Backscatter technology and intelligent reflecting technology surface technology in the Internet of Things

One of the key challenges of the Internet of Things (IoT) is to sustainably power the large number of IoT devices in real-time. This chapter considers a wireless power transfer (WPT) scenario between an energy transmitter (ET) capable of retrodirective WPT and an energy receiver (ER) capable of ambient backscatter in the presence of an ambient source (AS). Recently, Backscatter technology and intelligent reflecting Technology surface (IRS) have been proposed as a key enabling technology for achieving a smart and reconfigurable signal propagation environment in future wireless networks. Specifically, IRS is a metasurface composed of a large number of low-cost passive reflecting elements. By adaptively adjusting the reflection amplitude and phase shift of each element at an IRS, the strength and direction of the electromagnetic wave becomes highly controllable, whereby the reflected signal can be intentionally enhanced or weakened at different receivers. This chapter exploits an intelligent reflecting surface assisted wireless powered IoT networks. Specifically, we consider a power station (PS) intelligent reflecting surface provides wireless charging to multiple IoT devices, which utilizes harvested energy to transmit their own data to an access point (AP). The IRS is deployed to enhance wireless energy transfer (WET) and wireless information transfer (WIT) capabilities by intelligently tuning the phase shifts of a large number of low-cost passive reflecting elements. To evaluate the performance of the considered system, we are interested in the maximization problem of the sum throughput, subjecting to the constraints of the transmission time scheduling as well as the unit-modulus of the phase shifts. Due to the coupled variables, the formulated problem is not jointly convex with respect to the phase shifts of both WET and WIT as well as the transmission time scheduling. To circumvent this nonconvexity, we first derive the closed-form phase shifts of the WIT phase by a triangle inequality. It follows that the Lagrange dual method and the KKT conditions are considered to derive the optimal transmission time scheduling in closed-form. We also propose the Majorization-Minimization (MM) and Complex Circle Manifold (CCM) algorithms to derive the closed-form phase shifts of the WET phase. Finally, numerical results are demonstrated to validate the performance of the proposed scheme, which highlights the beneficial role of the IRS in comparison to the benchmark schemes. Firstly, nonorthogonal multiple access (NOMA) and ambient backscatter communication have been envisioned as two promising technologies for the Internet-of-things due to their high spectral efficiency and energy efficiency. Motivated by this fact, we consider an ambient backscatter NOMA system in the presence of a malicious eavesdropper. Under the realistic assumptions of residual hardware impairments (RHIs), channel estimation errors (CEEs) and imperfect successive interference cancellation (ipSIC), we investigate the physical layer security (PLS) of the ambient backscatter NOMA systems with emphasis on reliability and security. In order to further improve the security of the considered system, an artificial noise scheme is proposed where the radio frequency (RF) source acts as a jammer that transmits interference signals to the legitimate receivers and eavesdropper. On this basis, the analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived. To gain more insights, the asymptotic analysis and corresponding diversity orders for the OP in the high signal-to-noise ratio (SNR) regime are carried out, and the asymptotic behaviors of the IP in the high main-to-eavesdropper ratio (MER) region are explored as well. Then, the correctness of the theoretical analysis is verified by the Monte Carlo simulation results. These results show that compared with the nonideal conditions, the reliability of the considered system is high under ideal conditions, but the security is low. Secondly, in this chapter, we investigate the reliability and the security of the ambient backscatter (AmBC) nonorthogonal multiple access (NOMA) systems, where the source aims to communicate with two NOMA users in the presence of an eavesdropper. To be practical, we assume that all nodes and backscatter device (BD) suffer from in-phase and quadrature-phase imbalance (IQI). More specifically, some analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived. In order to obtain more insights, the asymptotic behaviors for the OP in the high signal-to-noise ratio (SNR) regime are explored, and corresponding diversity orders are derived. Numerical results show that: 1) Although IQI reduces the reliability, it can enhance the security; 2) Compared with the orthogonal multiple access (OMA) systems, the considered AmBC NOMA systems can obtain better reliability when the SNR is lower; 3) There are error floors for the OP in the high SNR regime due to the reflection coefficient β ; 4) There exists a trade-off between reliability and security. Finally, we study the impact of an intelligent reflecting surface (IRS) on computational performance in a mobile edge computing (MEC) system. Specifically, an access point (AP) equipped with an edge server provides MEC services to multiple internet of thing (IoT) devices that choose to offload a portion of their own computational tasks to the AP with the remaining portion being locally computed. We deploy an IRS to enhance the computational performance of the MEC system by intelligently adjusting the phase shift of each reflecting element. A joint design problem is formulated for the considered IRS assisted MEC system, aiming to optimize its sum computational bits and taking into account the CPU frequency, the offloading time allocation, transmit power of each device as well as the phase shifts of the IRS. To deal with the nonconvexity of the formulated problem, we conduct our algorithm design by finding the optimized phase shifts first and then achieving the jointly optimal solution of the CPU frequency, the transmit power and the offloading time allocation by considering the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions. Numerical evaluations highlight the advantage of the IRS-assisted MEC system in comparison with the benchmark schemes.