Yiran Xu

Optimal Fractional Frequency Reuse and Power Control in the Heterogeneous Wireless Networks

Heterogeneous wireless networks have emerged as a new paradigm to meet the fast growing wireless network capacity and coverage demands. Due to the co-deployment of high power and low power nodes in the same network using the same spectrum, more advanced interference coordination and radio resource management schemes are required than in the traditional cellular network in order to achieve a high network capacity and good user experience. In this paper, we propose an optimal fractional frequency reuse and power control scheme that can effectively coordinate the interference among high power and low power nodes. The scheme can be optimized to maximize the sum of the long term log-scale throughput among all the user equipments (UEs). Towards that end, the Lagrange dual function is first derived for the proposed optimization problem. Gradient descent method is then used to search the optimal solution for the convex dual problem. Due to the strong duality condition, the optimal solution for the dual problem is also the optimal solution for the primal problem. Simulation results show that the proposed scheme can greatly improve the wireless heterogeneous network performance on system capacity and user experience.

QoE-aware mobile association and resource allocation over wireless heterogeneous networks

As video content delivery over wireless networks is expected to grow tremendously in upcoming years, how to support energy and bandwidth consuming video applications with high Quality of Experience (QoE) becomes a challenging issue in the future wireless networks. Clearly, there is an urgency for a new disruptive paradigm to bridge the gap between the increasing capacity plus energy demands and the scarce wireless network resources. In this paper, we propose a spectrum and energy efficient mobile association and resource allocation scheme in wireless heterogeneous networks based on two new performance metrics: video content aware or QoE-aware Energy Efficiency (QEE) and video content aware or QoE-aware Spectral Efficiency (QSE). QEE and QSE evaluate the power consumption and bandwidth consumption from video qualitys perspective. First we conduct a fundamental study between QEE and QSE in a point-to-point wireless environment. Then we propose a mobile associations and resource allocation scheme in a heterogeneous wireless network that can optimize QEE and QSE. The system level problem is formulated as a mixed-integer nonlinear optimization problem. Nonlinear fractional programming approach and dual decomposition method are applied to search the optimal solutions in a computationally efficient way.

Video Quality-Based Spectral and Energy Efficient Mobile Association in Heterogeneous Wireless Networks

The staggering mobile growth is shaping to be the biggest shift in technology since the advent of the Internet, paving the way for unprecedented and yet to be thought of video services and applications. The proliferation of these mobile devices and applications, however, requires new paradigms to satisfy the increasing demands for capacity and energy, and achieve a good video quality. In this paper, we propose a video quality-based framework for spectrum and energy efficient mobile association and resource allocation in heterogeneous wireless networks. The basic tenets of the framework are (1) two novel performance metrics, namely QSE and QEE, to capture spectrum usage and energy consumption from video qualitys perspective; and (2) a computationally efficient optimization model to derive mobile association and resource allocation for video connections in heterogeneous wireless networks. To this end, we first study the fundamental tradeoff between QSE and QEE in a PtP Rayleigh fading wireless channel. We then study QSE and QEE at the system level and develop a mobile association and resource allocation scheme that aims to jointly optimize system level QSE and QEE. The problem is formulated as a mixed-integer nonlinear optimization problem. Nonlinear fractional programming approach and dual decomposition method are applied to search the optimal solutions in a computationally efficient way. The simulation results evaluate the performance tradeoff between QSE and QEE, and show that the system performance, including PSNR distribution and maximum QSE/QEE values, greatly depends on bandwidth and power decaying factors.

Cooperative Non-Orthogonal Multiple Access in Heterogeneous Networks

In order to address the ever increasing high capacity demands, next generation wireless networks are required to revolutionize the infrastructure design and air interface technologies. In this paper, we introduce a cooperative non-orthogonal multiple access (NOMA) technique with successive interference cancellation (SIC) in wireless heterogeneous networks. Aiming to improve the system capacity, the cooperative NOMA scheme exploits both NOMA and dirty paper coding (DPC), based on which a resource scheduling optimization problem is formulated. The optimization problem is a combinatorial mixed-integer non-linear problem. A genetic algorithm is used to solve the problem with a low computational complexity. Simulation results show that the proposed cooperative NOMA scheme can significantly improve the network capacity.

Optimal intra-cell cooperation in the heterogeneous relay networks

Heterogeneous wireless networks have emerged as a new paradigm to meet the fast increasing wireless capacity and coverage demands. Cooperative communication is a promising technique to further improve the cell edge performance for future communication systems by allowing nodes in a communication network to collaborate with each other in information transmission. This paper presents an optimal intra-cell cooperative transmission in a relay based heterogeneous networks to best address both capacity and coverage demands. We first formulate the optimization problem to maximize the time averaged log-scale throughput. The Lagrange dual function is then derived for the proposed optimization problem, from which we use gradient descent method to search the optimal intra-cell cooperative transmission solution. Simulation results show that the optimal cooperative transmission can greatly improve the log-scale throughput in the heterogeneous networks with relays.

