Time-Reversal Wireless Paradigm for Green Internet of Things: An Overview <s> Z <s> This paper addresses the Internet of Things. Main enabling factor of this promising paradigm is the integration of several technologies and communications solutions. Identification and tracking technologies, wired and wireless sensor and actuator networks, enhanced communication protocols (shared with the Next Generation Internet), and distributed intelligence for smart objects are just the most relevant. As one can easily imagine, any serious contribution to the advance of the Internet of Things must necessarily be the result of synergetic activities conducted in different fields of knowledge, such as telecommunications, informatics, electronics and social science. In such a complex scenario, this survey is directed to those who want to approach this complex discipline and contribute to its development. Different visions of this Internet of Things paradigm are reported and enabling technologies reviewed. What emerges is that still major issues shall be faced by the research community. The most relevant among them are addressed in details. <s> BIB001 </s> Time-Reversal Wireless Paradigm for Green Internet of Things: An Overview <s> Z <s> The combination of the Internet and emerging technologies such as nearfield communications, real-time localization, and embedded sensors lets us transform everyday objects into smart objects that can understand and react to their environment. Such objects are building blocks for the Internet of Things and enable novel computing applications. As a step toward design and architectural principles for smart objects, the authors introduce a hierarchy of architectures with increasing levels of real-world awareness and interactivity. In particular, they describe activity-, policy-, and process-aware smart objects and demonstrate how the respective architectural abstractions support increasingly complex application. <s> BIB002
The signal received at transceiver B is the convolution of and , plus additive white Gaussian noise (AWGN) with zero-mean and variance , i.e., Z Z where and . Thanks to the temporal focusing, when , the power of achieves its maximum for , i.e., As the receiver, transceiver B simply samples the received signal every seconds at , BIB001 for , in order to detect the symbol where ≜ . Consequently, the resulting signal-to-interference-plus-noise ratio (SINR) is obtained as assuming that each information symbol has unit power. 3) An Equivalent System Model with Limited Bandwidth: Based on (2)-(10), one can come up with an equivalent system model shown in Fig. 7 for the system with limited system bandwidth as shown in Fig. 6 . In the equivalent system model, is treated as the effective channel response for such a finite-bandwidth system, taking into account the use of the band-limiting pulse shaping filter . Accordingly, the time-reversed (and conjugated) version of the equivalent channel response is the corresponding TR signature waveform for the equivalent model. Fig. 7 . Basic TR communications with equivalent channel response . BIB002 The duration of each chip is .  Note that in this paper, the base-band system model is considered. As a result, no RF components are included in the system diagrams. In the following discussion of the TRDMA scheme in this paper, we use the simpler equivalent model by looking at the effective channel response , which can be verified by comparing Figs. 6 and 7.