Software Defined Radio for Cognitive Networks

  • Nathan Dumont

Student thesis: Doctoral ThesisPhD


The introduction of software radio has meant that standards for radio communication can evolve in a much more natural way, changing only a little at a time without making all of the hardware obsolete. It has become apparent that these changes may affect some systems more favourably than others so allowing the software radio to decide how to adapt can actually improve the link quality. This development is known as cognitive radio and can improve the performance of a single radio link. As an extension of this progress is being made on designing cognitive networks where the software radios which make up the network not only optimise their own link but share information about their goals and situation with other nodes in the network, using all of this data together can optimise overall end-to-end performance of the network.These advances in network design and optimisation come at a time where many parts of the world are re-structuring the television broadcast bands. These have been allocated for a long time and are a generous allocation of a valuable resource. With the power of a cognitive network it is possible to design equipment that can automatically avoid the licensed TV transmitters which only take a fraction of the total bandwidth in any one area. This allows many smaller cells to be fitted between the main transmitters.Assessing the availability of bandwidth and generating maps of available spectrum for these new cognitive networks requires a new approach to radio propagation modelling in the TV bands. Previous models use a worst case scenario to make sure that there is at least enough signal to receive the public service broadcasts in the majority of homes. Predicting where the limits of reception are and where it would be safe to broadcast on these channels requires a better, terrain dependent transmission model. In this thesis the Parabolic Equation Model is applied to the problem of predicting TV band occupancy and the results of this modelling is compared to field measurement to get an idea of how accurate the model is in practice.
Date of Award2 Apr 2014
Original languageEnglish
Awarding Institution
  • University of Bath
SupervisorStephen Pennock (Supervisor) & Robert Watson (Supervisor)


  • software defined radio
  • propagation modelling
  • parabolic equation model

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