Airborne Cognitive Networking: Design, Development, and Deployment
George Sklivanitis, Adam M. Gannon, Konstantinos Tountas, Dimitris A. Pados, Stella N. Batalama, Stephen P. Reichhart, Michael J. Medley, Ngwe Thawdar, Ulysses Lee, John D. Matyjas, Scott Pudlewski, Andrew Drozd, Ashwin Amanna, Fred Latus, Zachary K. Goldsmith, D. Díaz · IEEE Access · 2018
We design, develop, and experimentally validate a complete integrated software/hardware platform for airborne cognitive networking in both indoor and outdoor environments. We first present the concept of all-spectrum cognitive networking and describe a distributed algorithm for maximizing network spectral efficiency by jointly optimizing channel access code-waveforms and routes in a multi-hop network. We then discuss system design parameters and implementation details for setting up a software-defined radio (SDR) testbed that enables reconfigurability at the physical (PHY), medium-access control (MAC), and network (NET) layers of the network protocol stack, either by a user or by means of autonomous decisions. Our algorithmic developments toward spectrally-efficient cognitive networking are software optimized on heterogeneous multi-core general-purpose processor-based SDR architectures by leveraging the design of a novel software-radio framework that offers self-optimization and real-time adaptation capabilities at the PHY, MAC, and NET layers of the network protocol stack. We verify our system design approach in a large-scale testbed deployment of ten terrestrial and one airborne SDR platforms at the Stockbridge Controllable Contested Environment at the Air Force Research Laboratory, Rome, NY, USA. Proof-ofconcept experimental results from both indoor and outdoor testbed deployments show that the proposed system can be used to build all-spectrum cognitive networks that withstand intentional interference at PHY and NET layers and can cognitively coexist with non-cross-layer optimized networks.