1,474 publications from this institution
Radiative wireless power transfer (WPT) is a promising technology to provide cost-effective and real-time power supplies to wireless devices. Although radiative WPT shares many similar characteristics with the extensively studied wireless information transfer or communication, they also differ significantly in terms of design objectives, transmitter/receiver architectures and hardware constraints, and so on. In this paper, we first give an overview on the various WPT technologies, the historical development of the radiative WPT technology and the main challenges in designing contemporary radiative WPT systems. Then, we focus on the state-of-the-art communication and signal processing techniques that can be applied to tackle these challenges. Topics discussed include energy harvester modeling, energy beamforming for WPT, channel acquisition, power region characterization in multi-user WPT, waveform design with linear and non-linear energy receiver model, safety and health issues of WPT, massive multiple-input multiple-output and millimeter wave enabled WPT, wireless charging control, and wireless power and communication systems co-design. We also point out directions that are promising for future research.
WiFi offloading helps serve ever-increasing data traffic in cellular networks and mitigate the network congestion. Yet it can only apply to cellular users within WiFi coverage. Recently, delayed WiFi offloading is proposed to exploit users' mobility to purposely travel to WiFi coverage for data offloading. Its successful implementation depends on users' willingness to delay ongoing cellular data services until entering WiFi coverage. This paper proposes an incentive mechanism to allow a network operator to optimally reward his users to participate in delayed WiFi offloading, so as to reduce the network congestion. We formulate the design problem as a two-stage Stackelberg game: in Stage I, the operator announces a uniform reward to users to delay their existing cellular services; and in Stage II, each user decides to join the delayed offloading or not, depending on the reward, the network congestion, and his estimation of waiting cost for WiFi connection. The operator and users may or may not know all users' mobility and waiting cost information; thus, we propose optimal reward mechanisms under various information availability scenarios. Interestingly, we show that the optimal reward does not always increase with the cellular traffic load, as the increased network congestion can also help motivate users to switch to WiFi networks.
