Green Networking in Cellular HetNets: A Unified Radio Resource Management Framework with Base Station ON/OFF Switching

In this paper, the problem of energy efficiency in cellular heterogeneous networks (HetNets) is investigated using radio resource and power management combined with the base station (BS) ON/OFF switching. The objective is to minimize the total power consumption of the network while satisfying the quality of service (QoS) requirements of each connected user. We consider the case of co-existing macrocell BS, small cell BSs, and private femtocell access points (FAPs). Three different network scenarios are investigated, depending on the status of the FAPs, i.e., HetNets without FAPs, HetNets with closed FAPs, and HetNets with semi-closed FAPs. A unified framework is proposed to simultaneously allocate spectrum resources to users in an energy efficient manner and switch off redundant small cell BSs. The high complexity dual decomposition technique is employed to achieve optimal solutions for the problem. A low complexity iterative algorithm is also proposed and its performances are compared to those of the optimal technique. The particularly interesting case of semi-closed FAPs, in which the FAPs accept to serve external users, achieves the highest energy efficiency due to increased degrees of freedom. In this paper, a cooperation scheme between FAPs and mobile operator is also investigated. The incentives for FAPs, e.g., renewable energy sharing and roaming prices, enabling cooperation are discussed to be considered as a useful guideline for inter-operator agreements.Comment: 15 pages, 9 Figures, IEEE Transactions on Vehicular Technology 201

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

Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure

A dynamic almost blank subframe scheme for video streaming traffic model in heterogeneous networks

© 2015 IEEE. In heterogeneous network (HetNet), the coverage area of picocell is small due to transmission power difference between macro eNodeB (eNB) and pico eNB. As a result, the traffic load is distributed unequally which yields to macrocell overloading. In order to overcome this issue, cell range expansion (CRE) technique has been proposed. However, the CRE approach can affect the downlink signal quality of the offloaded users and then these users experience high downlink interference from macro eNB on their control and data channels. Therefore, such inter-cell interference coordination (ICIC) techniques are needed to realize the promised capacity and coverage. Enhanced ICIC (eICIC) is a time domain technique to mitigate interference in HetNets using almost blank subframes (ABSs). However, the static ABS value cannot support the dynamic changing of network conditions. In this paper, a dynamic ABS scheme is proposed based on Genetic Algorithm to find the best ABS value and ABS locations in a frame to mitigate interference problem between macrocell and picocells for video streaming traffic model. Exhaustive simulation results show that the proposed scheme can improve the system performance in terms of throughput, outage probability and delay

A Planning and Optimization Framework for Hybrid Ultra-Dense Network Topologies

The deployment of small cells has been a critical upgrade in Fourth Generation (4G) mobile networks as they provide macrocell traffic offloading gains, improved spectrum reuse and reduce coverage holes. The need for small cells will be even more critical in Fifth Generation (5G) networks due to the introduction of higher spectrum bands, which necessitate denser network deployments to support larger traffic volumes per unit area. A network densification scenario envisioned for evolved fourth and fifth generation networks is the deployment of Ultra-Dense Networks (UDNs) with small cell site densities exceeding 90 sites/km2 (or inter-site distances of less than 112 m). The careful planning and optimization of ultra-dense networks topologies have been known to significantly improve the achievable performance compared to completely random (unplanned) ultra-dense network deployments by various third-part stakeholders (e.g. home owners). However, these well-planned and optimized ultra-dense network deployments are difficult to realize in practice due to various constraints, such as limited or no access to preferred optimum small cell site locations in a given service area. The hybrid ultra-dense network topologies provide an interesting trade-off, whereby, an ultra-dense network may constitute a combination of operator optimized small cell deployments that are complemented by random small cell deployments by third-parties. In this study, an ultra-dense network multiobjective optimization framework and post-deployment power optimization approach are developed for realization and performance comparison of random, optimized and hybrid ultra-dense network topologies in a realistic urban case study area. The results of the case study demonstrate how simple transmit power optimization enable hybrid ultra-dense network topologies to achieve performance almost comparable to optimized topologies whilst also providing the convenience benefits of random small cell deployments

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

Connectivity Management for HetNets based on the Principles of Autonomicity and Context-Awareness

