Enabling Data Driven Communications in Terahertz Bands
Abstract
Overview: Among emerging technologies, data transmission in the Terahertz (THz) band, specifically between 0.1 and 10 THz, has the potential to leverage the wide bandwidths available at THz frequencies to meet the high data rate requirements and to assure robust communications in challenging environments for national defense applications. The unprecedented multi-gigahertz (GHz) bandwidth in THz-band, however, comes at the expense of significant propagation loss, blockage effect, and the need for specialized radio frequency electronics design. To address the unique behavior of wireless channels in the THz band, it is necessary to revisit baseband signal processing techniques, e.g., receiver design, channel estimation, joint beamforming and beamcombining codebook design, etc. while keeping the computing costs low. Recent advances in artificial intelligence (AI) motivate communications engineers to incorporate machine and deep learning tools at the baseband physical (PHY) layer design of wireless communication systems to enhance the end-to-end performance without yielding prohibitive computational complexity in real-time applications. This proposal aims to study fundamental challenges for baseband signal processing while operating at THz-band, design innovative algorithms while leveraging machine and deep learning (DL), and analyze the end-to-end system performance in a standardized and practical testbed. Intellectual Merit: This project will conduct a comprehensive investigation of the challenges inherent to THz-bands and develop analytical tools and propose novel signal processing algorithms accordingly while focusing on minimizing real-time computational complexity and maximizing network throughput. In summary, this successful accomplishment of this project will lead to (1) systematic investigation of baseband signal processing challenges at the receiver and thereby design innovative, data-driven, robust, and low-complexity solutions, (2) joint design of beamforming and beamcombinining at the transmitter and receiver, respectively while preserving low probability interception and detection properties to ensure jam-resilient signal transmission, and (3) build a practical testbed for THz-band communication systems for channel sounding to develop THz-band channel model in different indoor and outdoor settings. Broader Impacts: This project will deliver publicly available datasets and research outcomes from AI-assisted PHY-layer design for THz-band transmissions for robust wireless communication systems. The results and analysis conducted in this project will allow the wireless communication researchers to extend the developed idea to other standardized and non-standardized ad-hoc communication systems. Undergraduate and graduate students will learn how to conduct the fundamental study, address research problems, and design AI-assisted robust wireless communication systems subject to challenging propagation conditions. Students will be trained with fundamental tools like statistical signal processing, machine and DL, computer programming, etc., required to conduct the research thrusts proposed in this proposal. An integrated education and outreach program will be developed to foster interdisciplinary research training among different fields of Electrical and Computer Engineering. Achieving these goals will foster efficient PHY-layer algorithms for THz-band communication systems in non-commercial and military use-cases. The research findings will be published in high-quality journals, transactions, and conference proceedings.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 08, 2022
- Source ID
- W911NF2210224
Entities
People
- Imtiaz Ahmed
Organizations
- Army Contracting Command
- Howard University
- United States Army