Clustering-based interference management in densely deployed femtocell networks

Deploying femtoceUs underlaying macrocells is a promising way to improve the capacity and enhance the coverage of a cellular system. However, densely deployed femtocells in urban area also give rise to intra-tier interference and cross-tier issue that should be addressed properly in order to acquire the expected performance gain. In this paper, we propose an interference management scheme based on joint clustering and resource allocation for two-tier Orthogonal Frequency Division Multiplexing （OFDM）-based femtoeeU networks. We formulate an optimization task with the objective of maximizing the sum throughput of the femtocell users （FUs） under the consideration of intra-tier interference mitigation, while controlling the interference to the maeroeell user （MU） under its bearable threshold. The formulation problem is addressed by a two-stage procedure： femtoeells clustering and resource allocation. First, disjoint femtocell clusters with dynamic sizes and numbers are generated to minimize intra-tier interference. Then each cluster is taken as a resource allocation unit to share all subehannels, followed by a fast algorithm to distribute power among these subchannels. Simulation results show that our proposed schemes can improve the throughput of the FUs with acceptable complexity.

Adaptive Soft Frequency Reuse Scheme for In-building Dense Femtocell Networks

Femtocell networks have emerged as a key technology in residential, office building or hotspot deployments that can sig- nificantly fulfill high data demands in order to offioad indoor traffic from outdoor macro cells. However, as one of the major challenges, inter-femtocell interference gets worse in 3D in-building scenarios because of the presence of numerous interfering sources and then needs to be considered in the early network planning phase. The indoor network planning and optimization tool suite, Ranplan Small- cell~, makes accurate prediction of indoor wireless RF signal propagation possible to guide actual indoor femtocell deployments. In this paper, a new adaptive soft frequency reuse scheme in the dense femtocell networks is proposed, where multiple dense femtocells are classified into a number of groups according to the dominant interference strength to others, then the minimum subchannels with different frequency reuse factors for these groups are determined and transmit powers of the group- ing sub-channels are adaptively adjusted based on the strength to mitigate the mutual inter- ference. Simulation results show the proposed scheme yields great performance gains in terms of the spectrum efficiency relative to the legacy soft frequency reuse and universal fre- quency reuse.

QoE-Oriented Resource Allocation for Multiuser-Multiservice Femtocell Networks

The pursuit of high data rate and assurance of quality of experience(QoE) for end users represent the main goals of future wireless communication systems.By introducing MOS(Mean Opinion Score) based assessment models for different types of applications,this paper proposed novel QoE-oriented radio resource allocation(RRA) algorithms for multiuser-multiservice femtocell networks.An optimal QoE-oriented RRA strategy is first analyzed using time-sharing method which is applicable to best effort applications.RRA algorithms based on the cross-layer architecture are then proposed for all types of applications by considering parameters extracted from different layers of networking protocols.In the proposed algorithms,a priority mechanism is employed to ensure fairness.Simulation results show that the proposed algorithms can significantly improve the overall perceived quality from the users' perspective in comparison with traditional Quality of Service(QoS)oriented algorithms.

Performance analysis of a distributed power control algorithm for shared and split spectrum femtocell networks

In this paper, we study the performance of a distributed power adjustment algorithm for shared and split spectrum allocation setups. The theoretical analysis reveals that the convergence of the power control algorithm is guaranteed under different spectrum allocation schemes and the convergence rate is exponential. The performance analysis is also carried out via simulations which demonstrate the algorithm fairness under Jain＇s and Atkinkons＇ fairness indices.