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

Abstract

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 multipleantenna 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.Index Terms-Energy-constrained IoT networks, when to activate WPT, energy beamforming, optimal resource allocation.

Comparing Backscatter Communication and Energy Harvesting in Massive IoT Networks

“…The secondary users are interested in taking advantage of the "ambient" energy of the RF signals carrying information to the primary users, not their content, using either BC or HTT (we consider both cases in this paper), which is why the network serves them only when the QoS of the primary users can be guaranteed while doing so. We assume that both the primary and secondary users have only one antenna (see also [19], [25], [27]). We make this assumption to simplify the model, and because of the low-power setting.…”

“…In general, η RF-DC (•) is a nonlinear function due to the diode non-linearity and the saturation behaviour [6]. However, in the literature [27][28][29], it is common to assume that it is linear, for the sake of analytical simplicity. As we will see later on in this paper, the problem is difficult to solve even when η RF-DC (•) is assumed to be linear.…”

Softwarization of UAV Networks: A Survey of Applications and Future Trends

“…The paradigm of energy harvesting is considered as the most appropriate technology to provide cost-effective and perpetual energy supplies for UAVs [322]. Recently, the radio frequency (RF) transmission has enabled the new concept of wireless power transfer (WPT) [323]. This concept has been applied in many UAV applications to provide controllable and sustainable energy supply for UAVs [324], [325].…”

Edge Learning with Unmanned Ground Vehicle: Joint Path, Energy and Sample Size Planning

“…For example, Qingqing et al [27] jointly optimized time allocation and power control for maximization of the weighted sum of the user energy efficiencies for wireless powered communications system. Following this, for the same system, Qingqing et al [28] maximized the weighted sum rate of the devices in the consideration of downlink and uplink time allocation and the power control at the devices. Bin et al [29] proposed a joint time scheduling and power allocation scheme to optimize the sum-rate for relay assisted batteryless IoT Networks.…”