The Impact on Full Duplex D2D Communication of Different LTE Transmission Techniques

© 2017 IEEE. To augment capacity of spectrum limited cellular systems, 3GPP proposed Licensed Assisted Access (LAA-LTE) while efforts are underway to standardize the standalone MulteFire (a small cell standalone version of LTE). LAA is expected to boost capacity of LTE via unlicensed spectrum (5GHz). On the other hand, recent advances in Self Interference Suppression (SIS) techniques allow radios to transmit and receive simultaneously on the same channel (i.e., in-band Full-Duplex, FD). As part of future wireless networks, Device-to-device (D2D) communications would find its great potential through this FD capability. However, due to high induced aggregate interference from FD and its impact on medium access probability, the rigorous and critical analysis is needed to find an optimum trade-off between performance efficiency and overheads. Using stochastic geometry and the random graph theory, in this article, we analyze the impact of different LTE network paradigms with HD/FD D2D devices. Moreover, the impact of state- of-the-art coexistence techniques (discontinuous transmission and listen-before-talk) recommended for LTE in unlicensed spectrum over HD/FD D2D network is also discussed. The analysis is supported with extensive simulation results that reveal insights of the coexistence mechanism efficiency employed by LTE, the impact of SIS and the cost of FD operation in D2D

Advanced Technologies for Energy Saving, Wireless Backhaul and Mobility Management in Heterogeneous Networks

In recent years, due to the increasing number of existing and new devices and applications, the wireless industry has experienced an explosion of data traffic usage. As a result, new wireless technologies have been developed to address the capacity crunch. Long-Term Evolution-Licensed Assisted Access (LTE-LAA) is developed to provide the tremendous capacity by extending LTE to 5 GHz unlicensed spectrum. Hyper-dense small cells deployment is another promising technique that can provide a ten to one hundred times capacity gain by bringing small cells closer to mobile user equipments [1]. In this thesis, I focus on three problems related to these two techniques. In Chapter 3, I present a novel activation and sleep mechanism for energy efficient small cell heterogeneous networks (HetNets). In the cell-edge area of a macrocell, the coverage area of a sleeping small-cell will be covered by a range of expanded small-cells nearby. In contrast, in areas close to the macrocell, user equipment (UE) associated with a sleeping small cell will be distributed to the macrocell. Furthermore, the enhanced inter-cell interference coordination (eICIC) technique is used to support range-expanded small cells to avoid Quality of Service (QoS) degradation. Under both hexagonal and stochastic geometry based models, it is demonstrated that the proposed sleeping mechanism significantly reduces the energy consumption of the network compared with the conventional methods while guaranteeing the QoS requirements. Small cells are currently connected to limited backhaul to reduce the deployment and operational costs. In Chapter 4, an optimisation scheme is proposed for small cells to utilise the bandwidth of macrocells as wireless backhaul. I provide the numerical analysis of the performance of both the targeted small cell and the whole network. In Chapter 5, the mobility management (MM) of heterogeneous and LTE-LAA networks are investigated. To avoid Ping-Pong handover (PPHO) and reduce handover failure rate in HetNets, a self-optimisation algorithm is developed to change the handover parameters of a base station automagically. Furthermore, the MM of LTE-LAA networks is analysed. A new handover mechanism is proposed for LTE-LAA networks. Compared with the conventional LTE networks, LTE-LAA networks trigger the handover not only by using UE mobility, but also by the availability of the unlicensed band. A comprehensive analysis of the handover triggering event and handover procedure is presented. Simulation results show that by introducing handover triggered by available unlicensed band, the ratio of handover to unlicensed spectrum has a significant improvement. Therefore, a noticeable enhanced throughput of UEs is achievable by LTE-LAA networks

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

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

Multi-channel Hybrid Access Femtocells: A Stochastic Geometric Analysis

For two-tier networks consisting of macrocells and femtocells, the channel access mechanism can be configured to be open access, closed access, or hybrid access. Hybrid access arises as a compromise between open and closed access mechanisms, in which a fraction of available spectrum resource is shared to nonsubscribers while the remaining reserved for subscribers. This paper focuses on a hybrid access mechanism for multi-channel femtocells which employ orthogonal spectrum access schemes. Considering a randomized channel assignment strategy, we analyze the performance in the downlink. Using stochastic geometry as technical tools, we model the distribution of femtocells as Poisson point process or Neyman-Scott cluster process and derive the distributions of signal-to-interference-plus-noise ratios, and mean achievable rates, of both nonsubscribers and subscribers. The established expressions are amenable to numerical evaluation, and shed key insights into the performance tradeoff between subscribers and nonsubscribers. The analytical results are corroborated by numerical simulations.Comment: This is the final version, which was accepted in IEEE Transactions on Communication

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future