A novel load-balancing scheme for cellular-WLAN heterogeneous systems with cell-breathing technique

This paper proposes a novel load-balancing scheme for an operator-deployed cellular-wireless local area network (WLAN) heterogeneous network (HetNet), where the user association is controlled by employing a cell-breathing technique for the WLAN network. This scheme eliminates the complex coordination and additional signaling overheads between the users and the network by allowing the users to simply associate with the available WLAN networks similar to the traditional WLAN-first association, without making complex association decisions. Thus, this scheme can be easily implemented in an existing operator-deployed cellular-WLAN HetNet. The performance of the proposed scheme is evaluated in terms of load distribution between cellular and WLAN networks, user fairness, and system throughput, which demonstrates the superiority of the proposed scheme in load distribution and user fairness, while optimizing the system throughput. In addition, a cellular-WLAN interworking architecture and signaling procedures are proposed for implementing the proposed load-balancing schemes in an operator-deployed cellular-WLAN HetNet

Energy efficiency in heterogeneous wireless access networks

In this article, we bring forward the important aspect of energy savings in wireless access networks. We specifically focus on the energy saving opportunities in the recently evolving heterogeneous networks (HetNets), both Single- RAT and Multi-RAT. Issues such as sleep/wakeup cycles and interference management are discussed for co-channel Single-RAT HetNets. In addition to that, a simulation based study for LTE macro-femto HetNets is presented, indicating the need for dynamic energy efficient resource management schemes. Multi-RAT HetNets also come with challenges such as network integration, combined resource management and network selection. Along with a discussion on these challenges, we also investigate the performance of the conventional WLAN-first network selection mechanism in terms of energy efficiency (EE) and suggest that EE can be improved by the application of intelligent call admission control policies

Distributed Cognitive RAT Selection in 5G Heterogeneous Networks: A Machine Learning Approach

The leading role of the HetNet (Heterogeneous Networks) strategy as the key Radio Access Network (RAN) architecture for future 5G networks poses serious challenges to the current cell selection mechanisms used in cellular networks. The max-SINR algorithm, although effective historically for performing the most essential networking function of wireless networks, is inefficient at best and obsolete at worst in 5G HetNets. The foreseen embarrassment of riches and diversified propagation characteristics of network attachment points spanning multiple Radio Access Technologies (RAT) requires novel and creative context-aware system designs. The association and routing decisions, in the context of single-RAT or multi-RAT connections, need to be optimized to efficiently exploit the benefits of the architecture. However, the high computational complexity required for multi-parametric optimization of utility functions, the difficulty of modeling and solving Markov Decision Processes, the lack of guarantees of stability of Game Theory algorithms, and the rigidness of simpler methods like Cell Range Expansion and operator policies managed by the Access Network Discovery and Selection Function (ANDSF), makes neither of these state-of-the-art approaches a favorite. This Thesis proposes a framework that relies on Machine Learning techniques at the terminal device-level for Cognitive RAT Selection. The use of cognition allows the terminal device to learn both a multi-parametric state model and effective decision policies, based on the experience of the device itself. This implies that a terminal, after observing its environment during a learning period, may formulate a system characterization and optimize its own association decisions without any external intervention. In our proposal, this is achieved through clustering of appropriately defined feature vectors for building a system state model, supervised classification to obtain the current system state, and reinforcement learning for learning good policies. This Thesis describes the above framework in detail and recommends adaptations based on the experimentation with the X-means, k-Nearest Neighbors, and Q-learning algorithms, the building blocks of the solution. The network performance of the proposed framework is evaluated in a multi-agent environment implemented in MATLAB where it is compared with alternative RAT selection mechanisms

An Innovative RAN Architecture for Emerging Heterogeneous Networks: The Road to the 5G Era

