Research On Interference Coordination Technologies For Dense Small Cell Networks

Mobile traffic demand has experienced an explosive growth in the past decades,and this growth trend will continue in the next few decades with the proliferation of smart devices and the diversification of mobile services.Unfortunately,the forth generation(4G)mobile networks,which have already been commercially deployed,cannot satisfy such inevitably increasing traffic demand.Therefore,the next generation mobile networks,which is commonly known as 5G,should be developed to support 1000 times increased data volume per area,higher spectral efficiency,higher energy efficiency,higher peak date rate and lower latency,and to meet various demands of different users.Among the envisioned technologies of 5G,network densification has drawn great attention from both academia and industry,since it has the potential to increase the capacity and spectrum utilization of the network linearly with the increasing of the number of deployed cells.In dense small cell network(DSCN),small base station(SBS)is overlaid in the range of macro base station(MBS),and the MBS and the SBSs are operated on orthogonal frequency bands.However,due to the small base station shared the spectrum,and reducing the cell size and deploying more low-cost SBS in the coverage area bring about serious interference from neighbor cells with the desired signal strength increasing.Not only that,although the SBS itself is a low power node,but with the large number of SBS deployed,the network power consumption problem can't be ignored.In this thesis,we focus on the interference coordination problem in DSCN,and optimize the power consumption and network capacity from the perspective of resource allocation and power control.The goal is to reduce the energy consumption in the network and to improve network capacity under the premise of satisfying the quality of service(QoS).The main contributions are as follows.In the aspect of power consumption optimization,we study the interference coordination problem of optimal power consumption in DSCN,and the interference between base stations can be reduced by combining the power control and channel resource allocation to minimize the power consumption in the network.As the SBS has the characteristics of random deployment and no plan,the existing hexagonal cellular model can't accurately reflect the deployment of SBS in DSCNs.And for the existing energy consumption research,most of the schemes chose to turn on/off SBS which is light load,dynamically.But this will increase the user outrage probability,delay and bring user re-access problem.So we focus on the deployment characteristics of SBS using poisson point processes(PPP)to model the SBS deployment,and then analyze the impact of the amount of power and resources allocated to the user on the average user rate.According to the analysis results,we allocate proper power and resource to ensure user's QoS while reduce energy consumption.The simulation results show that our scheme can effectively reduce the power consumption in the network compared with the traditional scheme.In the aspect of network capacity optimization,we study the interference coordination problem of optimal network throughput in DSCN.Most of traditional inter-cell interference coordination(ICIC)schemes use almost blank subframes(ABS)to completely avoid the inter-cell interference.But in fact,we observe that users can suffer a certain amount of interference as long as their quality of service(QoS)is satisfied.Not only that,the existing ABS mechanism using a blank spectrum of resources to reduce the interference between the base station,resulting in waste of spectrum resources.Therefore,we can improve the system throughput by reducing the transmission power instead of using ABS.Based on the above fact,we propose an interference coordination mechanism based on low power ABS(LP-ABS)scheme in DSCNs with the objective to maximize the downlink system throughput as well as guarantee users' QoS.In the proposed scheme,each SBS adopts an adaptive ABS ratio according to its traffic load condition.Then,a Q-learning based algorithm is proposed to get the optimal transmission power of the ABS subframes.Simulation results show that the significant advantages of the proposed scheme over tradition ICIC method.