Sensors are becoming omnipresent. A wide range of applications such as environmental monitoring, smart metering, and remote monitoring of roads are already making an extensive use of the sensor technology to measure and transmit a diverse set of physical signals over noisy wireless channels. Over the next decade, the number of machines and sensors connected to the Internet is expected to explode, creating the so called Internet of Things (IoT). It is foreseen that a significant portion of the quintillions of bytes of data that will be generated every day by IoT will be processed and transmitted using complexity, power, and energy constrained sensor nodes. For the sake of mathematical analysis, these practical constraints are usually relaxed or completely ignored, thereby simplifying the problem at hand, sometimes even to the extent that allows one to obtain closed-form solutions. The main goal of this research project is to question such simplifications commonly made among information/communication theory researchers, and to try to formulate more practically relevant problems which can still be analyzed rigorously.
The practical constraints above will be solidified as zero-delay, peak-power-limited, and energy-distortion frameworks and combinations thereof in a multi-user joint source-channel coding setting. Preliminary analyses demonstrate that the solutions to the communication problems in these frameworks are significantly different from their counterparts in the classical infinite-delay average power-distortion framework. More specifically, the best known coding schemes in the classical framework become either provably suboptimal or not applicable at all. This research project will strive for complete characterizations of fundamental limits of communication under the aforementioned practical constraints.
