There is a growing interest of wireless operators to migrate their existing 3G networks to different 4G technologies such as WiMAX and LTE. In this heterogeneous environment of wireless networks and architectures, one of the major concerns is how to allocate network resources efficiently to diverse traffic classes with different QoS constraints. Further it has been convincingly demonstrated through numerous high quality studies that multimedia traffic found in modern wireless networks exhibits LongRange Dependence (LRD) and selfsimilarity, a phenomenon which cant' be captured by traditional traffic modeling based on simplistic Poisson model. Unlike most existing studies that are primarily based on simplistic Poisson model and traditional scheduling algorithms, this research presents an analytical performance model for multiple queue systems with selfsimilar traffic input scheduled by a novel and promising scheduling mechanism. Our proposed model is substantiated on G/M/1 queuing system that considers multiple classes of traffic exhibiting longrangedependence and selfsimilar characteristics. We analyzethe model on the basis of newly proposed scheduling scheme. We present closed form expressions of expected waiting times for multiple traffic classes. We develop a finite queue Markov chain for the proposed scheduling scheme. We develop a discrete event simulator to understand the behavior of multiple classes of selfsimilar traffic under this newly proposed schedulingmechanism. The results indicate that our proposed scheduling algorithm provides preferential treatment to realtime applications such as voice and video but not to that extent that data applications are starving for bandwidth and outperforms all other scheduling schemes that are available in the market.