Optimization and Analysis of Wireless Powered Multi-antenna Cooperative Systems

In this paper, we consider a three-node cooperative wireless powered communication system consisting of a multi-antenna hybrid access point (H-AP) and a single-antenna relay and a single-antenna user. The energy constrained relay and user first harvest energy in the downlink and then the relay assists the user using the harvested power for information transmission in the uplink. The optimal energy beamforming vector and the time split between harvest and cooperation are investigated. To reduce the computational complexity, suboptimal designs are also studied, where closed-form expressions are derived for the energy beamforming vector and the time split. For comparison purposes, we also present a detailed performance analysis in terms of the achievable outage probability and the average throughput of an intuitive energy beamforming scheme, where the H-AP directs all the energy towards the user. The findings of the paper suggest that implementing multiple antennas at the H-AP can significantly improve the system performance, and the closed-form suboptimal energy beamforming vector and time split yields near optimal performance. Also, for the intuitive beamforming scheme, a diversity order of (N+1)/2 can be achieved, where N is the number of antennas at the H-AP

Optimal Power Allocation for Energy Recycling Assisted Cooperative Communications

We investigate the problem of optimal power allocation for energy recycling cooperative communications systems, employing full duplex relays, based on the criterion of maximizing the rate, or equivalently the Signal to Noise Ratio (SNR), of the system. A system model is investigated where each time slot is split into an information transmission phase, during which the Source (S) transmits information to the destination (D) and a full-duplex Relay (R), and an energy harvesting phase. During the energy harvesting phase, R relays information to D, while concurrently it performs energy harvesting, exploiting a signal transmitted by S and energy recycling, exploiting its own transmission. For this system model, we formulate a rate/SNR maximization problem, in order to compute the optimal source power levels for both information transfer and energy transfer phases. The cost function of this optimization problem is then substituted by a sharp approximation, which allows for obtaining an analytically tractable power allocation. The performance of the resulting power allocation is then assessed by means of Monte Carlo simulations, and it is found that it outperforms existing solutions. It is therefore shown that our proposed solution can contribute towards increasing the range of IoT networks

Full-Duplex Wireless-Powered Relay with Self-Energy Recycling

This letter studies a wireless-powered amplify-and-forward relaying system, where an energy-constrained relay node assists the information transmission from the source to the destination using the energy harvested from the source. We propose a novel two-phase protocol for efficient energy transfer and information relaying, in which the relay operates in full-duplex mode with simultaneous energy harvesting and information transmission. Compared with the existing protocols, the proposed design possesses two main advantages: i) it ensures uninterrupted information transmission since no time switching or power splitting is needed at the relay for energy harvesting; ii) it enables the so-called self-energy recycling, i.e., part of the energy (loop energy) that is used for information transmission by the relay can be harvested and reused in addition to the dedicated energy sent by the source. Under the multiple-input single-output (MISO) channel setup, the optimal power allocation and beamforming design at the relay are derived. Numerical results show a significant throughput gain achieved by our proposed design over the existing time switching-based relay protocol.Comment: 10 pages, 5 figure

Secrecy Throughput Maximization for Full-Duplex Wireless Powered IoT Networks under Fairness Constraints

In this paper, we study the secrecy throughput of a full-duplex wireless powered communication network (WPCN) for internet of things (IoT). The WPCN consists of a full-duplex multi-antenna base station (BS) and a number of sensor nodes. The BS transmits energy all the time, and each node harvests energy prior to its transmission time slot. The nodes sequentially transmit their confidential information to the BS, and the other nodes are considered as potential eavesdroppers. We first formulate the sum secrecy throughput optimization problem of all the nodes. The optimization variables are the duration of the time slots and the BS beamforming vectors in different time slots. The problem is shown to be non-convex. To tackle the problem, we propose a suboptimal two stage approach, referred to as sum secrecy throughput maximization (SSTM). In the first stage, the BS focuses its beamforming to blind the potential eavesdroppers (other nodes) during information transmission time slots. Then, the optimal beamforming vector in the initial non-information transmission time slot and the optimal time slots are derived. We then consider fairness among the nodes and propose max-min fair (MMF) and proportional fair (PLF) algorithms. The MMF algorithm maximizes the minimum secrecy throughput of the nodes, while the PLF tries to achieve a good trade-off between the sum secrecy throughput and fairness among the nodes. Through numerical simulations, we first demonstrate the superior performance of the SSTM to uniform time slotting and beamforming in different settings. Then, we show the effectiveness of the proposed fair algorithms