Minimum Throughput Maximization in UAV-Aided Wireless Powered Communication Networks

This paper investigates unmanned aerial vehicle (UAV)-aided wireless powered communication network (WPCN) systems where a mobile access point (AP) at the UAV serves multiple energy-constrained ground terminals (GTs). Specifically, the UAVs first charge the GTs by transmitting the wireless energy transfer (WET) signals in the downlink. Then, by utilizing the harvested wireless energy from the UAVs, the GTs send their uplink wireless information transmission (WIT) signals to the UAVs. In this paper, depending on the operations of the UAVs, we adopt two different scenarios, namely integrated UAV and separated UAV WPCNs. First, in the integrated UAV WPCN, a UAV acts as a hybrid AP in which both energy transfer and information reception are processed at a single UAV. In contrast, for the separated UAV WPCN, we consider two UAVs each of which behaves as an energy AP and an information AP independently, and thus the energy transfer and the information decoding are separately performed at two different UAVs. For both systems, we jointly optimize the trajectories of the UAVs, the uplink power control, and the time resource allocation for the WET and the WIT to maximize the minimum throughput of the GTs. Since the formulated problems are non-convex, we apply the concave-convex procedure by deriving appropriate convex bounds for non-convex constraints. As a result, we propose iterative algorithms which efficiently identify a local optimal solution for the minimum throughput maximization problems. Simulation results verify the efficiency of the proposed algorithms compared to conventional schemes.Comment: 22 pages, 7 figure

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

Full-Duplex Wireless-Powered Communication Network with Energy Causality

In this paper, we consider a wireless communication network with a full-duplex hybrid access point (HAP) and a set of wireless users with energy harvesting capabilities. The HAP implements the full-duplex through two antennas: one for broadcasting wireless energy to users in the downlink and one for receiving independent information from users via time-division-multiple-access (TDMA) in the uplink at the same time. All users can continuously harvest wireless power from the HAP until its transmission slot, i.e., the energy causality constraint is modeled by assuming that energy harvested in the future cannot be used for tranmission. Hence, latter users' energy harvesting time is coupled with the transmission time of previous users. Under this setup, we investigate the sum-throughput maximization (STM) problem and the total-time minimization (TTM) problem for the proposed multi-user full-duplex wireless-powered network. The STM problem is proved to be a convex optimization problem. The optimal solution strategy is then obtained in closed-form expression, which can be computed with linear complexity. It is also shown that the sum throughput is non-decreasing with increasing of the number of users. For the TTM problem, by exploiting the properties of the coupling constraints, we propose a two-step algorithm to obtain an optimal solution. Then, for each problem, two suboptimal solutions are proposed and investigated. Finally, the effect of user scheduling on STM and TTM are investigated through simulations. It is also shown that different user scheduling strategies should be used for STM and TTM.Comment: Energy Harvesting, Wireless Power Transfer, Full-Duplex, Optimal Resource Allocation, Optimizatio

Multiuser Scheduling for Simultaneous Wireless Information and Power Transfer Systems

In this thesis, we study the downlink multiuser scheduling and power allocation problem for systems with simultaneous wireless information and power transfer (SWIPT). In the first part of the thesis, we focus on multiuser scheduling. We design optimal scheduling algorithms that maximize the long-term average system throughput under different fairness requirements, such as proportional fairness and equal throughput fairness. In particular, the algorithm designs are formulated as non-convex optimization problems which take into account the minimum required average sum harvested energy in the system. The problems are solved by using convex optimization techniques and the proposed optimization framework reveals the tradeoff between the long-term average system throughput and the sum harvested energy in multiuser systems with fairness constraints. Simulation results demonstrate that substantial performance gains can be achieved by the proposed optimization framework compared to existing suboptimal scheduling algorithms from the literature. In the second part of the thesis, we investigate the joint user scheduling and power allocation algorithm design for SWIPT systems. The algorithm design is formulated as a non-convex optimization problem which maximizes the achievable rate subject to a minimum required average power transfer. Subsequently, the non-convex optimization problem is reformulated by big-M method which can be solved optimally. Furthermore, we show that joint power allocation and user scheduling is an efficient way to enlarge the feasible trade-off region for improving the system performance in terms of achievable data rate and harvested energy.Comment: Master Thesis, Institute for Digital Communications, Friedrich-Alexander-Universit\"at Erlangen-N\"urnberg, Germany http://www.idc.lnt.de/en

