# Zero Energy IoT Devices in Smart Cities Using RF Energy Harvesting
## 2 Literature
### Other RF-Based EH-WSN Protocols  
Ref. [5] presented a routing protocol for EH-WSN. In this work, he used the improved energy-efficient ant-based routing algorithm (IEEABR) for RF energy harvesting and management of the harvested and available energy for wireless sensor networks. He first discusses the RF power density, storage of the harvested power, calculation of the received power, and management of the power in the EH-WSN protocol. IEEABR technique used for routing. The author of this paper used the Friis equation [20], which is used in a situation where the distance between two nodes or antennas is known, and this equation is discussed in [20] in detail. Ref. [21] presented an energy harvesting-aware routing protocol.  
\[\frac{P_{t}}{G_{t}}=\frac{G_{t}G_{r}\lambda^{2}}{(4\pi)^{2}d^{2}} \tag{6}\]  
where \(P_{t}\) is the transmitted power, \(P_{t}\) is the received power, \(G_{t}\) is the transmitter gain power, \(G_{r}\) is the receiver antenna's received power, \(d\) is the T-R-Separation distance in meters, and \(\lambda\) is the wavelength in meters. Gain power is based on the aperture of the antenna.  
Power density equation is as follows:  
\[P_{D}=\frac{P_{t}}{(4\pi)R^{2}} \tag{7}\]  
where \(P_{D}\) is the power density and \(R\) is the distance between the transmitter and the receiving antenna, \(P_{t}\) is the peak or average power. The energy storage equation is as follows:  
\[\mathrm{T}\;=\frac{C}{I_{N}} \tag{8}\]  
where \(C\) is the theoretical capacity of the battery expressed in ampere-hours, \(\mathrm{I}\) is the current drawn in Ampere (A), \(\mathrm{T}\) is the time of discharge in seconds, and \(\mathrm{n}\) is the Peukert number. The power management algorithm's main idea is as follows: First of all, initialize the routing table and find the neighbor nodes; if a node is visited two times, then halt otherwise selects the next node according to the probabilistic equation. This process will continue until the destination node is reached. The author used NS-2 for simulation results. Ref. [22] used the AODV traditional routing algorithm for presenting the EH-based routing protocol EH-AODV. EHAODV uses the advantages of AODV with only minor changes in the packet header by replacing hop count with transmission cost (TC). TC is used in route request (RREQ) and route reply (RREP) operations. TC is a predictable technique that can be predicted through the below equations. Ref. [23] presented a MAC protocol. The basic idea is that, first of all, a sensor node will harvest energy through RF, and then the sensor node will charge its battery. After charging, the node will sense and gather the respected information. A backup time concept is used for packet collision avoidance and then the sensor waits for a certain amount of time. At last, the packet can be transmitted when there is no collision. Ref. [14] presented an RF-EH battery-free energy cooperation wireless network for reducing communication latency to improve network performance. The authors of [24; 25] presented a cluster-based protocol that harvests energy from solar.  
The work of [26] is related to our study but does not consider mobile, so nearest-farthest problems exist. The research in [27] used distributed secure state estimation (SSE) under sparse sensor attacks to recover the states of the considered CPS from corrupted measurements.