# Wireless Energy Harvesting for Internet-of-Things Devices Using Directional Antennas
## 1 Introduction  
Nowadays, many devices have increased dramatically with the rapid development of the Internet-of-Things (IoT). Numerous sensing devices have been developed for the applications of smart homes/cities/offices [1]. Nevertheless, owing to the limited capacity of batteries, efficient energy saving to prolong the lifetime of devices is crucial. Traditional implementation focuses on reducing energy consumption using various energy-saving strategies. Recently, researchers have proposed various energy-harvesting technologies with different renewable energy resources, like conversions from piezoelectric energy, winds [2], solar energy [3], mechanical vibration [4], and electromagnetic energy. One of the most important technologies is wireless energy transfer (WET), in which devices can convert radio frequency (RF) into electrical energy to charge themselves [5]. The RF technology can be widely used in various networks, like sensor networks or cognitive radio networks. With the technology of RF energy harvesting, wireless sensor devices do not need to replace batteries. RF energy harvesting can be performed based on two types of antennas: omnidirectional antenna or directional antenna. In general, the access point (AP) is equipped with antennas fixed at specific locations. Omnidirectional antenna can transmit energy in all directions; thus, all devices in the transmission range can receive RF energy at the same time. However, due to the lower antenna gain of the omnidirectional antenna, the transmission range is relatively short [6]. On the other hand, the directional antenna can transmit energy in only one direction each time. The area of radio transmission is called the direction sector. Devices in the sector receive RF energy from the power source. Because directional antennas usually have higher antenna gain, their transmission ranges are relatively longcompared to omnidirectional antennas [7]. However, multiple directional antennas are required to cover all directions. Beamforming technology has been proposed to improve the implementation of RF energy harvesting. The technology of beamforming employs an antenna array composed of multiple antennas and exploits the spatial domain to gain extra degrees of freedom. Furthermore, it can generate pencil beams to focus the signal in a narrow direction [8]. In practice, an AP needs accurate knowledge of channel state information (CSI) from/to devices to increase energy beamforming gain. Although the design and implementation of the base station is complicated due to the requirements of CSI and the antenna array [9], the charging time of the devices can be significantly reduced. With the technology of beamforming and WET, it is important to choose a series of appropriate directions for energy transmission. To charge devices to the target battery level, we should have a set of time periods for different directions. Furthermore, when the battery of a device is full, it may perform some specific tasks, e.g., transmitting data to the AP or performing some calculation or upgrading tasks. If a lot of devices are fully charged at the same time, the simultaneous data transmission may cause interference among different devices and the simultaneous computation/upgrade overhead may result in sensing service interruption. To avoid the above issues, it is desirous to gradually increase the number of fully charged devices. In terms of energy overflow of the battery, reducing overflow is equivalent to reducing the number of devices that are fully charged at the same time. To the best of our knowledge, none of the previous work addresses the problem of shortening the charging time and improving the performance of data transmission for charged devices. In this work, we are motivated to propose two algorithms to shorten the recharging time and minimize battery overflow for devices. The proposed greedy algorithm selects a sector to be charged in a greedy manner, in which each sector may overlap with each other.