Dynamical Spectrum Sharing and Medium Access Control for Heterogeneous Cognitive Radio Networks

This paper tackles the issue of spectrum sharing and medium access control among heterogeneous secondary users. Two solutions are proposed in this paper. The first solution can be used in centralized fashion where a central entity exists which decides transmission power for all secondary users. This solution tries to minimize the time required by secondary users to clear their queues. The second solution assumes the autonomy of secondary users where the decision to update transmission power is distributed among users. Dynamical system approach is used to model system behavior. The trajectory of interference noise level suffered by secondary users is used to update transmission power at the beginning of each time frame based on the proposed dynamic power assignment rule. This rule couples the responses of all secondary users in a way which simplifies future interference noise forecasting. A forecasting engine based on deep neural network is proposed. This engine gives secondary users the ability to acquire useful knowledge from surrounding wireless environment. As a result, better transmission power allocation is achieved. Evaluation experiments have confirmed that adopting deep neural network can improve the performance by 46% on average. All of the proposed solutions have achieved an outstanding performance.