Towards an Application-Aware Resource Scheduling With Carrier Aggregation in Cellular Systems

In this letter, we introduce an application-aware approach for resource block scheduling with carrier aggregation in long-term-evolution advanced (LTE-advanced) cellular networks. In our approach, users are partitioned in different groups based on the carriers coverage area. In each group of users, users equipments (UE)s are assigned resource blocks (RB)s from all in band carriers. We use a utility proportional fairness (PF) approach in the utility percentage of the application running on the UE. Each user is guaranteed a minimum quality of service (QoS) with a priority criterion that is based on the type of application running on the UE. We prove that our scheduling policy exists, and therefore, the optimal solution is tractable. Simulation results are provided to compare the performance of the proposed RB scheduling approach with other scheduling policies.

[1]  Chung Shue Chen,et al.  Self-organized resource allocation in LTE systems with weighted proportional fairness , 2012, 2012 IEEE International Conference on Communications (ICC).

[2]  Ahmed Abdel-Hadi,et al.  An optimal application-aware resource block scheduling in LTE , 2014, 2015 International Conference on Computing, Networking and Communications (ICNC).

[3]  Ahmed Abdel-Hadi,et al.  A utility proportional fairness approach for resource allocation in 4G-LTE , 2014, 2014 International Conference on Computing, Networking and Communications (ICNC).

[4]  Xuemin Shen,et al.  A Dual-Decomposition-Based Resource Allocation for OFDMA Networks With Imperfect CSI , 2010, IEEE Transactions on Vehicular Technology.

[5]  Xuemin Shen,et al.  Resource allocation in OFDMA networks based on interior point methods , 2010, Wirel. Commun. Mob. Comput..

[6]  Ahmed Abdel-Hadi,et al.  Utility Proportional Fairness Resource Allocation with Carrier Aggregation in 4G-LTE , 2013, MILCOM 2013 - 2013 IEEE Military Communications Conference.

[7]  Stefania Sesia,et al.  LTE - The UMTS Long Term Evolution, Second Edition , 2011 .

[8]  Josef A. Nossek,et al.  Rate Balancing in Multiuser MIMO OFDM Systems , 2009, IEEE Transactions on Communications.