Dabing Ling

QoE-based cross-layer design for video applications over LTE

Video applications such as video-on-demand and videoconferencing over wireless networks require system resources to be allocated dynamically and optimally in accordance with the time-varying environment and video contents. User-perceived quality is tending to be a crucial factor in evaluating the success of video applications. The aim of this paper is to propose a cross-layer design scheme for optimizing resource allocation of video applications over Long Term Evolution (LTE) networks based on Quality of Experience (QoE) evaluation. We propose a novel mapping model between Peak Signal-to-Noise Ratio (PSNR) and Mean Opinion Score (MOS) based on a hyperbolic tangent function, which can reflect the relation between objective system parameters and subjective perceived quality simply and precisely. The cross-layer architecture presented in this paper jointly optimizes the Application (APP) layer, the Media Access Control (MAC) layer and the Physical (PHY) layer of the wireless protocol stack. On the basis of this architecture, we present a QoE prediction function and utilize the Particle Swarm Optimization (PSO) method to solve the resource allocation problem. Simulation results show that the proposed scheme significantly outperforms the traditional scheduling scheme in terms of maximizing user-perceived quality as well as maintaining fairness among users.

A multi-cell adaptive resource allocation scheme based on potential game for ICIC in LTE-A

Intercell interference coordination in Third Generation Partnership Project long-term evolution-advanced system has received much attention both from the academia and the standardization communities. Moreover, the network architecture of long-term evolution-advanced system is modified to take into account coordinated transmission. In this article, we study the dynamic resource allocation problem and potential game theory and propose a multicell adaptive distributed resource allocation algorithm based on potential game. The allocation process is divided into two steps; subchannel is allocated first, and then, transmitted power is optimized dynamically according to a novel pricing factor. Besides, existence and uniqueness of Nash equilibrium of the proposed game model are assured. As a result, intercell interference is well coordinated. Simulation results show that transmitted power is saved efficiently and system fairness is improved to a large extent, accompanied with good performance gain of total and cell-edge throughputs. Copyright

Energy-efficient power optimization with Pareto improvement in two-tier femtocell networks

In two-tier femtocell networks, where a central macrocell underlaid with femtocells, femtocells may cause serious interference and consume large amounts of energy for its large-scale application. To solve the problem this paper presents an energy-efficient power optimization for two-tier femtocell networks in the analytical setting of a game theoretic framework, where both circuit and transmission power have been considered. Notice that the Nash equilibrium of the game is not efficient. We introduce pricing of interference, so as to obtain Pareto improvement of the non-cooperative power control game. In order to protect cellular user from severe cross-tier interference and guarantee that cellular user can obtain its Signal-to-Interference-Plus-Noise Ratio (SINR) target, we propose an algorithm which reduces transmit powers of the strongest femtocell interferers. According to simulation results, pricing can improve user utilities significantly.

Gradient projection based QoS driven cross-layer scheduling for video applications

We proposed a novel cross-layer optimization approach for video streaming applications in orthogonal frequency division multiplexing (OFDM) based networks. Parameters in media access control (MAC) layer and physical layer are optimized jointly in a cross-layer framework. The main objective is to maximize video quality by reducing the end-to-end distortion in application layer for each user. Potential games theory is adopted to solve this cross-layer problem in distributed way. Convergence of game is guaranteed by gradient projection, which reduces the time complexity of optimization considerably. Simulation results have confirmed that the gradient projection based cross-layer optimization can significantly enhance the video quality performance with low time complexity and high scalability.