Pricing-based distributed mobile association for heterogeneous networks with cooperative relays

Heterogeneous networks improve the spectrum efficiency and coverage of wireless communication networks by deploying low-power nodes on top of the conventional network nodes. In this paper, we consider a heterogeneous cellular network with multiple low-power relay nodes (RN) deployed in each cell using in-band wireless backhaul between the RN and the base stations (BS). The RNs work cooperatively with the BSs on the downlink communication towards the user equipments (UE). Due to the disparity between the transmit powers of the BSs and the RNs, mobile association schemes developed for the conventional homogeneous networks may lead to a highly unbalanced traffic loading with most of the traffic being concentrated on the BSs. In this paper, we propose a new mobile association framework for the heterogeneous wireless networks with intra-cell node cooperations. The proposed framework aims to maximize the network capacity and balance the traffic load among the network nodes. Furthermore, we introduce a pricing mechanism to enable the distributed implementation of the proposed scheme. Numerical results show that a prominent improvement in network capacity can be achieved by the proposed pricing-based mobile association scheme.

A NOMA and MU-MIMO Supported Cellular Network with Underlaid D2D Communications

The paper studies a scheme that jointly considers beamforming based MU-MIMO and NOMA in a downlink cellular network with underlaid D2D users. Two different MU-MIMO beamforming schemes are developed. The first beamforming scheme aims to eliminate the interference caused by different beams while the second one aims to cancel out the interference from base stations to D2D users. An optimization problem is formulated to maximize the total system sum throughput of both cellular users and D2D users. Since the optimization problem is NP hard and difficult to solve, we develop a suboptimal sequential solution by determining the zero-forcing beamforming matrix for MU-MIMO first. Then a user grouping and optimal power allocation algorithm is proposed in order to maximize the capacity of cellular users in each beam. Simulation results show that MUMIMO beamforming, NOMA and D2D together will significantly improve the overall system throughput.

Optimal intra-cell cooperation with precoding in wireless heterogeneous networks

Wireless heterogeneous networks have emerged as a new paradigm to meet the fast increasing wireless capacity and coverage demands. Coordinated Multipoint Processing (CoMP) and Precoding are two promising techniques to further improve the network capacity and spectral efficiency. This paper presents an optimal intra-cell CoMP resource allocation scheme in a wireless heterogeneous network and explores the Tomlinson-Harashima Precoding (THP) in the physical layer to reduce the inter-user interference. The objective is to maximize the aggregate proportional rates in the system. We derive an asymptotically optimal solution for resource allocation by using a gradient descent based scheduling and KKT conditions for optimality. Simulation results demonstrate the system proportional fairness capacity gain of proposed resource allocation scheme and this resource management framework provides a guideline for future radio resource management in wireless heterogeneous networks.

Tradeoffs in video transmission over wireless heterogeneous networks: Energy, bandwidth and QoE

In this paper, we propose a multi-objective optimization framework to address the joint mobile association and resource allocation problem in a video transmitted wireless heterogeneous network. We consider user quality of experience (QoE) as one of the design objectives together with two other performance metrics to characterize the design tradeoffs among perceived video quality, power consumption, and network resource consumption. In order to find the Pareto optimal solutions for a multi-objective optimization problem, we first apply weighted Tchebycheff approach to aggregate multiple objectives and minimize the Tchebycheff distance between the optimal solution and utopia solution. Dual decomposition technique is then introduced to decompose the above mentioned problem into a series of similar subproblems. By using linear relaxation and variable transformation, standard convex optimization method is applied to solve these subproblems efficiently and the optimal mobile association and resource allocation are obtained. System level simulation studies numerically demonstrate the tradeoffs among three design objectives and provide an insightful understanding on the performance compromise under multi-objective conditions.

An algebraic framework for mobile association in wireless heterogeneous networks

Heterogeneous network via the deployment of a diverse set of base stations (BSs) has become a hot research topic to improve spectral efficiency and network capacity. In this paper, we consider a cellular network with multiple low-power relay nodes (RN) deployed in each cell to help the downlink transmission between the BS and the user equipments (UE). With conventional mobile association schemes, traffic load may concentrate on the BSs due to their high transmit power, leading to a highly unbalanced traffic load distribution and inefficient utilization of the RNs. We first derive a generalized algebraic framework for mobile association optimization of UEs, considering the load balance of BSs and RNs. In addition, we propose a greedy mobile association algorithm to accept UEs according to the effective consuming resource table. Simulation studies demonstrate the effectiveness of our proposed algorithm.