The global demand for mobile-broadband data services has experienced phenomenal growth over the last few years, driven by the rapid proliferation of smart devices such as smartphones and tablets. This growth is expected to continue unabated as mobile data traffic is predicted to grow anywhere from 20 to 50 times over the next 5 years. Exacerbating the problem is that such unprecedented surge in smartphones usage, which is characterized by frequent short on/off connections and mobility, generates heavy signaling traffic load in the network signaling storms . This consumes a disproportion amount of network resources, compromising network throughput and efficiency, and in extreme cases can cause the Third-Generation (3G) or 4G (long-term evolution (LTE) and LTE-Advanced (LTE-A)) cellular networks to crash. As the conventional approaches of improving the spectral efficiency and/or allocation additional spectrum are fast approaching their theoretical limits, there is a growing consensus that current 3G and 4G (LTE/LTE-A) cellular radio access technologies (RATs) won\u27t be able to meet the anticipated growth in mobile traffic demand. To address these challenges, the wireless industry and standardization bodies have initiated a roadmap for transition from 4G to 5G cellular technology with a key objective to increase capacity by 1000Ã? by 2020 . Even though the technology hasn\u27t been invented yet, the hype around 5G networks has begun to bubble. The emerging consensus is that 5G is not a single technology, but rather a synergistic collection of interworking technical innovations and solutions that collectively address the challenge of traffic growth. The core emerging ingredients that are widely considered the key enabling technologies to realize the envisioned 5G era, listed in the order of importance, are: 1) Heterogeneous networks (HetNets); 2) flexible backhauling; 3) efficient traffic offload techniques; and 4) Self Organizing Networks (SONs). The anticipated solutions delivered by efficient interworking/ integration of these enabling technologies are not simply about throwing more resources and /or spectrum at the challenge. The envisioned solution, however, requires radically different cellular RAN and mobile core architectures that efficiently and cost-effectively deploy and manage radio resources as well as offload mobile traffic from the overloaded core network. The main objective of this thesis is to address the key techno-economics challenges facing the transition from current Fourth-Generation (4G) cellular technology to the 5G era in the context of proposing a novel high-risk revolutionary direction to the design and implementation of the envisioned 5G cellular networks. The ultimate goal is to explore the potential and viability of cost-effectively implementing the 1000x capacity challenge while continuing to provide adequate mobile broadband experience to users. Specifically, this work proposes and devises a novel PON-based HetNet mobile backhaul RAN architecture that: 1) holistically addresses the key techno-economics hurdles facing the implementation of the envisioned 5G cellular technology, specifically, the backhauling and signaling challenges; and 2) enables, for the first time to the best of our knowledge, the support of efficient ground-breaking mobile data and signaling offload techniques, which significantly enhance the performance of both the HetNet-based RAN and LTE-A\u27s core network (Evolved Packet Core (EPC) per 3GPP standard), ensure that core network equipment is used more productively, and moderate the evolving 5G\u27s signaling growth and optimize its impact. To address the backhauling challenge, we propose a cost-effective fiber-based small cell backhaul infrastructure, which leverages existing fibered and powered facilities associated with a PON-based fiber-to-the-Node/Home (FTTN/FTTH)) residential access network. Due to the sharing of existing valuable fiber assets, the proposed PON-based backhaul architecture, in which the small cells are collocated with existing FTTN remote terminals (optical network units (ONUs)), is much more economical than conventional point-to-point (PTP) fiber backhaul designs. A fully distributed ring-based EPON architecture is utilized here as the fiber-based HetNet backhaul. The techno-economics merits of utilizing the proposed PON-based FTTx access HetNet RAN architecture versus that of traditional 4G LTE-A\u27s RAN will be thoroughly examined and quantified. Specifically, we quantify the techno-economics merits of the proposed PON-based HetNet backhaul by comparing its performance versus that of a conventional fiber-based PTP backhaul architecture as a benchmark. It is shown that the purposely selected ring-based PON architecture along with the supporting distributed control plane enable the proposed PON-based FTTx RAN architecture to support several key salient networking features that collectively significantly enhance the overall performance of both the HetNet-based RAN and 4G LTE-A\u27s core (EPC) compared to that of the typical fiber-based PTP backhaul architecture in terms of handoff capability, signaling overhead, overall network throughput and latency, and QoS support. It will also been shown that the proposed HetNet-based RAN architecture is not only capable of providing the typical macro-cell offloading gain (RAN gain) but also can provide ground-breaking EPC offloading gain. The simulation results indicate that the overall capacity of the proposed HetNet scales with the number of deployed small cells, thanks to LTE-A\u27s advanced interference management techniques. For example, if there are 10 deployed outdoor small cells for every macrocell in the network, then the overall capacity will be approximately 10-11x capacity gain over a macro-only network. To reach the 1000x capacity goal, numerous small cells including 3G, 4G, and WiFi (femtos, picos, metros, relays, remote radio heads, distributed antenna systems) need to be deployed indoors and outdoors, at all possible venues (residences and enterprises)

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

Towards UAV Assisted 5G Public Safety Network

Ensuring ubiquitous mission-critical public safety communications (PSC) to all the first responders in the public safety network is crucial at an emergency site. The first responders heavily rely on mission-critical PSC to save lives, property, and national infrastructure during a natural or human-made emergency. The recent advancements in LTE/LTE-Advanced/5G mobile technologies supported by unmanned aerial vehicles (UAV) have great potential to revolutionize PSC. However, limited spectrum allocation for LTE-based PSC demands improved channel capacity and spectral efficiency. An additional challenge in designing an LTE-based PSC network is achieving at least 95% coverage of the geographical area and human population with broadband rates. The coverage requirement and efficient spectrum use in the PSC network can be realized through the dense deployment of small cells (both terrestrial and aerial). However, there are several challenges with the dense deployment of small cells in an air-ground heterogeneous network (AG-HetNet). The main challenges which are addressed in this research work are integrating UAVs as both aerial user and aerial base-stations, mitigating inter-cell interference, capacity and coverage enhancements, and optimizing deployment locations of aerial base-stations. First, LTE signals were investigated using NS-3 simulation and software-defined radio experiment to gain knowledge on the quality of service experienced by the user equipment (UE). Using this understanding, a two-tier LTE-Advanced AG-HetNet with macro base-stations and unmanned aerial base-stations (UABS) is designed, while considering time-domain inter-cell interference coordination techniques. We maximize the capacity of this AG-HetNet in case of a damaged PSC infrastructure by jointly optimizing the inter-cell interference parameters and UABS locations using a meta-heuristic genetic algorithm (GA) and the brute-force technique. Finally, considering the latest specifications in 3GPP, a more realistic three-tier LTE-Advanced AG-HetNet is proposed with macro base-stations, pico base-stations, and ground UEs as terrestrial nodes and UABS and aerial UEs as aerial nodes. Using meta-heuristic techniques such as GA and elitist harmony search algorithm based on the GA, the critical network elements such as energy efficiency, inter-cell interference parameters, and UABS locations are all jointly optimized to maximize the capacity and coverage of the AG-HetNet

Analytical Performance Evaluation of Cooperative and Multi-Radio Concepts in Emerging Wireless Networks

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