QoE-driven joint radio and transport optimized EPS bearer rates of multi-services in LTE

This paper proposes an efficient optimization algorithm to dynamically control the Evolved Packet System (EPS) bearer rates to transport various services between the UE and Evolved Packet Core (EPC) in a LTE Femtocell network scenario. The algorithm is focused on improving the accumulated QoE in the networks and takes joint consideration of limited radio and transport resource so as to leverage the resource management in LTE Radio Access Network (RAN) and transport network. In case of link congestion applications running on TCP tend to share the capacity equally. However, different traffic types have different QoE behaviors and hence sharing the resource equally will lead to a non-optimal aggregated QoE. The proposed algorithm will solve this problem by considering the QoE of individual application flows. We formulate the problem as a convex optimization problem, which maximizes the aggregated QoE, represented by Mean Opinion Score (MOS) value, of all users using different applications, and then solve it using Lagrangian relaxation method. The performance of our algorithms is investigated and evaluated by simulations. The simulations show that our proposed QoE-driven rate shaping algorithm results in a significantly better aggregated QoE compared to the legacy scheme that with fixed rate shaping, especially in heavily congested scenarios. Moreover, a discussion on how often to adjust the shaping rates is given based on the complexity and performance investigations.

Subjects

Bearer shaping

EPS bearer

Lagrangian relaxation

LTE femtocell cluster

QoE

Radio resource allocation

Subgradient projection method

Utility

Options

QoE-driven joint radio and transport optimized EPS bearer rates of multi-services in LTE