Group Cooperation with Optimal Resource Allocation in Wireless Powered Communication Networks

This paper considers a wireless powered communication network (WPCN) with group cooperation, where two communication groups cooperate with each other via wireless power transfer and time sharing to fulfill their expected information delivering and achieve "win-win" collaboration. To explore the system performance limits, we formulate optimization problems to respectively maximize the weighted sum-rate and minimize the total consumed power. The time assignment, beamforming vector and power allocation are jointly optimized under available power and quality of service requirement constraints of both groups. For the WSR-maximization, both fixed and flexible power scenarios are investigated. As all problems are non-convex and have no known solution methods, we solve them by using proper variable substitutions and the semi-definite relaxation. We theoretically prove that our proposed solution method guarantees the global optimum for each problem. Numerical results are presented to show the system performance behaviors, which provide some useful insights for future WPCN design. It shows that in such a group cooperation-aware WPCN, optimal time assignment has the greatest effect on the system performance than other factors.Comment: 13 pages, 14 figures, to appear in IEEE Transactions on Wireless Communications Information Theory (cs.IT

Resource Allocation for Secure Communications in Cooperative Cognitive Wireless Powered Communication Networks

We consider a cognitive wireless powered communication network (CWPCN) sharing the spectrum with a primary network who faces security threats from eavesdroppers (EAVs). We propose a new cooperative protocol for the wireless powered secondary users (SU) to cooperate with the primary user (PU). In the protocol, the SUs first harvest energy from the power signals transmitted by the cognitive hybrid access point during the wireless power transfer (WPT) phase, and then use the harvested energy to interfere with the EAVs and gain transmission opportunities at the same time during the wireless information transfer (WIT) phase. Taking the maximization of the SU ergodic rate as the design objective, resource allocation algorithms based on the dual optimization method and the block coordinate descent method are proposed for the cases of perfect channel state information (CSI) and collusive/non-collusive EAVs under the PU secrecy constraint. More PU favorable greedy algorithms aimed at minimizing the PU secrecy outage probability are also proposed. We furthermore consider the unknown EAVs' CSI case and propose an efficient algorithm to improve the PU security performance. Extensive simulations show that our proposed protocol and corresponding resource allocation algorithms can not only let the SU gain transmission opportunities but also improve the PU security performance even with unknown EAVs' CSI.Comment: Submitted to IEEE Systems Journal for possible publicatio

Power-Efficient and Secure WPCNs with Hardware Impairments and Non-Linear EH Circuit

In this paper, we design a robust resource allocation algorithm for a wireless-powered communication network (WPCN) taking into account residual hardware impairments (HWIs) at the transceivers, the imperfectness of the channel state information, and the non-linearity of practical radio frequency energy harvesting circuits. In order to ensure power-efficient secure communication, physical layer security techniques are exploited to deliberately degrade the channel quality of a multiple-antenna eavesdropper. The resource allocation algorithm design is formulated as a non-convex optimization problem for minimization of the total consumed power in the network, while guaranteeing the quality of service of the information receivers in terms of secrecy rate. The globally optimal solution of the optimization problem is obtained via a two-dimensional search and semidefinite programming relaxation. To strike a balance between computational complexity and system performance, a low-complexity iterative suboptimal resource allocation algorithm is then proposed. Numerical results demonstrate that both the proposed optimal and suboptimal schemes can significantly reduce the total system power consumption required for guaranteeing secure communication, and unveil the impact of HWIs on the system performance: (1) residual HWIs create a system performance bottleneck in the high transmit/receive power regimes; (2) increasing the number of transmit antennas can effectively reduce the system power consumption and alleviate the performance degradation due to residual HWIs; (3) imperfect CSI increases the system power consumption and exacerbates the impact of residual HWIs.Comment: Submitted for possible journal publicatio

