Simulation of digital message transfer with MIL-STD protocols across HF radio networks

The model of the digitized battlefield utilizes communications networks that automatically execute data transfers between functional areas-combat, combat support and combat service support. With evolving technology and standards, high frequency (HF) radio networking offers one avenue to support tactical and global communications requirements for quick responses to sudden contingencies and for rapid deployments. Standardized ALE procedures, improved signal-processing modems, and interoperable message transfer protocols provide basic elements to create adaptive, automated HF radio networks to support information exchange among Command, Control, Communications and Intelligence (C4I) systems. Unlike other communications services, however, dynamic ionospheric conditions, heavy utilization and inadvertent jamming make the HF channel a hostile one, where links between nodes are subject to frequent failure. These factors yield significantly degraded performance without adaptive, dynamic management. The occurrence of self-jamming under heavy load conditions adds further complexity to performance analysis and prediction. Assessment of network design relative to optimized performance presents a challenging problem. This paper describes computer simulation predictions which provide a basis for assessment of HF radio networks that operates with the MIL-STD procedures and protocols. The simulation model extends earlier work for MIL-STD-188-141A Automatic Link Establishment (ALE) with an implementation of MIL-STD-187-721 for HF network access. It also implements the message format provisions of MIL-STD-188-220 for the data link protocol to enhance battlefield interoperability and compatibility to support the exchange of digital information. It adds to simulation efforts on HF radio network performance. The purpose of this study is to assess the integration of these MIL-STD protocols and the network performance under heavy message load. The results are applied to network management under normal as well as stressed conditions to optimize information exchange and network resource allocation