A cellular neural network and utility-based scheduler for multimedia CDMA cellular networks

In this paper, a cellular neural network and utility (CNNU)-based scheduler is proposed for multimedia CDMA cellular networks supporting differentiated quality-of-service (QoS). The cellular neural network is powerful for complicated optimization problems and implementable by circuits with rapid convergence to a desired equilibrium; the utility-based scheduling algorithm can efficiently utilize the radio resource for system and provide QoS requirements and fairness for connections. A relevant utility function for each connection is here defined as its radio resource function further weighted by both a QoS requirement deviation function and a fairness compensation function. The CNNU-based scheduler determines a radio resource assignment vector for all connections so that the overall system utility is maximized and the system throughput can be achieved as high as possible. At the same time, the performance measures of all connections are kept closed to their QoS requirements in an efficient way.