Ali Imran

A Survey of Self Organisation in Future Cellular Networks

This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks.

Challenges in 5G: how to empower SON with big data for enabling 5G

While an al dente character of 5G is yet to emerge, network densification, miscellany of node types, split of control and data plane, network virtualization, heavy and localized cache, infrastructure sharing, concurrent operation at multiple frequency bands, simultaneous use of different medium access control and physical layers, and flexible spectrum allocations can be envisioned as some of the potential ingredients of 5G. It is not difficult to prognosticate that with such a conglomeration of technologies, the complexity of operation and OPEX can become the biggest challenge in 5G. To cope with similar challenges in the context of 3G and 4G networks, recently, self-organizing networks, or SONs, have been researched extensively. However, the ambitious quality of experience requirements and emerging multifarious vision of 5G, and the associated scale of complexity and cost, demand a significantly different, if not totally new, approach toward SONs in order to make 5G technically as well as financially feasible. In this article we first identify what challenges hinder the current self-optimizing networking paradigm from meeting the requirements of 5G. We then propose a comprehensive framework for empowering SONs with big data to address the requirements of 5G. Under this framework we first characterize big data in the context of future mobile networks, identifying its sources and future utilities. We then explicate the specific machine learning and data analytics tools that can be exploited to transform big data into the right data that provides a readily useable knowledge base to create end-to-end intelligence of the network. We then explain how a SON engine can build on the dynamic models extractable from the right data. The resultant dynamicity of a big data empowered SON (BSON) makes it more agile and can essentially transform the SON from being a reactive to proactive paradigm and hence act as a key enabler for 5Gs extremely low latency requirements. Finally, we demonstrate the key concepts of our proposed BSON framework through a case study of a problem that the classic 3G/4G SON fails to solve.

Control-Data Separation Architecture for Cellular Radio Access Networks: A Survey and Outlook

Conventional cellular systems are designed to ensure ubiquitous coverage with an always present wireless channel irrespective of the spatial and temporal demand of service. This approach raises several problems due to the tight coupling between network and data access points, as well as the paradigm shift towards data-oriented services, heterogeneous deployments and network densification. A logical separation between control and data planes is seen as a promising solution that could overcome these issues, by providing data services under the umbrella of a coverage layer. This article presents a holistic survey of existing literature on the control-data separation architecture (CDSA) for cellular radio access networks. As a starting point, we discuss the fundamentals, concepts, and general structure of the CDSA. Then, we point out limitations of the conventional architecture in futuristic deployment scenarios. In addition, we present and critically discuss the work that has been done to investigate potential benefits of the CDSA, as well as its technical challenges and enabling technologies. Finally, an overview of standardisation proposals related to this research vision is provided.

A Cell Outage Management Framework for Dense Heterogeneous Networks

In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes-a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., k-nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner.

Black Tea Polyphenols: A Mechanistic Treatise

Dietary interventions are among the emerging trends to curtail physiological malfunctioning like cancer, diabetes, cardiac complications, etc. The essence of phytonutrients has developed the concept of nutraceuticals at the junction of diet health linkages. In this context, theaflavin & thearubigins are the oxidized derivatives of black tea catechins during fermentation having nutraceutical potential owing to esterification of hydroxyl ring with digallate esters. Theaflavin may influence activation of transcription factors such as NFnB or AP-1 that ultimately hinder the formation of nitric oxide expression gene. Likewise, black tea contains a unique amino acid theanine acts as neurotransmitter owing to its ability to cross the blood–brain barrier. Moreover, it boasts immunity by enhancing the disease-fighting ability of gamma delta T cells. Theaflavin & thearubigins act as safeguard against oxidative stress thereby effective in the cardiac functioning. The mechanistic approach of these antioxidants is likely to be associated with inhibition of redox sensitive transcription factors & pro-oxidant enzymes such as xanthine oxidase or nitric oxide synthase. However, their involvement in antioxidative enzyme induction as in glutathione-S-transferases is also well documented. They act as curative agent against numerous pathological disorders by disrupting the electron chain thus inhibiting the progression of certain ailments. Black tea polyphenols established themselves as strong antioxidants due to their standard one-electron potential, and their vitality is dependent on the concentration of polyphenols and pH for their inclusive execution. Present review is an attempt to enrich the readers regarding the health promoting aspects of black tea polyphenols. Concomitantly, it needs core attention of researchers for the exploitations of black tea flavanols as an important dietary constituent for the vulnerable segment.

