present the performance evaluation of a power beacon-assisted wireless-powered communication system in the presence of multiple co-channel interferers. We consider and compare three distinct interference modeling scenarios, namely the totally induced interference is approximated by the Gamma distribution, interferers are distributed according to a Poisson point process and interferers are distributed according to a binomial point process. Analytical expressions for the outage probability and the ergodic capacity of the considered system under each interference scenario are derived. Furthermore, optimization problems are formulated to determine the optimum switching time maximizing the achieved ergodic capacity. Numerical results accompanied with Monte Carlo simulations are presented to corroborate the proposed theoretical analysis.

On the Ergodic Secrecy Capacity of Intelligent Reflecting Surface Aided Wireless Powered Communication Systems

This letter studies physical layer security (PLS) of an intelligent reflecting surface (IRS) aided wireless powered communication (WPC) system in the presence of a passive eavesdropper, and proposes three secure IRS-WPC modes. In mode-I, the IRS is deployed between hybrid access point (HAP) and wireless user (U) for co-located power station (PS) and access point (AP). In mode-II, the IRS is deployed between AP and U for separate PS and AP, while in mode-III, the IRS is deployed between PS and U for separate PS and AP. For each mode, the optimal phase shift is designed to maximize the reception of energy and information at legitimate receiver. The accurate and asymptotic ergodic secrecy capacity (ESC) of each mode is analyzed, and various new closed-form expressions are obtained. The results reveal that mode-I and mode-II significantly outperform benchmark without IRS, while mode-III outperforms benchmark without IRS under lower transmission power or small number of IRS elements.

Extreme Age of Information for Wireless-Powered Communication Systems

The extreme or maximum age of information (AoI) is analytically studied for wireless communication systems. In particular, a wireless powered single-antenna source node and a receiver (connected to the power grid) equipped with multiple antennas are considered when operated under independent Rayleigh-faded channels. Via the extreme value theory and its corresponding statistical features, we demonstrate that the extreme AoI converges to the Gumbel distribution whereas its corresponding parameters are obtained in straightforward closed-form expressions. Capitalizing on this result, the risk of the extreme AoI realization is analytically evaluated according to some relevant performance metrics, while some useful engineering insights are manifested.

Optimal downlink and uplink design in a wireless powered two‐user indoor communication system

This paper applies the wireless powered communication network (WPCN) to an indoor communication system with two energy harvesting (EH) enabled users. Unlike the existing WPCN works designed for outdoor communications, where each user harvests energy only from the signals transmitted by a dedicatedly deployed hybrid access point (H-AP), due to the short device-to-device distance in the indoor scenario, each user additionally harvests a sufficient amount of energy from the information signals transmitted by the H-AP and the other user. First, the joint downlink and uplink throughput are maximized for the wireless powered indoor communication system. This problem is non-convex. Thus, the authors manage to transform this problem into a convex one and solve it using convex optimization techniques. The solutions reveal that the total throughput increases largely over a reduced device-to-device distance due to the resultant harvested energy from both energy and information signals at each user. However, an unfair downlink versus uplink rate allocation phenomenon is observed. Thus, considering the importance of uplink communication quality for various indoor applications, a new problem is further proposed to maximize the uplink sum-throughput over both users with an additional constraint to ensure a sufficient downlink rate. This problem is also shown to be non-convex and is solved optimally by using a method similar to that in the first problem. Numerical results demonstrate the effectiveness of the proposed approach for improving the downlink versus uplink rate allocation fairness in the indoor wireless-powered communication system.

Online policies for throughput maximization of backscatter assisted wireless powered communication via reinforcement learning approaches

In this paper, we consider the design of online policies in a backscatter assisted wireless powered communication system, aiming at maximizing the longterm average throughput. We consider a complete data life cycle, from sampling, compression, transmission to reception and decompression. Practical constraints including finite battery capacity, time-varying uplink channel and nonlinear energy harvesting model are considered. An optimization problem is formulated in a Markov decision process framework to maximize the longterm average throughput by a hybrid of mode switching, time and power allocation, and compression ratio selection. Capitalizing on this, we first adopt value iteration (VI) algorithm to find offline optimal solution as benchmark. Then, we propose Q-learning (QL) and deep Q-learning (DQL) algorithms to obtain online solutions without prior information. Simulation results demonstrate the effectiveness of the hybrid transmission mode with flexible data compression. Furthermore, DQL-based online solution performs the closest to the optimal VI-based offline solution and significantly outperforms the other two baseline schemes QL and random policy. Insight analysis on the structure of the optimal policy is also provided.

