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We consider wireless-powered amplify-and-forward and decode-and-forward relaying in cooperative communications, where an energy constrained relay node first harvests energy through the received radio-frequency signal from the source and then uses the harvested energy to forward the source information to the destination node. We propose time-switching based energy harvesting (EH) and information transmission (IT) protocols with two modes of EH at the relay. For continuous time EH, the EH time can be any percentage of the total transmission block time. For discrete time EH, the whole transmission block is either used for EH or IT. The proposed protocols are attractive because they do not require channel state information at the transmitter side and enable relay transmission with preset fixed transmission power. We derive analytical expressions of the achievable throughput for the proposed protocols. The derived expressions are verified by comparison with simulations and allow the system performance to be determined as a function of the system parameters. Finally, we show that the proposed protocols outperform the existing fixed time duration EH protocols in the literature, since they intelligently track the level of the harvested energy to switch between EH and IT in an online fashion, allowing efficient use of resources.Radio frequency (RF) or wireless energy harvesting has recently emerged as an attractive solution to power nodes in future wireless networks [2]- [6]. Wireless energy harvesting techniques are now evolving from theoretical concepts into practical devices for low-power electronic applications [7]. The feasibility of wireless energy harvesting for low-power cellular applications has been studied using experimental results, which have been summarised in [2]. With wireless energy harvesting, there is a choice between harvesting energy from ambient sources or by carefully designing wireless power transfer links. For instance, a power density of around 1 mW/m 2 is reported around 50 meter distance from the base station in the GSM band (935 MHz -960 MHz) [4], which means that a wireless device with a typical size of around 100 cm 2 can harvest power in the range of tens of µW. Such an amount of harvested power could be sufficient for relaying nodes in sensor networks with sporadic activities. For devices that need to support frequent communication activities, harvesting ambient RF energy is not sufficient. Instead, harvesting wireless energy from carefully designed power transfer links is needed. In addition, the energy conversion efficiency of the wireless energy harvesting plays an important role in determining the amount of energy that can be harvested. Employing different circuit design technologies, wireless energy harvesting with energy conversion efficiency in the range of 10%-80% has been reported over a wide range of frequencies, e.g., 15 MHz -2.5 GHz [2], [8]. More specifically, energy conversion efficiency of around 65% has been reported in the ISM band (900 MHz, 2.4 GHz) with 13 nm CMOS techno...

In this paper, we consider a decode-and-forward (DF) relaying network based on wireless energy harvesting. The energy constrained relay node first harvests energy through radio-frequency (RF) signals from the source node. Next, the relay node uses the harvested energy to forward the decoded source information to the destination node. The source node transfers energy and information to the relay node through two mechanisms, i) time switching-based relaying (TSR) and ii) power splitting-based relaying (PSR). Considering wireless energy harvesting constraint at the relay node, we derive the exact analytical expressions of the achievable throughput and ergodic capacity of a DF relaying network for both TSR and PSR schemes. Through numerical analysis, we study the throughput performance of the overall system for different system parameters, such as energy harvesting time, power splitting ratio, and signal-tonoise-ratio (SNR). In particular, the throughput performance of the PSR scheme outperforms the throughput performance of the TSR scheme for a wide range of SNRs.

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Unmanned aerial vehicles (UAVs) can be deployed as flying base stations (BSs) to leverage the strength of line-of-sight connections and effectively support the coverage and throughput of wireless communication.This paper considers a multiuser communication system, in which a single-antenna UAV-BS serves a large number of ground users by employing non-orthogonal multiple access (NOMA). The max-min rate optimization problem is formulated under total power, total bandwidth, UAV altitude, and antenna beamwdith constraints. The objective of max-min rate optimization is non-convex in all optimization variables, i.e. UAV altitude, transmit antenna beamwidth, power allocation and bandwidth allocation for multiple users. A pathfollowing algorithm is proposed to solve the formulated problem. Next, orthogonal multiple access (OMA) and dirty paper coding (DPC)-based max-min rate optimization problems are formulated and respective pathfollowing algorithms are developed to solve them. Numerical results show that NOMA outperforms OMA and achieves rates similar to those attained by DPC. In addition, a clear rate gain is observed by jointly optimizing all the parameters rather than optimizing a subset of parameters, which confirms the desirability of their joint optimization. Index TermsA. A. Nasir is with the 2 Unmanned aerial vehicle (UAV), non-orthogonal multiple access (NOMA), orthogonal multiple access (OMA), dirty paper coding (DPC), non-convex optimization, throughput. I. INTRODUCTION Unmanned aerial vehicles (UAVs) can assist normal communication networks by acting as flying base stations (UAV-BSs) and taking care of traffic demand in exceptional situations, e.g., sports events, concerts, disaster position, military situations, traffic congestion, etc. [1]-[6]. UAVs can also function as temporary hotspots or relay nodes for connections between the safe area and disaster areas [7]-[9]. Ground users served by the UAV-BSs can expect line-of-sight (LoS) air-to-ground communication. Thus, UAV-enabled communication can be efficient in supporting the coverage and throughput of wireless communications [10], [11]. UAV-enabled communication networks have recently gained significant interests and are actively investigated in open literature. Thanks to the flexibility of UAV deployment, the coverage area, throughput, and energy efficiency of UAV-enabled communication can be improved by UAV placement [12]-[14], beamwidth control [15], [16], and power allocation [1], [17], [18].Unlike conventional cellular communication, which operates in a rich scattering environment that supports multi-antenna array transmission for spatial diversity, UAV-enabled downlink communication exhibits much poorer scattering and as such a single-antenna UAV is most desired. To be served by the same UAV over the same time, multiple users must share the communication bandwidth.Usually each user is assigned an individual bandwidth channel so its achievable rate is very sensitive to the number of users sharing the same bandwidth. Naturally one may think to assig...

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Considering a multicell network for secure wireless information and power transfer, this paper studies the joint design of transmit beamformers at the base stations (BSs) and receive signal splitting ratios at the end users' equipment (UEs). The primary concern in this work is the network internal security, where there may be a single multi-antenna eavesdropper or there is a risk that any near user may accidentally eavesdrop on the received signal of any far user. The objective is to maximize the minimum secrecy user rate under BS transmit power and UE minimum harvested energy constraints. New pathfollowing algorithms are proposed for computational solutions of these difficult nonconvex optimization problems. Each iteration involves one simple convex quadratic program (QP). Numerical results confirm that the proposed algorithms converge quickly after few iterations having low computational complexity.

Oscillator phase noise (PHN) and carrier frequency offset (CFO) can adversely impact the performance of orthogonal frequency division multiplexing (OFDM) systems, since they can result in inter carrier interference and rotation of the signal constellation. In this paper, we propose an expectation conditional maximization (ECM) based algorithm for joint estimation of channel, PHN, and CFO in OFDM systems. We present the signal model for the estimation problem and derive the hybrid Cramér-Rao lower bound (HCRB) for the joint estimation problem. Next, we propose an iterative receiver based on an extended Kalman filter for joint data detection and PHN tracking.Numerical results show that, compared to existing algorithms, the performance of the proposed ECM-based estimator is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high signal-to-noise ratio (SNR). In addition, the combined estimation algorithm and iterative receiver are more computationally efficient than existing algorithms and result in improved average uncoded and coded bit error rate (BER) performance.