Load Balancing of Elastic Data Traffic in Heterogeneous Wireless Networks

The increasing amount of mobile data traffic has resulted in an architectural innovation in cellular networks through the introduction of heterogeneous networks. In heterogeneous networks, the deployment of macrocells is accompanied by the use of low power pico and femtocells (referred to as microcells) in hot spot areas inside the macrocell which increase the data rate per unit area. The purpose of this thesis is to study the load balancing problem of elastic data traffic in heterogeneous wireless networks. These networks consist of different types of cells with different characteristics. Individual cells are modelled as an M/G/1 - PS queueing system. This results in a multi-server queueing model consisting of a single macrocell with multiple microcells within the area. Both static and dynamic load balancing schemes are developed to balance the data flows between the macrocell and microcells so that the mean flow-level delay is minimized. Both analytical and numerical methods are used for static policies. For dynamic policies, the performance is evaluated by simulations. The results of the study indicate that all dynamic policies can significantly improve the flow-level delay performance in the system under consideration compared to the optimal static policy. The results also indicate that MJSQ and MP are best policies although MJSQ needs less state information. The performance gain of most of the dynamic polices is insensitive with respect to the flow size distribution. In addition, many interesting tests are conducted such as the effect of increasing the number of microcells and the impact of service rate difference between macrocell and microcells

Self-optimizing load balancing with backhaul-constrained radio access networks

Self-Organizing Network (SON) technology aims at autonomously deploying, optimizing and repairing the Radio Access Networks (RAN). SON algorithms typically use Key Performance Indicators (KPIs) from the RAN. It is shown that in certain cases, it is essential to take into account the impact of the backhaul state in the design of the SON algorithm. We revisit the Base Station (BS) load definition taking into account the backhaul state. We provide an analytical formula for the load along with a simple estimator for both elastic and guaranteed bit-rate (GBR) traffic. We incorporate the proposed load estimator in a self-optimized load balancing algorithm. Simulation results for a backhaul constrained heterogeneous network illustrate how the correct load definition can guarantee a proper operation of the SON algorithm.Comment: Wireless Communications Letters, IEEE, 201

Adaptive stochastic radio access selection scheme for cellular-WLAN heterogeneous communication systems

This study proposes a novel adaptive stochastic radio access selection scheme for mobile users in heterogeneous cellular-wireless local area network (WLAN) systems. In this scheme, a mobile user located in dual coverage area randomly selects WLAN with probability of ω when there is a need for downloading a chunk of data. The value of ω is optimised according to the status of both networks in terms of network load and signal quality of both cellular and WLAN networks. An analytical model based on continuous time Markov chain is proposed to optimise the value of ω and compute the performance of proposed scheme in terms of energy efficiency, throughput, and call blocking probability. Both analytical and simulation results demonstrate the superiority of the proposed scheme compared with the mainstream network selection schemes: namely, WLAN-first and load balancing

Self Organizing strategies for enhanced ICIC (eICIC)

Small cells have been identified as an effective solution for coping with the important traffic increase that is expected in the coming years. But this solution is accompanied by additional interference that needs to be mitigated. The enhanced Inter Cell Interference Coordination (eICIC) feature has been introduced to address the interference problem. eICIC involves two parameters which need to be optimized, namely the Cell Range Extension (CRE) of the small cells and the ABS ratio (ABSr) which defines a mute ratio for the macro cell to reduce the interference it produces. In this paper we propose self-optimizing algorithms for the eICIC. The CRE is adjusted by means of load balancing algorithm. The ABSr parameter is optimized by maximizing a proportional fair utility of user throughputs. The convergence of the algorithms is proven using stochastic approximation theorems. Numerical simulations illustrate the important performance gain brought about by the different algorithms.Comment: Submitted to WiOpt 201

Cost-Effective Cache Deployment in Mobile Heterogeneous Networks

This paper investigates one of the fundamental issues in cache-enabled heterogeneous networks (HetNets): how many cache instances should be deployed at different base stations, in order to provide guaranteed service in a cost-effective manner. Specifically, we consider two-tier HetNets with hierarchical caching, where the most popular files are cached at small cell base stations (SBSs) while the less popular ones are cached at macro base stations (MBSs). For a given network cache deployment budget, the cache sizes for MBSs and SBSs are optimized to maximize network capacity while satisfying the file transmission rate requirements. As cache sizes of MBSs and SBSs affect the traffic load distribution, inter-tier traffic steering is also employed for load balancing. Based on stochastic geometry analysis, the optimal cache sizes for MBSs and SBSs are obtained, which are threshold-based with respect to cache budget in the networks constrained by SBS backhauls. Simulation results are provided to evaluate the proposed schemes and demonstrate the applications in cost-effective network deployment