AoI-Optimal Joint Sampling and Updating for Wireless Powered Communication Systems

This paper characterizes the structure of the Age of Information (AoI)-optimal policy in wireless powered communication systems while accounting for the time and energy costs of generating status updates at the source nodes. In particular, for a single source-destination pair in which a radio frequency (RF)-powered source sends status updates about some physical process to a destination node, we minimize the long-term average AoI at the destination node. The problem is modeled as an average cost Markov Decision Process (MDP) in which, the generation times of status updates at the source, the transmissions of status updates from the source to the destination, and the wireless energy transfer (WET) are jointly optimized. After proving the monotonicity property of the value function associated with the MDP, we analytically demonstrate that the AoI-optimal policy has a threshold-based structure w.r.t. the state variables. Our numerical results verify the analytical findings and reveal the impact of state variables on the structure of the AoI-optimal policy. Our results also demonstrate the impact of system design parameters on the optimal achievable average AoI as well as the superiority of our proposed joint sampling and updating policy w.r.t. the generate-at-will policy.

Reinforcement Learning Based Adaptive Resource Allocation for Wireless Powered Communication Systems

Wireless powered communication (WPC) is one of the promising techniques for future energy-constrained wireless networks. In this letter, we consider a WPC system composed of a hybrid access point and an energy harvesting node (EHN). In this system, we propose a reinforcement learning based adaptive resource allocation scheme that dynamically assigns the channel resources to minimize the outage probability of information transfer while satisfying the average power constraint at the EHN, which is formulated as a constrained Markov decision process (MDP) problem. To solve this challenging problem, we first transform the originally formulated problem into its equivalent unconstrained MDP with multi-objective. Then, to find the resource allocation policy, we propose a novel Q-learning algorithm. Numerical results demonstrate the superior performance and effectiveness of the proposed scheme.

On the Throughput of Interference-Based Wireless Powered Communications With Receive Antenna Selection

We propose an interference-based wireless powered communication system in which an energy constrained source harvests energy from a single dominant co-channel interferer and then transmits information to a destination equipped with N receive antennas. Assuming interference dominates noise power at the destination and the receive antenna that maximizes the signal-to-interference ratio is selected, we investigate the average throughput for the delay-limited and delay-tolerant transmission modes. In particular, we derive an analytical expression of the average throughput for the delay-limited transmission mode, and a precise lower bound on the average throughput for the delay-tolerant transmission mode. Furthermore, we derive simplified asymptotic expressions of the average throughput for both transmission modes assuming asymptotically large number of receive antennas (i.e., N → ∞). We use the obtained asymptotic expressions to derive insightful closed-form expressions for the optimal energy harvesting time, which maximizes the average throughput, for both transmission modes. We show that the throughput-optimal energy harvesting time for the delay-limited and the delay-tolerant transmission scale like O(1/√N) and O(1/log(N)), respectively, for asymptotically large N.

On the Throughput of Wireless Powered Communication Systems With a Multiple Antenna Bidirectional Relay

We consider an amplify-and-forward-based relay network comprising a hybrid access point, multi-antenna bidirectional relay and user terminal (UT). The relay first harvests energy using a power splitting (PS) scheme and then transfers power wirelessly to the UT. We analyze the throughput assuming maximum ratio combining in conjunction with a linear combination of information beamforming and energy beamforming at the relay. In particular, we derive two new closed-form approximations for the ergodic throughput in the asymptotic regime for a large number of antennas at the relay. We also present new solutions for the optimal beamforming vector and PS factor that maximize throughput. Finally, all the analytical results are corroborated through simulations.

Online Policies for Throughput Maximization of Energy-Constrained Wireless-Powered Communication Systems

This work considers the design of online transmission policy in a wireless-powered communication system with a given energy budget. The system design objective is to maximize the long-term throughput of the system exploiting the energy storage capability at the wireless-powered node. We formulate the design problem as a constrained Markov decision process (CMDP) problem and obtain the optimal policy of transmit power and time allocation in each fading block via the Lagrangian approach. To investigate the system performance in different scenarios, numerical simulations are conducted with various system parameters. Our simulation results show that the optimal policy significantly outperforms a myopic policy which only maximizes the throughput in the current fading block. Moreover, the optimal allocation of transmit power and time is shown to be insensitive to the change of modulation and coding schemes, which facilitates its practical implementation.