Στο περιβάλλον του Διαδικτύου του Μέλλοντος, η Πέμπτη γενιά (5G) δικτύων έχει ήδη αρχίσει να καθιερώνεται. Τα δίκτυα 5G αξιοποιούν υψηλότερες συχνότητες παρέχοντας μεγαλύτερο εύρος ζώνης, ενώ υποστηρίζουν εξαιρετικά μεγάλη πυκνότητα σε σταθμούς βάσης και κινητές συσκευές, σχηματίζοντας ένα περιβάλλον ετερογενών δικτύων, το οποίο στοχεύει στο να καλυφθούν οι απαιτήσεις της απόδοσης ως προς την μικρότερη δυνατή συνολική χρονοκαθυστέρηση και κατανάλωση ενέργειας. Η αποδοτική διαχείριση της συνδεσιμότητας σε ένα τόσο ετερογενές δικτυακό περιβάλλον αποτελεί ανοιχτό πρόβλημα, με σκοπό να υποστηρίζεται η κινητικότητα των χρηστών σε δίκτυα διαφορετικών τεχνολογιών και βαθμίδων, αντιμετωπίζοντας θέματα πολυπλοκότητας και διαλειτουργικότητας, υποστηρίζοντας τις απαιτήσεις των τρεχουσών εφαρμογών και των προτιμήσεων των χρηστών και διαχειρίζοντας ταυτόχρονα πολλαπλές δικτυακές διεπαφές. Η συλλογή, η μοντελοποίηση, η διεξαγωγή συμπερασμάτων και η κατανομή πληροφορίας περιεχομένου σε σχέση με δεδομένα αισθητήρων θα παίξουν κρίσιμο ρόλο σε αυτήν την πρόκληση. Με βάση τα παραπάνω, κρίνεται σκόπιμη η αξιοποίηση των αρχών της επίγνωσης περιεχομένου και της αυτονομικότητας, καθώς επιτρέπουν στις δικτυακές οντότητες να είναι ενήμερες του εαυτού τους και του περιβάλλοντός τους, καθώς και να αυτοδιαχειρίζονται τις λειτουργίες τους ώστε να πετυχαίνουν συγκεκριμένους στόχους. Επιπλέον, χρειάζεται ακριβής ποσοτική αξιολόγηση της απόδοσης λύσεων διαχείρισης της συνδεσιμότητας για ετερογενή δίκτυα, οι οποίες παρουσιάζουν διαφορετικές στρατηγικές επίγνωσης περιβάλλοντος, απαιτώντας μια μεθοδολογία που να είναι περιεκτική και γενικά εφαρμόσιμη ώστε να καλύπτει διαφορετικές προσεγγίσεις, καθώς οι υπάρχουσες μεθοδολογίες στην βιβλιογραφία είναι σχετικά περιορισμένες. Tο σύνολο της μελέτης επικεντρώνεται σε δύο θεματικούς άξονες. Στο πρώτο θεματικό μέρος της διατριβής, αναλύεται ο ρόλος της επίγνωσης περιβάλλοντος και της αυτονομικότητας, σε σχέση με την διαχείριση της συνδεσιμότητας, αναπτύσσοντας ένα πλαίσιο ταξινόμησης και κατηγοριοποίησης, επεκτείνοντας την τρέχουσα βιβλιογραφία. Με βάση το προαναφερθέν πλαίσιο, ταξινομήθηκαν και αξιολογήθηκαν λύσεις για την υποστήριξη της κινητικότητας σε ετερογενή δίκτυα, οι οποίες δύνανται να θεωρηθούν ότι παρουσιάζουν επίγνωση περιβάλλοντος και αυτο-διαχειριστικά χαρακτηριστικά. Επιπλέον, μελετήθηκε κατά πόσον οι αποφάσεις που λαμβάνονται ως προς την επιλογή του κατάλληλου δικτύου, σύμφωνα με την κάθε λύση, είναι αποτελεσματικές και προτάθηκαν τρόποι βελτιστοποίησης των υπαρχουσών αρχιτεκτονικών, καθώς και προτάσεων προς περαιτέρω ανάπτυξη σχετικών μελλοντικών λύσεων. Στο δεύτερο θεματικό μέρος της διατριβής, αναπτύχθηκε μια ευέλικτη αναλυτική μεθοδολογία, περιλαμβάνοντας όλους τους παράγοντες που μπορούν να συνεισφέρουν στην συνολική χρονοκαθυστέρηση, λαμβάνοντας υπόψιν την σηματοδοσία, την επεξεργαστική επιβάρυνση και την συμφόρηση (μελέτη ουράς), επεκτείνοντας την τρέχουσα βιβλιογραφία. Η μεθοδολογία είναι περιεκτική, ενώ ταυτόχρονα προσφέρει κλειστού τύπου λύσεις και έχει την δυνατότητα να προσαρμόζεται σε διαφορετικές προσεγγίσεις. Προς απόδειξη αυτού, εφαρμόσαμε την μεθοδολογία σε δύο λύσεις με διαφορετική στρατηγική επίγνωσης περιβάλλοντος (μια μεταδραστική και μια προδραστική). Και για τις δύο προσεγγίσεις, τα αναλυτικά αποτελέσματα επιβεβαιώθηκαν από προσομοιώσεις, επιβεβαιώνοντας την αποτελεσματικότητα και την ακρίβεια της αναλυτικής μεθοδολογίας. Επιπλέον, αποδείχθηκε ότι η προδραστική προσέγγιση εμφανίζει καλύτερη απόδοση ως προς την συνολική χρονοκαθυστέρηση, ενώ χρειάζεται σημαντικά λιγότερους επεξεργαστικούς πόρους, παρουσιάζοντας πιθανά οφέλη και στην συνολική ενεργειακή κατανάλωση και στα λειτουργικά και κεφαλαιουχικά κόστη (OPEX και CAPEX)