A Cellular Neural Network and Utility-Based Radio Resource Scheduler for Multimedia CDMA Communication Systems
The paper proposes a Cellular Neural Network and Utility (CNNU)-based radio resource scheduler for multimedia CDMA communication systems supporting differentiated Quality-of-Service (QoS). Here, the authors define a relevant utility function for each connection, which is its radio resource function weighted by a QoS requirement deviation function and a fairness compensation function. They also propose Cellular Neural Networks (CNN) to design the utility-based radio resource scheduler according to the Lyapunov method to solve the constrained optimization problem. The CNN is powerful for complicated optimization problems and has been proved that it can rapidly converge to a desired equilibrium; the utility-based scheduling algorithm can efficiently utilize the radio resource for system, keep the QoS requirements of connections guaranteed, and provide the weighted fairness for connections.