Due to their ﬂexibility and low cost deployment, unmanned aerial vehicles (UAV) will most likely act as base stations and backhaul relays in the next generation of wireless communication systems. However, these UAVs—in the untethered mode—can only operate for a ﬁnite time due to limited energy they carry in their batteries. In free-space optical communications, one solution is to transport both the data and the energy from the source to the UAV through the laser beam—a concept known as simultaneous lightwave information and power transfer (SLIPT). In this study, we have analyzed the SLIPT scheme for laser-powered decode-and-forward UAV relays in an optical wireless backhaul. The major goal of this study is to optimally allocate the received beam energy between the decoding circuit, the transmitting circuit and the rotor block of the relay in order to maximize a quality-of-service metric such as maximum achievable rate, outage or error probabilities. As expected, we note that the optimal power allocation depends heavily on the source-relay and relay-destination channel conditions. In the ﬁnal part of this study, we have maximized the operational time of the UAV relay given that the maximum achievable rate stays above a certain threshold in order to meet a minimum quality-of-service requirement. Index Terms Decode-and-forward relay, energy harvesting, error probability, free-space optics, hovering unmanned aerial vehicle, laser-powered unmanned aerial vehicle, maximum achievable rate, optimal power allocation, outage prob- ability, simultaneous lightwave information and power transfer I. I/n.sc/t.sc/r.sc/o.sc/d.sc/u.sc/c.sc/t.sc/i.sc/o.sc/n.sc Free-space optics—or free-space laser communications—is slated to be a promising technology for the support of higher data rates in the backhaul of next generation of wireless communication systems. One 2 of the major advantages of laser communications is the availability of large bands in the optical domain of the electromagnetic spectrum that can help achieve transmission rates in tens of of Gigabits per second. Another advantage of FSO is the realization of low-cost and small-sized noncoherent energy detecting receivers that may be easily mounted on a small aerial platform such as a UAV. It is expected that UAVs will play an important role in the future generation of wireless communications [1] just as they are set to revolutionize almost all the aspects of a modern human society: from smart package delivery and traﬃc monitoring to surveillance and security applications to name a few. One of the major applications of UAVs in a wireless communication architecture will be the replacement of traditional base stations—which are ﬁxed on the ground and therefore stationary—with ﬂying aerial vehicles that will oﬀer much more ﬂexibility to a system designer in terms of maximizing a certain quality-of-service metric (maximum achievable rate, bit error rate) of the communication system [2]. Such UAVs will also ﬁnd applications as hovering relays in the backhaul of a future communication system due to their relative ease and quick deployment in a dense urban environment [3]. One of the major hurdles in the extensive deployment of UAVs for wireless communications is the limited amount of energy that is stored on an on-board battery. Thus, once the stored energy is exhausted, the communication link faces a disruption because the UAV has to alight on the ground charging station to recharge the battery. This problem may be resolved by two possible solutions: i) either by using a tether cable that acts both as a stabilizing force as well as a source of energy [4] to power the UAV, or, ii) by employing beam-powered scheme (commonly known as Simultaneous Wireless Information and Power Transferor SWIPT for short) in which the radio or laser beam is used both for data transmission as well as for supplying power to the UAV battery [5]. Even though the tethered scheme provides a continuous source of power supply, it limits the region of operation or the coverage area of the UAV. The SWIPT scheme allows far more ﬂexibility in this regard; however, if the supplied laser power is not enough, the UAV may still experience some downtime that will limit the uninterrupted operational time of the UAV. A. Motivation for Current Study In this paper, we have analyzed the energy optimization problem for a laser-powered hovering UAV decode-and-forward (DF) relay in a dual-hop communications link. The laser-powered scheme uses the same beam for data transmission as well as for energy supply to the UAV, and is commonly known as simultaneous lightwave information and power transfer scheme—or SLIPT for short—in literature. In the context of SLIPT and DF relays, an important problem is the optimal allocation of the received energy 3 between the following three channels in the relay with the aim to optimize a certain quality-of-service metric of the system: i) energy used for symbol decoding at the relay, ii) energy required for symbol transmission to the destination or the next relay, and iii) the energy needed to power the rotors. For instance, if one allocates too much energy for symbol decoding at the relay, then a small fraction of the remaining energy is allocated for symbol transmission to the destination or for rotor power. This will likely deteriorate the error rate or the data rate performance at the destination and will also reduce the uptime of the UAV. Hence, an optimal allocation of energy between all three channels at the relay is needed in order to maximize the overall system performance. II. B/a.sc/c.sc/k.sc/g.sc/r.sc/o.sc/u.sc/n.sc/d.sc L/i.sc/t.sc/e.sc/r.sc/a.sc/t.sc/u.sc/r.sc/e.sc R/e.sc/v.sc/i.sc/e.sc/w.sc /a.sc/n.sc/d.sc C/o.sc/n.sc/t.sc/r.sc/i.sc/b.sc/u.sc/t.sc/i.sc/o.sc/n.sc/s.sc /o.sc/f.sc C/u.sc/r.sc/r.sc/e.sc/n.sc/t.sc S/t.sc/u.sc/d.sc/y.sc Sixth generation and beyond communication networks envisage a world where the number of mobile communication devices will far exceed the number of ﬁxed or stationary terminals. Therefore, energy harvesting for mobile devices constitutes one of the major areas of research on future networks, and in this regard, the ideas behind SWIPT and SLIPT have garnered tremendous interest in the last few years. An important, high-level, paper on SWIPT is [5] wherein the authors lay out a concise introduction and discuss preliminary ideas on the technology behind SWIPT. An important article on SLIPT—which is actually the basis of study in this paper—is [6] in which the authors discuss the optimization problems concerning the SLIPT scheme for airborne radio access networks. In their work, the energy allocation for a UAV-based access network is optimized in order to maximize the individual achievable rates and the sum rate of spectrum users. The same authors in [7] apply SLIPT in order to maximize system performance for indoor internet-of-things applications. They solve a fundamental optimization problem in which the harvested energy is maximized under the constraint that the Quality of Service does not go below a certain threshold. Speciﬁcally in the domain of indoor visible light communications (VLC), the study [8] focuses on receiver design in the domains of time and signal components and photoelectric converters. The same study also applies SLIPT to various network topologies and communication technologies such as multiple-input multiple-out and hybrid radio-VLC frequency communications. Another paper that applies SLIPT to visible light communications is [9] in which the authors investigate the downlink unicast signal transmission of multi-LED multi-user SLIPT networks. In their paper, they study the total transmit power minimizationproblemunderthetheconstraintsofachievableraterequirement,minimumenergyharvesting and dimming control requirements. Finally, another study that applies SLIPT to VLC systems is [10] in 4 which the authors optimize the energy harvesting and data rate performance of multiple users under lighting constraints. Now we discuss some