Maximizing Ergodic Throughput in Wireless Powered Communication Networks

In this letter, the uplink (UL) wireless information transmission (WIT) and downlink (DL) wireless power transfer (WPT) in cell-free massive multiple-input multiple-output (CF-mMIMO) networks are investigated. Specifically, the mobile terminals (MTs) collect the radio-frequency energy emitted from the access points (APs) in the DL WPT phase and then use the harvested energy (HE) to transmit pilot and data symbols in the UL WIT phase. Considering the performance of CF-mMIMO networks with a large number of MTs is severely bottlenecked by pilot contamination, the superimposed pilot transmission (SPT) is advocated to alleviate its impact and improve transmission efficiency. Based on the SPT, closed-form UL achievable spectral efficiency (SE) and DL average HE expressions are derived. Simulation results verify the accuracies of the derived expressions and indicate that the SPT significantly outperforms the regular pilot transmission in terms of both SE and HE.

In this paper, we study a wireless powered communication network (WPCN) subject to the co-channel interference. In the down-link (DL), the hybrid access point (H-AP) broadcasts the wireless energy offered by the radio frequency (RF) signal to the user and relay. In the up-link (UL), the user and relay nodes transmit information to the H-AP through time-division-multiple-access (TDMA). In contrast to conventional WPCN, the interference can be considered as additional energy, not just as a threat for the data transmissions. Through the manner of curve fitting, we obtain the closed-form expression for the system outage probability and the throughput. Furthermore, the optimal time allocation to maximize the average system throughput is obtained. Finally it is shown that the theoretical results fit the simulation results closely and the proposed optimal scheme achieves the best performances.

This paper proposes a joint beamforming and resource allocation scheme to maximize the minimum capacity for wireless powered communication network (WPCN) designed for multi-user distributed massive multi-input multi-output (DM-MIMO) system with full-duplex radio remote heads (RRHs), which enable simultaneous uplink (UL) and downlink (DL) communications. The minimum capacity is maximized by a proposed algorithm based on the non-negative matrix theory. The simulation results have demonstrated that the achievable max-min capacity of the DM-MIMO is considerably higher compared to that of the CMMIMO system. It has also showed that the convergence speed of the proposed algorithm is so fast.

This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN), in which a UAV is dispatched as a mobile access point (AP) to serve a set of ground users periodically. The UAV employs the radio frequency (RF) wireless power transfer (WPT) to charge the users in the downlink, and the users use the harvested RF energy to send independent information to the UAV in the uplink. Unlike the conventional WPCN with fixed APs, the UAV-enabled WPCN can exploit the mobility of the UAV via trajectory design, jointly with the wireless resource allocation optimization, to maximize the system throughput. In particular, we aim to maximize the uplink common (minimum) throughput among all ground users over a finite UAV's flight period, subject to its maximum speed constraint and the users' energy neutrality constraints. The resulted problem is nonconvex and thus difficult to be solved optimally. To tackle this challenge, we first consider an ideal case without the UAV's maximum speed constraint, and obtain the optimal solution to the relaxed problem. The optimal solution shows that the UAV should successively hover above a finite number of ground locations for downlink WPT, as well as above each of the ground users for uplink communication. Next, we consider the general problem with the UAV's maximum speed constraint. Based on the above multilocation-hovering solution, we first propose an efficient successive hover-and-fly trajectory design, jointly with the downlink and uplink wireless resource allocation, and then propose a locally optimal solution by applying the techniques of alternating optimization and successive convex programming (SCP). Numerical results show that the proposed UAV-enabled WPCN achieves significant throughput gains over the conventional WPCN with fixed-location AP.

