  Handling the massive number of devices needed in numerous applications such
as smart cities is a major challenge given the scarcity of spectrum resources.
Dynamic spectrum access (DSA) is seen as a potential candidate to support the
connectivity and spectrum access of these devices. We propose an efficient
technique that relies on particle filtering to enable distributed resource
allocation and sharing for large-scale dynamic spectrum access networks. More
specifically, we take advantage of the high tracking capability of particle
filtering to efficiently assign the available spectrum and power resources
among cognitive users. Our proposed technique maximizes the per-user throughput
while ensuring fairness among users, and it does so while accounting for the
different users' quality of service requirements and the channel gains'
variability. Through intensive simulations, we show that our proposed approach
performs well by achieving high overall throughput while improving user's
fairness under different objective functions. Furthermore, it achieves higher
performance when compared to state-of-the-art techniques.
