Autonomous and Intelligent Wireless Transceivers

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With the introduction of the concept of Internet of Things, the number of wireless devices and sensors is exponentially increasing, doubling every three to four years. It is projected to reach over 125 billion devices by 2030. However, such trend creates challenges in maintaining, monitoring, and controlling all these devices. These challenges motivate the need for self-powered and self-reliant smart sensors and wireless devices. Aiming at autonomy, this research program proposes new wireless receiver architectures and energy harvesting techniques that improve the energy efficiency of sensors and wireless devices. In particular, a highly selective receiver using passive mixing techniques, will be proposed to filter through a received desired signal at a given carrier frequency, while directing the reflected in-band and out-of-band interferers toward an energy harvesting circuit. The energy in these unwanted interferers will be harnessed and used to self-power the receiver. Waveform shaping techniques will be used to build highly efficient, broadband, and high dynamic range energy harvesting circuits. In the area of circuit intelligence, less reliance on conventional definite architectures of digital signal processors and a shift toward neuromorphic architectures suitable for artificial intelligence will not only reduce significantly the energy needed by their signal processing components but also bring more intelligence to these sensors and devices. This research proposal will benefit from the advancement in artificial intelligence algorithms and neuromorphic circuitry. It will propose new architectures of reconfigurable and adaptive analog RF circuits that increase the wireless system intelligence. These architectures will rely less on human input by incorporating self-calibrating simplified neuromorphic circuit elements. Using this concept, an all-digital self-calibrating transmitter will be proposed. In this smart transmitter, the use of highly efficient switch mode power amplifiers will lower the power consumption of the transmitter. The Self calibration techniques of the RF front-end are anticipated to mitigate the distortion produced by these nonlinear circuits without the need for the computational complexity of digital predistortion commonly used in currently adopted solutions. The proposed new smart and autonomous transmitter and receiver frontend architectures will be an enabling technology for the design of more cognitive, more ubiquitous, and faster networks of the future generations of wireless communication standards.