In this paper, we find the optimum lengths of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">UL</sub> , T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DL</sub> and B i.e. the uplink (UL) and downlink (DL) pilots and feedback bits respectively maximizing the sum of the lower bounds of the UL and the DL rates. With the aid of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">UL</sub> symbols, the Base Station (BS) estimates the UL channel of each user. T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DL</sub> symbols are means of estimating the downlink channel, which after being normalized and quantized with B bits, is made available at the BS. Estimated Channel State Information (CSI) and quantized Channel Direction Information (CDI), which may be received erroneously, are thus available at the BS for computing the receive and the transmit Zero-forcing (ZF) filters, respectively. The use of ZF enables the derivation of analytical DL and UL mean squared error (MSE) expressions that give a lower bound on the DL and UL rates, respectively, needed for our optimization.

The newly emerging wireless powered communication networks (WPCNs) have recently drawn significant attention, where radio signals are used to power wireless terminals for information transmission. In this paper, we study a WPCN where one multi-antenna access point (AP) coordinates energy transfer and information transfer to/from a set of single-antenna users. A harvest-then-transmit protocol is assumed where the AP first broadcasts wireless power to all users via energy beamforming in the downlink (DL), and then the users send their independent information to the AP simultaneously in the uplink (UL) using their harvested energy. To optimize the users' throughput and yet guarantee their rate fairness, we maximize the minimum throughput among all users by a joint design of the DL-UL time allocation, the DL energy beamforming, and the UL transmit power allocation plus receive beamforming. We solve this non-convex problem optimally by two steps. First, we fix the DL-UL time allocation and obtain the optimal DL energy beamforming, UL power allocation and receive beamforming to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of all users. This problem is shown to be in general non-convex; however, we convert it equivalently to a spectral radius minimization problem, which can be solved efficiently by applying the alternating optimization based on the non-negative matrix theory. Then, the optimal time allocation is found by a one-dimension search to maximize the minimum rate of all users. Furthermore, two suboptimal designs of lower complexity are proposed, and their throughput performance is compared against that of the optimal solution.

Intelligent reflecting surface (IRS) can effectively enhance the energy and spectral efficiency of wireless communication system through the use of a large number of lowcost passive reflecting elements. In this paper, we investigate throughput optimization of IRS-assisted user cooperation in a wireless powered communication network (WPCN), where the two WDs harvest wireless energy and transmit information to a common hybrid access point (HAP). In particular, the two WDs first exchange their independent information with each other and then form a virtual antenna array to transmit jointly to the HAP. We aim to maximize the common (minimum) throughput performance by jointly optimizing the transmit time and power allocations of the two WDs on wireless energy and information transmissions and the passive array coefficients on reflecting the wireless energy and information signals. By comparing with some existing benchmark schemes, our results show that the proposed IRS-assisted user cooperation method can effectively improve the throughput performance of cooperative transmission in WPCNs.

In this paper, we consider deploying an intelligent reflecting surface (IRS) to enhance the downlink (DL) energy transfer and uplink (UL) information transmission efficiency for secure multiple-input multiple-output (MIMO) wireless powered communication networks (WPCNs). We aim to maximize the secrecy throughput of all users by jointly optimizing the DL/UL time allocation, the energy transmit covariance matrix of hybrid access point (AP), the information transmit beamforming matrix of users and the phase shifts of IRS in DL/UL, subject to constraints of energy/information transmit power at the hybrid AP/users and that of unit-modulus IRS phase shifts for DL/UL. To tackle the non-convex problem, we first transform the original problem into an equivalent form based on the mean-square error (MSE) method given time allocation, and then apply the alternating algorithm to update the optimization variables iteratively. Specifically, the energy covariance matrix and the information beamforming matrix are obtained based on the dual subgradient method. For the IRS phase shifts, we investigate two IRS beamforming reflection setups, namely different DL/UL IRS beamforming and identical DL/UL IRS beamforming. For the former case, the second-order cone programming technique and the Majorization-Minimization algorithm/element by element iterative algorithm are applied to obtain the DL and UL IRS phase shifts, respectively. For the latter case, the IRS phase shifts are obtained by the successive convex approximation technique. To further reduce the computational complexity of the single-user system, we derive the closed-form solutions of IRS phase shifts in each iteration for the two different reflection setups. Simulation results show that all the proposed algorithms can greatly improve the secrecy throughput compared to the conventional system without IRS.

