AFRL; IAI, Inc.: EARN: Energy Aware Radio Networking for Energy Efficient Tactical Communications

Faculty

Sennur Ulukus

Funding Agency

Air Force Research Laboratory

Year

2020

Descriptions

This is SBIR funding with IAI, Inc. One year, $50,000. Dr. Ulukus is a subcontractor to IAI, with the following tasks.

Support developing proactive radio resource management module. The purpose of this task is to develop a radio resource management scheme that allows the radio to efficiently allocate its resources based on the forecasted battery/ energy harvesting states in order to improve the performance.

Support developing learning-based cooperative framework for energy efficiency: The purpose of this task is to develop an intelligent cooperation scheme using machine learning, for the purpose of achieving energy efficient radio transmissions. This task includes a machine learning framework for optimal relay selection and a joint machine-learning based optimal selection of transmission parameters by the radio and relay based on their energy and traffic state to achieve the target performance.

Support developing energy-aware age of information minimizing schemes. Age of information is a metric that measures the timeliness/freshness of the delivered information, and hence it is an important metric to consider while developing the EARN system. The purpose of this task is to develop algorithms that determine optimal spectrum access parameters that minimizes the age-of-information thus ensuring the timeliness of the information delivered while considering the radio’s battery profile.