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 case

Joint Multi-Cell Resource Allocation Using Pure Binary-Integer Programming for LTE Uplink

Due to high system capacity requirement, 3GPP Long Term Evolution (LTE) is likely to adopt frequency reuse factor 1 at the cost of suffering severe inter-cell interference (ICI). One of combating ICI strategies is network cooperation of resource allocation (RA). For LTE uplink RA, requiring all the subcarriers to be allocated adjacently complicates the RA problem greatly. This paper investigates the joint multi-cell RA problem for LTE uplink. We model the uplink RA and ICI mitigation problem using pure binary-integer programming (BIP), with integrative consideration of all users' channel state information (CSI). The advantage of the pure BIP model is that it can be solved by branch-and-bound search (BBS) algorithm or other BIP solving algorithms, rather than resorting to exhaustive search. The system-level simulation results show that it yields 14.83% and 22.13% gains over single-cell optimal RA in average spectrum efficiency and 5th percentile of user throughput, respectively.Comment: Accepted to IEEE Vehicular Technology Conference (VTC Spring), Seoul, Korea, May, 201

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Dynamic Radio Cooperation for Downlink Cloud-RANs with Computing Resource Sharing

A novel dynamic radio-cooperation strategy is proposed for Cloud Radio Access Networks (C-RANs) consisting of multiple Remote Radio Heads (RRHs) connected to a central Virtual Base Station (VBS) pool. In particular, the key capabilities of C-RANs in computing-resource sharing and real-time communication among the VBSs are leveraged to design a joint dynamic radio clustering and cooperative beamforming scheme that maximizes the downlink weighted sum-rate system utility (WSRSU). Due to the combinatorial nature of the radio clustering process and the non-convexity of the cooperative beamforming design, the underlying optimization problem is NP-hard, and is extremely difficult to solve for a large network. Our approach aims for a suboptimal solution by transforming the original problem into a Mixed-Integer Second-Order Cone Program (MI-SOCP), which can be solved efficiently using a proposed iterative algorithm. Numerical simulation results show that our low-complexity algorithm provides close-to-optimal performance in terms of WSRSU while significantly outperforming conventional radio clustering and beamforming schemes. Additionally, the results also demonstrate the significant improvement in computing-resource utilization of C-RANs over traditional RANs with distributed computing resources.Comment: 9 pages, 6 figures, accepted to IEEE MASS 201