LAUSR

We design two estimation schemes, Method I and Method II, for rapidly obtaining separate estimates of the number of active nodes of each traffic type in a heterogeneous machine-to-machine (M2M) network with T types of nodes (e.g., those that send emergency, periodic, normal type data etc.), where $$T\ge 2$$ T ≥ 2 is an arbitrary integer. Method I is a simple scheme, and Method II is more sophisticated and outperforms Method I. Also, we design a medium access control (MAC) protocol that supports multi-channel operation for a heterogeneous M2M network with T types of nodes, operating as a secondary network using Cognitive Radio technology. In every time frame, our Cognitive MAC protocol uses the proposed estimation schemes to rapidly estimate the active node cardinality of each type, and uses these estimates to find the optimal contention probabilities to be used. We compute a closed form expression for the expected number of time slots required by Method I to execute, and a simple upper bound on it. Also, we analytically obtain expressions for the expected number of successful contentions per frame and the expected amount of energy consumed. Finally, we evaluate the performances of our proposed estimation schemes and Cognitive MAC protocol using simulations.