On Optimal Policies in Full-Duplex Wireless Powered Communication Networks

The optimal resource allocation scheme in a full-duplex Wireless Powered Communication Network (WPCN) composed of one Access Point (AP) and two wireless devices is analyzed and derived. AP operates in a full-duplex mode and is able to broadcast wireless energy signals in downlink and receive information data in uplink simultaneously. On the other hand, each wireless device is assumed to be equipped with Radio-Frequency (RF) energy harvesting circuitry which gathers the energy sent by AP and stores it in a finite capacity battery. The harvested energy is then used for performing uplink data transmission tasks. In the literature, the main focus so far has been on slot-oriented optimization. In this context, all the harvested RF energy in a given slot is also consumed in the same slot. However, this approach leads to sub-optimal solutions because it does not take into account the Channel State Information (CSI) variations over future slots. Differently from most of the prior works, in this paper we focus on the long-term weighted throughput maximization problem. This approach significantly increases the complexity of the optimization problem since it requires to consider both CSI variations over future slots and the evolution of the batteries when deciding the optimal resource allocation. We formulate the problem using the Markov Decision Process (MDP) theory and show how to solve it. Our numerical results emphasize the superiority of our proposed full-duplex WPCN compared to the half-duplex WPCN and reveal interesting insights about the effects of perfect as well as imperfect self-interference cancellation techniques on the network performance.Comment: Proc. IEEE Symp. Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), May 201

Placement Optimization of Energy and Information Access Points in Wireless Powered Communication Networks

The applications of wireless power transfer technology to wireless communications can help build a wireless powered communication network (WPCN) with more reliable and sustainable power supply compared to the conventional battery-powered network. However, due to the fundamental differences in wireless information and power transmissions, many important aspects of conventional battery-powered wireless communication networks need to be redesigned for efficient operations of WPCNs. In this paper, we study the placement optimization of energy and information access points in WPCNs, where the wireless devices (WDs) harvest the radio frequency energy transferred by dedicated energy nodes (ENs) in the downlink, and use the harvested energy to transmit data to information access points (APs) in the uplink. In particular, we are interested in minimizing the network deployment cost with minimum number of ENs and APs by optimizing their locations, while satisfying the energy harvesting and communication performance requirements of the WDs. Specifically, we first study the minimum-cost placement problem when the ENs and APs are separately located, where an alternating optimization method is proposed to jointly optimize the locations of ENs and APs. Then, we study the placement optimization when each pair of EN and AP are co-located and integrated as a hybrid access point, and propose an efficient algorithm to solve this problem. Simulation results show that the proposed methods can effectively reduce the network deployment cost and yet guarantee the given performance requirements, which is a key consideration in the future applications of WPCNs.Comment: This paper is accepted and to appear in IEEE Transactions on Wireless Communication

Generalized Wireless-Powered Communications: When to Activate Wireless Power Transfer?

Wireless-powered communication network (WPCN) is a key technology to power energy-limited massive devices, such as on-board wireless sensors in autonomous vehicles, for Internet-of-Things (IoT) applications. Conventional WPCNs rely only on dedicated downlink wireless power transfer (WPT), which is practically inefficient due to the significant energy loss in wireless signal propagation. Meanwhile, ambient energy harvesting is highly appealing as devices can scavenge energy from various existing energy sources (e.g., solar energy and cellular signals). Unfortunately, the randomness of the availability of these energy sources cannot guarantee stable communication services. Motivated by the above, we consider a generalized WPCN where the devices can not only harvest energy from a dedicated multiple-antenna power station (PS), but can also exploit stored energy stemming from ambient energy harvesting. Since the dedicated WPT consumes system resources, if the stored energy is sufficient, WPT may not be needed to maximize the weighted sum rate (WSR). To analytically characterize this phenomenon, we derive the condition for WPT activation and reveal how it is affected by the different system parameters. Subsequently, we further derive the optimal resource allocation policy for the cases that WPT is activated and deactivated, respectively. In particular, it is found that when WPT is activated, the optimal energy beamforming at the PS does not depend on the devices' stored energy, which is shown to lead to a new unfairness issue. Simulation results verify our theoretical findings and demonstrate the effectiveness of the proposed optimal resource allocation.Comment: TV

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

Optimizing Throughput Fairness of Cluster-based Cooperation in Underlay Cognitive WPCNs

