Reduced feedback schemes are a crucial component of orthogonal frequency division multiplexing-based 4G and 5G cellular systems that use downlink scheduling, adaptive modulation and coding, and multiple-input-multiple-output ...

This thesis presents results on error correcting codes for settings such as: (a) distributed storage, (b) private information retrieval, and (c) low-latency streaming. It also presents two new decoding algorithms for Polar ...

The goal of this thesis is to study the compression problems arising in distributed computing systematically. In the first part of the thesis, we study gradient compression for distributed first-order optimization. We ...

The capability of hand-held devices to acquire high-definition visual content has led to a tremendous increase in the number of images and videos captured daily. However, camera hardware and pipelines are not perfect and ...

The reliable storage of Big Data across a spatially distributed network of nodes, calls for erasure-correcting codes that in addition to protecting against data loss, can also efficiently handle node repair. The need for ...

In this computer era, we all live in a place where the demand for data and computing is increasing day by day. Since the need for faster data retrieval and faster computation brings us a reliability as the solution, we ...

The primary contribution of this thesis is the comprehensive design, development, and deployment of a pyroElectric, InfraRed-sensor-based IntruSion classification (EIRIS) platform, along with attendant detection and ...

Caching is a promising technique that can reduce the amount of data transmitted over latency-prone links, effectively trading affordable memory for expensive bandwidth resources. The frequently demanded content is stored ...

A vast majority of the Internet of Things (IoT) devices will be connected in a topology where the edge-devices push data to a local gateway, which forwards the data to a cloud for further processing. In sizeable outdoor ...

Deep learning techniques which employ trained neural networks to solve problems have witnessed widespread adoption in diverse fields like medicine, architecture, robotics, autonomous vehicles, wireless communications, ...