  In this paper, we introduce an approach for application-aware resource block
scheduling of elastic and inelastic adaptive real-time traffic in fourth
generation Long Term Evolution (LTE) systems. The users are assigned to
resource blocks. A transmission may use multiple resource blocks scheduled over
frequency and time. In our model, we use logarithmic and sigmoidal-like utility
functions to represent the users applications running on different user
equipments (UE)s. We present an optimal problem with utility proportional
fairness policy, where the fairness among users is in utility percentage (i.e
user satisfaction with the service) of the corresponding applications. Our
objective is to allocate the resources to the users with priority given to the
adaptive real-time application users. In addition, a minimum resource
allocation for users with elastic and inelastic traffic should be guaranteed.
Every user subscribing for the mobile service should have a minimum
quality-of-service (QoS) with a priority criterion. We prove that our
scheduling policy exists and achieves the maximum. Therefore the optimal
solution is tractable. We present a centralized scheduling algorithm to
allocate evolved NodeB (eNodeB) resources optimally with a priority criterion.
Finally, we present simulation results for the performance of our scheduling
algorithm and compare our results with conventional proportional fairness
approaches. The results show that the user satisfaction is higher with our
proposed method.