On Buffer-Constrained Throughput of a Wireless-Powered Communication System

In this paper, the buffer-constrained throughput performance of a multi-user wireless-powered communication (WPC) system is investigated, where energy harvesting follows a non-linear model. The investigation focuses on the buffer overflow performance of sending data in the downlink (DL) from the access point (AP) node to each user equipment (UE) node and that in the uplink from each UE node to the AP node, based on which the throughput performance on both directions when a buffer constraint is enforced is studied. Specifically, the buffer overflow probability at each node is analyzed, based on which the buffer-constrained throughput is studied. In addition, to ensure the throughput performance under the buffer constraint, the DL transmission power allocation policy and the required energy storage capacity at each UE are investigated. Also, the optimal channel time allocation policy is studied with the objective of maximizing the minimum buffer-constrained throughput guaranteed to each UE at the same time. To this aim, an optimization problem is first formulated and then a dichotomy-based time allocation algorithm combined with a one-dimensional search is proposed to solve this problem. The analysis and results, explicitly relating the throughput to the buffer constraint in addition to WPC characteristics, shed new light on the design and performance analysis of WPC systems.

Resource Allocation for a Wireless Powered Integrated Radar and Communication System

The integrated radar and communication system is promising in the next generation wireless communication networks. However, its performance is confined by the limited energy. In order to overcome this, a wireless powered integrated radar and communication system is proposed. An energy minimization problem is formulated subject to constraints on the radar and communication performances. The energy beamforming and radar-communication waveform are jointly optimized to minimize the consumption energy. The challenging non-convex problem is solved by using semidefinite relaxation and auxiliary variable methods. It is proved that the optimal solution can be obtained. Simulation results demonstrate that our proposed optimal design outperforms the benchmark scheme.

Transmission delay minimization in wireless powered communication systems

We study transmission delay minimization of a wireless powered communication (WPC) system in a point-to-point scenario with one hybrid access point (HAP) and one WPC node. In this type of communications, the HAP sends energy to the node at the downlink (DL) for a given time duration and the WPC node harvests enough radio frequency (RF) power. Then, at the uplink (UL) channel, the WPC node transmits its collected data in a given time duration to the HAP. Minimizing such round trip delay is our concern here. So, we have defined four optimization problems to minimize this delay by applying the optimal DL and UL time durations and also the optimal power at the HAP. These optimization problems are investigated here with thorough comparison of the obtained results. After that, we extend our study to the multiuser case with one HAP and $K$ nodes and two different optimization problems are studied again in these cases.

Performance Analysis of Near-Optimal Energy Buffer Aided Wireless Powered Communication

In this paper, we consider a wireless powered communication system, where an energy harvesting (EH) node harvests energy from a radio frequency (RF) signal broadcasted by an access point (AP) in the downlink (DL). The node stores the harvested energy in an energy buffer and uses the stored energy to transmit data to the AP in the uplink (UL). We investigate two simple online transmission policies for the EH node, namely a best-effort policy and an on-off policy, which do not require knowledge of the EH profile nor channel knowledge. In particular, for both policies, the EH node transmits in each time slot with a constant desired power if sufficient energy is available in its energy buffer. Otherwise, the node transmits with the maximum possible power in the best-effort policy and remains silent in the on-off policy. For both policies, we use the theory of discrete-time continuous-state Markov chains to analyze the limiting distribution of the stored energy for finite- and infinite-size energy buffers. We provide this limiting distribution in closed form for a Nakagami- $m$ fading DL channel and analyze the outage probability for a Nakagami- $m$ fading UL channel. All derived analytical results are not limited to EH via RF WPT but are applicable for any independent and identically distributed EH process from e.g. solar and wind energy. Our results reveal that, for low-to-medium outage probabilities, the best-effort policy is superior to the on-off policy and the optimal UL transmit power of the EH node that minimizes the outage probability is always less than the average harvested power. The opposite behaviour is observed for high outage probabilities. Furthermore, we show that the minimum outage probability of the two proposed policies is near-optimal.

Performance Analysis of Wireless Powered Communications With Multiple Antennas

This paper analytically investigates the performance of a wireless powered communication system, where a source powered by multiple dedicated power beacons communicates with a destination. Specifically, we consider a harvest-then-transmit multiple-input multiple-output communication system, where the source uses all harvested energy for information transmission in each time block. The random placement of terminals is characterized by stochastic geometry tools. Taking into account the effects of imperfect channel state information in wireless energy transfer and wireless information transmission, the ergodic achievable rate of information transmission is derived analytically by considering co-channel interference (CCI) and the noise. In addition, assuming the CCI can be accurately approximated by a Gamma distributed variable, the outage probability of information transmission is investigated. Numerical results validate the analytical results and show the impacts of the antenna number, distribution density, estimation error, and the transmit power of terminals on the system performance.