Performance Analysis of UserCentric SBS Deployment with Load Balancing in Heterogeneous Cellular Networks: A Thomas Cluster Process Approach Abstract   In conventional heterogeneous cellular networks (HCNets), the locations of user equipments (UEs) and base stations (BSs) are modeled randomly using two different homogeneous Poisson point processes (PPPs). However, this might not be a suitable assumption in case of UE distribution because UE density is not uniform everywhere in HCNets. Keeping in view the existence of nonuniform UEs, the small base stations (SBSs) are assumed to be deployed in the areas with high UE density, which results in correlation between UEs and BS locations. In this paper, we analyse the performance of HCNets with nonuniform UE deployment containing a union of clustered and uniform UE sets. The clustered UEs are considered to be modeled according to Thomas cluster process, and random UEs are assumed to be deployed via homogeneous PPP. The SBSs are considered to be deployed at the center of the UE clusters, which results in usercentric SBS deployment. We derive outage probability and rate coverage of the proposed model. Furthermore, to improve the network performance, the impact of association biasing is also assumed. Our results show that the usercentric SBS deployment outperforms the conventional HCNets model. Increase in association bias upto a certain value results in performance improvement of the proposed usercentric HCNet.

Joint User Association and Resource Allocation in Heterogeneous Cellular Networks: Comparison of Two Modeling Approaches The performance of different combinations of user association (UA) and resource allocation (RA) in heterogeneous cellular networks has been extensively studied using a classic modeling approach based on system snapshots. There have been also many studies focusing on the dynamics of the system using queueing models. These modeling approaches are rarely compared with each other though they each bring different insights to the design problem. In this paper, we consider a queueing modelbased approach to study the interplay of UA and RA, and compare the results to those obtained using snapshot models. Specifically, we formulate three different joint UA and RA optimization problems corresponding to the following three performance metrics: the maximum achievable arrival rate, the average system delay, and the maximum peruser delay. These problems are nonconvex integer programs. We have therefore developed numerical techniques to compute either their exact solutions or tight lower bounds. We obtain results for different combinations of RA and UA schemes, and compare the trends with those obtained via the snapshot approach. The trends on RA are very similar, which we take as a crossvalidation of the two modeling approaches for this kind of problem. The trends on user association are somewhat different which indicates a lack of robustness of the results and the need for a careful validation of UA models.