In this paper, we consider a secondary wireless powered communication network (WPCN) underlaid to a primary point-to-point communication link. The WPCN consists of a multi-antenna hybrid access point (HAP) that transfers wireless energy to a cluster of low-power wireless devices (WDs) and receives sensing data from them. To tackle the inherent severe user unfairness problem in WPCN, we consider a cluster-based cooperation where a WD acts as the cluster head that relays the information of the other WDs. Besides, we apply energy beamforming technique to balance the dissimilar energy consumptions of the WDs to further improve the fairness. However, the use of energy beamforming and cluster-based cooperation may introduce more severe interference to the primary system than the WDs transmit independently. To guarantee the performance of primary system, we consider an interference-temperature constraint to the primary system and derive the throughput performance of each WD under the peak interference-temperature constraint. To achieve maximum throughput fairness, we jointly optimize the energy beamforming design, the transmit time allocation among the HAP and the WDs, and the transmit power allocation of each WD to maximize the minimum data rate achievable among the WDs (the max-min throughput). We show that the non-convex joint optimization problem can be transformed to a convex one and then be efficiently solved using off-the-shelf convex algorithms. Moreover, we simulate under practical network setups and show that the proposed method can effectively improve the throughput fairness of the secondary WPCN, meanwhile guaranteeing the communication quality of the primary network.Comment: The paper has been submitted for potential journal publication. arXiv admin note: text overlap with arXiv:1707.0320

Traffic-Aware Backscatter Communications in Wireless-Powered Heterogeneous Networks

With the emerging Internet-of-Things services, massive machine-to-machine (M2M) communication will be deployed on top of human-to-human (H2H) communication in the near future. Due to the coexistence of M2M and H2H communications, the performance of M2M (i.e., secondary) network depends largely on the H2H (i.e., primary) network. In this paper, we propose ambient backscatter communication for the M2M network which exploits the energy (signal) sources of the H2H network, referring to traffic applications and popularity. In order to maximize the harvesting and transmission opportunities offered by varying traffic sources of the H2H network, we adopt a Bayesian nonparametric (BNP) learning algorithm to classify traffic applications (patterns) for secondary user (SU). We then analyze the performance of SU using the stochastic geometrical approach, based on a criterion for optimal traffic pattern selection. Results are presented to validate the performance of the proposed BNP classification algorithm and the criterion, as well as the impact of traffic sources and popularity.Comment: 14 pages, 10 figure

A Discrete Time-Switching Protocol for Wireless-Powered Communications with Energy Accumulation

This paper investigates a wireless-powered communication network (WPCN) setup with one multi-antenna access point (AP) and one single-antenna source. It is assumed that the AP is connected to an external power supply, while the source does not have an embedded energy supply. But the source could harvest energy from radio frequency (RF) signals sent by the AP and store it for future information transmission. We develop a discrete time-switching (DTS) protocol for the considered WPCN. In the proposed protocol, either energy harvesting (EH) or information transmission (IT) operation is performed during each transmission block. Specifically, based on the channel state information (CSI) between source and AP, the source can determine the minimum energy required for an outage-free IT operation. If the residual energy of the source is sufficient, the source will start the IT phase. Otherwise, EH phase is invoked and the source accumulates the harvested energy. To characterize the performance of the proposed protocol, we adopt a discrete Markov chain (MC) to model the energy accumulation process at the source battery. A closed-form expression for the average throughput of the DTS protocol is derived. Numerical results validate our theoretical analysis and show that the proposed DTS protocol considerably outperforms the existing harvest-then-transmit protocol when the battery capacity at the source is large.Comment: Presented at Globecom'1

Capacity of a Full-Duplex Wirelessly Powered Communication System with Self-Interference and Processing Cost

In this paper, we investigate the capacity of a point-to-point, full-duplex (FD), wirelessly powered communication system impaired by self-interference. This system is comprised of an energy transmitter (ET) and an energy harvesting user (EHU), both operating in a FD mode. The ET transmits energy towards the EHU. The EHU harvests this energy and uses it to transmit information back to the ET. As a result of the FD mode, both nodes are affected by self-interference. The self-interference has a different effect at the two nodes: it impairs the decoding of the received signal at the ET, however, it provides an additional source of energy for the EHU. This paper derives the capacity of this communication system assuming a processing cost at the EHU and additive white Gaussian noise channel with block fading. Thereby, we show that the capacity achieving scheme is relatively simple and therefore applicable to devices with limited resources. Moreover, our numerical results show significant improvements in terms of data rate when the capacity achieving strategy is employed compared to half-duplex transmission. Moreover, we show the positive and negative effects of the self-interference at the EHU and the ET, respectively. Furthermore, we show the crippling effect of the processing cost and demonstrate that failing to take it into consideration gives a false impression in terms of achievable rate

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

Towards Optimal Resource Allocation in Wireless Powered Communication Networks with Non-Orthogonal Multiple Access

The optimal allocation of time and energy resources is characterized in a Wireless Powered Communication Network (WPCN) with non-Orthogonal Multiple Access (NOMA). We consider two different formulations; in the first one (max-sum), the sum-throughput of all users is maximized. In the second one (max-min), and targeting fairness among users, we consider maximizing the min-throughput of all users. Under the above two formulations, two NOMA decoding schemes are studied, namely, low complexity decoding (LCD) and successive interference cancellation decoding (SICD). Due to the non-convexity of three of the studied optimization problems, we consider an approximation approach, in which the non-convex optimization problem is approximated by a convex optimization problem, which satisfies all the constraints of the original problem. The approximated convex optimization problem can then be solved iteratively. The results show a trade-off between maximizing the sum throughout and achieving fairness through maximizing the minimum throughput