Energy-Efficient Resource Allocation for Wireless Powered Communication Networks

This paper considers a wireless powered communication network (WPCN), where multiple users harvest energy from a dedicated power station and then communicate with an information receiving station. Our goal is to investigate the maximum achievable energy efficiency (EE) of the network via joint time allocation and power control while taking into account the initial battery energy of each user. We first study the EE maximization problem in the WPCN without any system throughput requirement. We show that the EE maximization problem for the WPCN can be cast into EE maximization problems for two simplified networks via exploiting its special structure. For each problem, we derive the optimal solution and provide the corresponding physical interpretation, despite the non-convexity of the problems. Subsequently, we study the EE maximization problem under a minimum system throughput constraint. Exploiting fractional programming theory, we transform the resulting non-convex problem into a standard convex optimization problem. This allows us to characterize the optimal solution structure of joint time allocation and power control and to derive an efficient iterative algorithm for obtaining the optimal solution. Simulation results verify our theoretical findings and demonstrate the effectiveness of the proposed joint time and power optimization.Comment: Transactions on Wireless Communication

Wireless Powered Cooperative Jamming for Secure OFDM System

This paper studies the secrecy communication in an orthogonal frequency division multiplexing (OFDM) system, where a source sends confidential information to a destination in the presence of a potential eavesdropper. We employ wireless powered cooperative jamming to improve the secrecy rate of this system with the assistance of a cooperative jammer, which works in the harvest-then-jam protocol over two time-slots. In the first slot, the source sends dedicated energy signals to power the jammer; in the second slot, the jammer uses the harvested energy to jam the eavesdropper, in order to protect the simultaneous secrecy communication from the source to the destination. In particular, we consider two types of receivers at the destination, namely Type-I and Type-II receivers, which do not have and have the capability of canceling the (a-priori known) jamming signals, respectively. For both types of receivers, we maximize the secrecy rate at the destination by jointly optimizing the transmit power allocation at the source and the jammer over sub-carriers, as well as the time allocation between the two time-slots. First, we present the globally optimal solution to this problem via the Lagrange dual method, which, however, is of high implementation complexity. Next, to balance tradeoff between the algorithm complexity and performance, we propose alternative low-complexity solutions based on minorization maximization and heuristic successive optimization, respectively. Simulation results show that the proposed approaches significantly improve the secrecy rate, as compared to benchmark schemes without joint power and time allocation.Comment: This paper is submitted for possible journal publicatio

NOMA-based Energy-Efficient Wireless Powered Communications

In this paper, we study the performance of non-orthogonal multiple access (NOMA) schemes in wireless powered communication networks (WPCN) focusing on the system energy efficiency (EE). We consider multiple energy harvesting user equipments (UEs) that operate based on harvest-then-transmit protocol. The uplink information transfer is carried out by using power-domain multiplexing, and the receiver decodes each UE's data in such a way that the UE with the best channel gain is decoded without interference. In order to determine optimal resource allocation strategies, we formulate optimization problems considering two models, namely half-duplex and asynchronous transmission, based on how downlink and uplink operations are coordinated. In both cases, we have concave-linear fractional problems, and hence Dinkelbach's method can be applied to obtain the globally optimal solutions. Thus, we first derive analytical expressions for the harvesting interval, and then we provide an algorithm to describe the complete procedure. Furthermore, we incorporate delay-limited sources and investigate the impact of statistical queuing constraints on the energy-efficient allocation of operating intervals. We formulate an optimization problem that maximizes the system effective-EE while UEs are applying NOMA scheme for uplink information transfer. Since the problem satisfies pseudo-concavity, we provide an iterative algorithm using bisection method to determine the unique solution. In the numerical results, we observe that broadcasting at higher power level is more energy efficient for WPCN with uplink NOMA. Additionally, exponential decay QoS parameter has considerable impact on the optimal solution, and in the presence of strict constraints, more time is allocated for downlink interval under half-duplex operation with uplink TDMA mode.Comment: 31 pages, 12 figures, to appear on IEEE Transactions on Green Communications and Networkin