With the growing popularity of the Internet of Things (IoT) and machine-to-machine (M2M) devices for automated remote control, massive smart devices are being envisioned. To cope with the heavy energy demand of such large-scale networks, new energy harvesting techniques have been considered. Among them, harvesting power from available radio frequency (RF) energy sources has attracted great attention.

RF energy harvesting enjoys the advantages of mobility, sustainability and scalability. The mode of using RF signals makes it possible to combine RF energy harvesting with wireless communications, which allows data and energy transmission at the same time. Hence, deciding how to allocate resources and schedule charging for such systems is worth a lot of effort.

In this thesis we f...[ Read more ]

With the growing popularity of the Internet of Things (IoT) and machine-to-machine (M2M) devices for automated remote control, massive smart devices are being envisioned. To cope with the heavy energy demand of such large-scale networks, new energy harvesting techniques have been considered. Among them, harvesting power from available radio frequency (RF) energy sources has attracted great attention.

RF energy harvesting enjoys the advantages of mobility, sustainability and scalability. The mode of using RF signals makes it possible to combine RF energy harvesting with wireless communications, which allows data and energy transmission at the same time. Hence, deciding how to allocate resources and schedule charging for such systems is worth a lot of effort.

In this thesis we firstly study a two-way relay system where the relay not only helps forward information but also provides energy to users. We propose a three-phase protocol and investigate the rate optimization problems by jointly optimizing time scheduling and power allocation at the relay and user side. Subsequently, we consider the energy consumption minimization problem with users’ quality-of-service (QoS) constraints. It is revealed that the energy consumption minimization problem actually contains the dual of rate maximization problems. Moreover, we obtain the capacity region for decode-and-forward (DF) relaying by solving the weighted sum rate maximization problem.

We then consider a two-user multiple access channel (MAC) with a wireless-powered relay-to-destination (R-D) link where the relay harvests energy from an RF signal sent by a dedicated power beacon (PB). Each frame is divided into three phases. In the first phase, the relay harvests energy from an RF signal sent by a dedicated PB. The relay then receives information from user nodes in the second phase, and forwards it to the destination in the third phase using its harvested energy. We investigate the sum rate maximization problem and characterize the capacity region of such channel under both the amplify-and-forward (AF) and DF relay strategies. For comparison, we also analyze the problems under conventional relaying. It is interesting to find that the shape of the capacity region is still pentagonal with a wireless-powered relay.

Finally, we look beyond the scenario of wireless communication and investigate a static network that consists of a PB and multiple wireless powered user nodes. Each user node is equipped with a rechargeable battery, and harvests energy only from the PB. We assume all user nodes are either in charge or work mode. Under this assumption, we first propose a charge scheduling scheme that achieves the system’s maximal energy efficiency. We then further investigate the system’s improvement with a multi-antenna PB using the energy beamforming technique. Next, we extend our scheduling scheme to a two-tier network architecture, where a first-tier PB first transfers energy to the second-tier sub-PBs, and then those sub-PBs deliver energy to the user nodes which belong to their clusters. It is shown that energy beamforming with multiple antennas brings a significant improvement to the system’s performance. Moreover, the two-tier architecture is shown to be superior to the one-tier architecture in terms of the energy transfer efficiency and the system’s realization complexity. As a supplement, the case that the PB has limited amount of energy is also investigated. The charge scheduling scheme that can achieve the maximal amount of total harvested energy is derived.