Acquisition of Software-Defined Radio Equipment for Adaptive Mobile Networking at the Tactical Edge
Abstract
Major Goals: One key limitation of the current mobile communication systems used by the U.S. Army is the lack of adaptability. These systems operate based on the fixed communication strategies that are configured during the tactical mission planning. It is difficult for them to autonomously maintain warfighters situational awareness over heterogeneous battlefield contexts, due to their deficiency of recognizing these contexts and adapting to the corresponding warfighter behaviors such as squad reformation. The major factor hindering such adaptability is the practical Disconnected, Intermittent, and Limited (DIL) network environment at the tactical edge, where end-to-end network connectivity is usually unavailable. Instead, environmental dynamics and warfighter mobility lead to opportunistic and intermittent network disconnection, and warfighters only communicate when they move into the communication range of others wireless radios, referred to as contact. Therefore, a solution to adaptive mobile networking in tactical DIL network environments is urgent. The PI envisions that such adaptability could be achieved based on properly articulated multi-genre network analysis, which exploits the close coupling between mobile communication networks and human social networks at the tactical edge to allow autonomous characterization of warfighters social dynamics from their contact patterns without manual inputs or configurations. Built on this vision, the PI is funded by ARO to develop sociological metrics and adaptive mobile networking paradigms for efficient mobile communication in tactical DIL network environments. However, the methods being used to evaluate the performance of the proposed networking paradigms, protocols and techniques in the PIs research have been limited to trace-driven simulation, which are ineffective in emulating the various practical wireless network characteristics, especially in the PHY and MAC layers, at the tactical edge.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 31, 2018
- Accession Number
- AD1066459
Entities
People
- Wei Gao
Organizations
- University of Tennessee system