Joint time‐slot and power allocation algorithm for data and energy integrated networks supporting internet of things (IoT)

IoT is an essential enabler for smart cities and smart society. However, its deployment at large scale faces a big challenge: battery replacement as most IoT devices are battery‐powered or even battery‐less. In a hostile environment, it is infeasible to replace batteries. Radio frequency (RF)‐enable wireless energy transfer (WET) is a promising technology to solve this problem. Since RF is also used for wireless data communication, a data and energy integrated network (DEIN) is the way forward. Based on the DEIN technology, a time allocation model is designed in this paper to manage the RF energy and uplink data transmission in different time slots. In the IoT scenario, the DEIN's primary service is to collect environmental information such as temperature, humidity, and luminance. Therefore, the uplink data transmission of the battery‐powered/battery‐less IoT nodes deserves more attention. To increase the uplink data transmission in case of consuming less energy in the DEIN system, we propose a joint time slot and power allocation algorithm to minimize the system's consumed energy for transmitting per bit of uplink data. It aims to maximize the efficiency of the DEIN system's energy utilization, which helps to achieve an energy‐efficient DEIN

Optimization of secure wireless communications for IoT networks in the presence of eavesdroppers

The problem motivates this paper is that securing the critical data of 5G based wireless IoT network is of significant importance. Wireless 5G IoT systems consist of a large number of devices (low-cost legitimate users), which are of low complexity and under strict energy constraints. Physical layer security (PLS) schemes, along with energy harvesting, have emerged as a potential candidate that provides an effective solution to address this issue. During the data collection process of IoT, PHY security techniques can exploit the characteristics of the wireless channel to ensure secure communication. This paper focuses on optimizing the secrecy rate for simultaneous wireless information and power transfer (SWIPT) IoT system, considering that the malicious eavesdroppers can intercept the data. In particular, the main aim is to optimize the secrecy rate of the system under signal to interference noise ratio (SINR), energy harvesting (EH), and total transmits power constraints. We model our design as an optimization problem that advocates the use of additional noise to ensure secure communication and guarantees efficient wireless energy transfer. The primary problem is non-convex due to complex objective functions in terms of transmit beamforming matrix and power splitting ratios. We have considered both the perfect channel state information (CSI) and the imperfect CSI scenarios. To circumvent the non-convexity of the primary problem in perfect CSI case, we proposed a solution based on the concave-convex procedure (CCCP) iterative algorithm, which results in a maximum local solution for the secrecy rate. In the imperfect CSI scenario, we facilitate the use of S-procedure and present a solution based on the iterative successive convex approximation (SCA) approach. Simulation results present the validations of the proposed algorithms. The results provide an insightful view that the proposed iterative method based on the CCCP algorithm achieves higher secrecy rates and lower computational complexity in comparison to the other algorithms