Optimisation of collaborative spectrum sensing with SIMO cognitive terminals using genetic algorithm

Cognitive radio has been identified as a potential candidate to increase spectrum utilisation by exploiting spectrum holes on a non-interfering basis. Spectrum sensing is the key functionality to make sure that the cognitive radio is aware and will not disturb the operation of the licensed users. Collaborative spectrum sensing is needed to overcome deleterious channel effects such as fading or the hidden node problem and to increase sensing reliability and accuracy. This paper presents a novel optimisation framework for collaborative spectrum sensing in the presence of imperfect reporting channels. It is also shown in this paper that in fading channels spectrum sensing performance can be significantly improved by using multiple antennas at the cognitive radio terminal. A weighted optimised collaborative spectrum sensing scheme with multiple antenna cognitive terminals, which maximises global probability of detection at the fusion centre using genetic algorithm is presented. Based on an individual user local conditions, the algorithm assigns optimal weight to the user observation at the fusion centre. Simulation results illustrate that significant collaborative and spatial diversity gains can be achieved by the proposed spectrum sensing framework.