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

Abstract

Abstract-In this paper, 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.

Data-driven performance evaluation of carrier aggregation in LTE-Advanced

“…To the best of our knowledge there are no works in the literature that evaluate the performance of CA with practical experiments. In fact, academic papers mainly focus on its optimization: for instance, [4] studies smart and fair resource allocation methods; application-aware resource allocation methods aiming to improve user ex-perience and resource optimization are discussed in [5], while [6] proposes algorithms to minimize CA (Multistream) energy consumption in heterogeneous networks. Finally, [7], [8] evaluate the energy efficiency of CA by means of practical measurements.…”

A proposed efficiency metric for LTE‐advanced carrier aggregation

“…This is as a result of investing the highest received power of the lowest frequency CC in sending more spatial streams. Consequently, and unlike the studies of [9,16], this achieves a balance between the CCs and results in the same coverage area for the same transmit power. Figure 5 shows the CA efficiency coverage maps for CCs with different antenna system for one cell.…”

Traffic-aware carrier allocation with aggregation for load balancing

“…The traffic to be transmitted is classified into two categories, inelastic and elastic traffic [13]. While inelastic traffic is generated by the real-time applications such as VoIP (voice over IP), elastic traffic is generated by applications including FTP (file transfer protocol) and HTTP (hyper text transfer protocol).…”

“…The application utility function of UE i, U i (r i ) is represented by sigmoidal-like function or logarithmic function [11] [13]. These functions have the following properties: 1) U i (0) = 0 and U (r i ) is an increasing function of r i , 2) U i (r i ) is twice continuously differentiable in r i .…”