A low-cost large-scale framework for cognitive radio routing protocols testing

Cognitive radio networks (CRNs) provide a solution to increase the utilization of the scarce radio frequency spectrum. Building testbeds for CRNs is one of the main challenges that can affect the wide deployability of such networks. In this paper, we present the design, implementation, and evaluation of CogFrame: a framework that facilitates the development of cost-efficient large-scale CRNs routing protocols testbeds. The framework allows the designers to focus on the CRNs routing protocols by abstracting the PHY and MAC layers while providing the necessary cross layer functionalities. CogFrame works with standard computers and WiFi cards to reduce the cost while allowing integration with other special hardware for more flexibility. In addition, CogFrame provides different modules for implementing and emulating complex scenarios such as regulatory authority policies, mobility management, and topology management. We benchmark the performance of CogFrame and compare it to standard ns-2 simulations and USRP2 implementations. In addition, we case study a location-aided routing protocol for CRNs using both CogFrame and ns-2 simulations. Our results highlight the ease of implementation, low-cost, and realistic replication of the CRN environment, showing the promise of CogFrame as a testbed for future CRNs implementations.