International audience

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.

In this paper, we consider a two-user wireless powered communication network (WPCN) with user cooperation, which consists of a hybrid access point (H-AP) and two users with energy harvesting circuit. The H-AP transfers energy to users during downlink (DL) and the users transmit information during uplink (UL) utilizing the harvested energy. To enhance user fairness, a user cooperation protocol is employed in which a user near from the H-AP relays the message of the other user by partially using its allocated time and energy resources. We maximize the sum-rate in the considered network subject to a set of quality of service (QoS) requirements by jointly optimizing the time allocation for DL energy transfer and UL information transmission. A novel closed-form solution is derived for the optimization problem using convex optimization techniques.

In Internet of Things (IoT) systems, a number of sensor devices monitor the physical system states and exchange information with each other. The main limitation is that the IoT devices are generally energy constrained since those are powered with batteries. To address this energy problem, we consider a cooperative wireless-powered communication network (WPCN), which consists of three phases: 1) downlink (DL) energy transfer from a multi-antenna access point (AP); 2) data sharing among IoT devices; and 3) uplink (UL) information transfer from single-antenna IoT devices. Based on the shared data and the harvested energy, the single-antenna IoT devices in the neighborhood cooperate to form a virtual antenna array in order to transmit their information simultaneously to the multi-antenna AP using a multiple-input multiple-output (MIMO) technique in the UL information transfer phase. In this study, the transmit covariance matrices (i.e., beamforming vectors and the corresponding transmit power allocation) used for both DL energy transfer and UL information transfer are jointly designed to maximize the UL capacity based on the Lagrangian method. Furthermore, the time allocation for each phase is optimized based on a stochastic gradient method. In the numerical results, it is shown that our proposed beamforming scheme and the stochastic time allocation can achieve near-optimal performance.

Unlike the time-division duplexing (TDD) systems, the downlink (DL) and uplink (UL) channels are not reciprocal anymore in the case of frequency-division duplexing (FDD). However, some long-term parameters, e.g. the time delays and angles of arrival (AoAs) of the channel paths, still enjoy reciprocity. In this paper, by efficiently exploiting the aforementioned limited reciprocity, we address the DL channel state information (CSI) feedback in a practical wideband massive multiple-input multiple-output (MIMO) system operating in the FDD mode. In particular, the base station (BS) can transmit the FFT-based pilots with the carefully-selected phase shifts to align the DL paths. Then the user can rely on the so-called time-domain aggregate channel (TAC) to derive the estimate of the DL CSI. Next, with the knowledge about the second-order statistics of the DL channels, the user is also able to compute feedback of reduced dimensionality. We demonstrate that each user can just feed back one scalar number per DL channel path for the BS to recover the DL CSIs. Comprehensive numerical results corroborate our designs.

Trajectory design and resource allocation for UAV energy minimization in a rotary-wing UAV-enabled WPCN

In this paper, we study the uplink (UL) and downlink (DL) ergodic capacity in the bidirectional dynamic network (BDN). By dynamically allocating the numbers of UL and DL remote radio heads (RRHs), BDN facilitates simultaneous UL and DL communications to accommodate the data traffic asymmetry. Assuming that the number of antennas at each RRH (M) is large, we derive the closed-form expressions for the ergodic achievable rates in BDN systems, and the theoretical results are shown to be accurate compared with the Monte Carlo simulation results. Furthermore, we investigate the performance of the limiting UL and DL rates when M goes to infinity, and it indicates that we can scale down the UL and DL power per user proportionally to 1/M to guarantee a certain UL or DL quality of service in BDN. Numerical results indicate that there exists an optimal ratio between UL and DL RRH numbers for the maximal spectral efficiency in BDN. Thanks to our proposed RRH layout which guarantees the uniformity and symmetry in the whole network, we can find the optimal ratio between UL and DL RRH numbers more easily.