A novel Self Organizing framework for adaptive Frequency Reuse and Deployment in future cellular networks

Recent research on Frequency Reuse (FR) schemes for OFDM/OFDMA based cellular networks (OCN) suggest that a single fixed FR cannot be optimal to cope with spatiotemporal dynamics of traffic and cellular environments in a spectral and energy efficient way. To address this issue this paper introduces a novel Self Organizing framework for adaptive Frequency Reuse and Deployment (SO-FRD) for future OCN including both cellular (e.g. LTE) and relay enhanced cellular networks (e.g. LTE Advance). In this paper, an optimization problem is first formulated to find optimal frequency reuse factor, number of sectors per site and number of relays per site. The goal is designed as an adaptive utility function which incorporates three major system objectives; 1) spectral efficiency 2) fairness, and 3) energy efficiency. An appropriate metric for each of the three constituent objectives of utility function is then derived. Solution is provided by evaluating these metrics through a combination of analysis and extensive system level simulations for all feasible FRDs. Proposed SO-FRD framework uses this flexible utility function to switch to particular FRD strategy, which is suitable for systems current state according to predefined or self learned performance criterion. The proposed metrics capture the effect of all major optimization parameters like frequency reuse factor, number of sectors and relay per site, and adaptive coding and modulation. Based on the results obtained, interesting insights into the tradeoff among these factors is also provided.

Mobility prediction for handover management in cellular networks with control/data separation

In research community, a new radio access network architecture with a logical separation between control plane (CP) and data plane (DP) has been proposed for future cellular systems. It aims to overcome limitations of the conventional architecture by providing high data rate services under the umbrella of a coverage layer in a dual connection mode. This configuration could provide significant savings in signalling overhead. In particular, mobility robustness with minimal handover (HO) signalling is considered as one of the most promising benefits of this architecture. However, the DP mobility remains an issue that needs to be investigated. We consider predictive DP HO management as a solution that could minimise the out-of-band signalling related to the HO procedure. Thus we propose a mobility prediction scheme based on Markov Chains. The developed model predicts the users trajectory in terms of a HO sequence in order to minimise the interruption time and the associated signalling when the HO is triggered. Depending on the prediction accuracy, numerical results show that the predictive HO management strategy could significantly reduce the signalling cost as compared with the conventional non-predictive mechanism.

Self organising cloud cells: a resource efficient network densification strategy

Network densification is envisioned as the key enabler for 2020 vision that requires cellular systems to grow in capacity by hundreds of times to cope with unprecedented traffic growth trends being witnessed since advent of broadband on the move. However, increased energy consumption and complex mobility management associated with network densifications remain as the two main challenges to be addressed before further network densification can be exploited on a wide scale. In the wake of these challenges, this paper proposes and evaluates a novel dense network deployment strategy for increasing the capacity of future cellular systems without sacrificing energy efficiency and compromising mobility performance. Our deployment architecture consists of smart small cells, called cloud nodes, which provide data coverage to individual users on a demand bases while taking into account the spatial and temporal dynamics of user mobility and traffic. The decision to activate the cloud nodes, such that certain performance objectives at system level are targeted, is carried out by the overlaying macrocell based on a fuzzy-logic framework. We also compare the proposed architecture with conventional macrocell only deployment and pure microcell-based dense deployment in terms of blocking probability, handover probability and energy efficiency and discuss and quantify the trade-offs therein.©2014 The Authors. Transactions on Emerging Telecommunications Technologies published by John Wiley & Sons, Ltd.

Use of learning, game theory and optimization as biomimetic approaches for Self-Organization in macro-femtocell coexistence

In this paper, we present the use of several Biomimetic approaches for Self Organization (SO) in heterogeneous scenarios where macrocell and femtocell networks coexist. Mainly these approaches are categorized in indirect biomimetics and direct biomimetics. Under indirect biomimetics we discuss 1) emerging paradigms in learning theory and 2) game theory for their potential to enable SO solutions in heterogeneous networks. By means of numerical results we demonstrate the pros and cons of these indirect biomimetic approaches for designing SO in macro-femto coexistence scenarios. Furthermore, we demonstrate the use of direct biomimetic approaches for designing SO by exploiting one to one mapping between a natural SO system and our system model for heterogeneous networks based on Outdoor Fixed Relays (OFR). Numerical results show that the proposed analytical solution can enhance wireless backhaul capacity of the OFR based femtocells by adapting the macro base station (BS) antenna tilts in a distributed and self organizing manner.

Data-driven analytics for automated cell outage detection in Self-Organizing Networks

In this paper, we address the challenge of autonomous cell outage detection (COD) in Self-Organizing Networks (SON). COD is a pre-requisite to trigger fully automated self-healing recovery actions following cell outages or network failures. A special case of cell outage, referred to as Sleeping Cell (SC) remains particularly challenging to detect in state-of-the-art SON, since it triggers no alarms for Operation and Maintenance (O&M) entity. Consequently, no SON compensation function can be launched unless site visits or drive tests are performed, or complaints are received by affected customers. To address this issue, we present and evaluates a COD framework, which is based on minimization of drive test (MDT) reports, a functionality recently specified in third generation partnership project (3GPP) Release 10, for LTE Networks. Our proposed framework aims to detect cell outages in an autonomous fashion by first pre-processing the MDT measurements using multidimensional scaling method and further employing it together with machine learning algorithms to detect and localize anomalous network behaviour. We validate and demonstrate the effectiveness of our proposed solution using the data obtained from simulating the network under various operational settings.