IEEE Access · 2018 · 34 citations · 56 references
EngineeringComputer EngineeringComputer ScienceComputer NetworksEmbedded SystemsHardware-software Co-designCognitive RadioRoutingSoftware-defined NetworkingSpectrum AllocationSpectrum ManagementWireless NetworksAirborne Radio CommunicationCognitive Radio NetworksMedium Access ControlMulti-hop CommunicationReal-time AdaptationSoftware Defined RadioSpectral EfficiencySpectrum Sharing
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.
56
CRAHNs: Cognitive radio ad hoc networks
Ian F. Akyildiz, Won-Yeol Lee, Kaushik Chowdhury · Ad Hoc Networks · 2009 · 1.3K citations