Uplink CoMP Capability Improvements In Heterogeneous Cellular Networks

LTE-Advanced meets the challenge raised by powerful, mobile devices and bandwidth-hungry applications by investing in solutions such as carrier aggregation, higher order MIMO, relay nodes and Coordinated Multipoint (CoMP) transmission/reception. The latter, in particular, is envisioned to be one of the most important techniques in LTE-Advanced to improve the throughput and functionality of cell borders. CoMP allows users to have multiple data transmission and reception from/toward multiple cooperating eNodeBs (eNBs), increasing the utilization factor of the network. Resource allocation in the uplink is especially beneficial because more sophisticated algorithms can leverage the availability of additional connection points where the signal from the User Equipment (UE) is processed, ultimately providing UEs with increased throughput. Additionally, a significant part of the interference caused by neighboring cells can be seen as a useful received signal thanks to CoMP, provided those cells are part of the Coordinated Reception Point (CRP) set. This is especially important in critical regions, in terms of interference, like cell edges. Finally, in the case of joint multi-cell scheduling, CoMP introduces a reduction in the backhaul load by requiring only scheduling data to be transferred between coordinated eNBs. Arguably, CoMP is most appealing in the uplink direction since it does not require UE modifications: indeed, users need not be aware that there is any kind of cooperation among receiving eNBs. UEs are merely scheduled for transmission on a set of frequencies that happens to be split among different eNBs, although they still retain standard signaling channels through only one of these eNBs, usually referred to as the serving cell. In this work we focus on uplink CoMP from a system point of view. Specifically, we are interested in comparing through simulation the performance of uplink CoMP in various scenarios with different user participation to CoMP transmissions and CoMP margins. Some works have already investigated uplink CoMP both in simulation and through field trials. Our contribution confirms the findings of previous works as far as the throughput gain for edge users is concerned, but introduces three novel observations that can spur future investigations on CoMP systems, in both downlink and uplink regime, and lead to the design of new resource allocation algorithms: • We look at Heterogeneous scenario where there is no restriction in the type of cells that can be in the CRP set, but simultaneously we introduce clustering option included limited number of Macro and small cells to be acted independently from other clusters in CoMP process. • We introduce a parameter called CoMP Pool Percentage (CPP), which quantifies the fraction of PRBs that are reserved for UEs using a specific eNB as CRP (out of the resources nominally available to that eNB). Our algorithm show that the setting of CPP must be carefully gauged depending on the number of CoMP users and the scenario. • We proposed an innovative dynamic algorithm to make decision of the CPP value in order to improve the gain for CoMP users while considering the whole network gain. Combination of the three above mentioned routine and algorithms, according to simulations, confirms an average gain of at least 20% percent for the CoMP users, (average over various population) locating in cell boarder, while the whole network benefits by average of 5% gain for all the users (see results section). The algorithm also guarantees more gain for more values of CoMP margin. In other words, the more the population of CoMP users locating in cell borders the more would be the achievable gain. Objectives of this PhD thesis are concluded as follows: • Design a Network-level simulator whose features are close to a real LTE network, including advanced capabilities and innovations • Observe the response of the network to parameters changes • Increase the throughput gain (using CoMP vs. non using it) and the quality of service • Design and evaluate the Novel Scheduling Algorithm • Compare the obtained results with real cases