Spectrum Sharing Strategies for Machine Type Communication in Cognitive Networks

In this work we investigate spectrum sensing strategies for enabling machine-to-machine applications in broadband communication systems. Our studies are carried out in two fronts: (i) experimental testbed using a dedicated software based on proprietary application programming interface for firmware spectrum analyzer; and (ii) computational implementations by means of the Monte Carlo approach. Our results show that cognitive radio effectively enables opportunistic spectrum access between primary and secondary users. In fact, we observed a gain about 10 dB when comparing our best spectrum sharing strategy against the reference (non cognitive radio) deployment scenario.