Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Sustainable scheduling policies for radio access networks based on LTE technology

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyIn the LTE access networks, the Radio Resource Management (RRM) is one of the most important modules which is responsible for handling the overall management of radio resources. The packet scheduler is a particular sub-module which assigns the existing radio resources to each user in order to deliver the requested services in the most efficient manner. Data packets are scheduled dynamically at every Transmission Time Interval (TTI), a time window used to take the user’s requests and to respond them accordingly. The scheduling procedure is conducted by using scheduling rules which select different users to be scheduled at each TTI based on some priority metrics. Various scheduling rules exist and they behave differently by balancing the scheduler performance in the direction imposed by one of the following objectives: increasing the system throughput, maintaining the user fairness, respecting the Guaranteed Bit Rate (GBR), Head of Line (HoL) packet delay, packet loss rate and queue stability requirements. Most of the static scheduling rules follow the sequential multi-objective optimization in the sense that when the first targeted objective is satisfied, then other objectives can be prioritized. When the targeted scheduling objective(s) can be satisfied at each TTI, the LTE scheduler is considered to be optimal or feasible. So, the scheduling performance depends on the exploited rule being focused on particular objectives. This study aims to increase the percentage of feasible TTIs for a given downlink transmission by applying a mixture of scheduling rules instead of using one discipline adopted across the entire scheduling session. Two types of optimization problems are proposed in this sense: Dynamic Scheduling Rule based Sequential Multi-Objective Optimization (DSR-SMOO) when the applied scheduling rules address the same objective and Dynamic Scheduling Rule based Concurrent Multi-Objective Optimization (DSR-CMOO) if the pool of rules addresses different scheduling objectives. The best way of solving such complex optimization problems is to adapt and to refine scheduling policies which are able to call different rules at each TTI based on the best matching scheduler conditions (states). The idea is to develop a set of non-linear functions which maps the scheduler state at each TTI in optimal distribution probabilities of selecting the best scheduling rule. Due to the multi-dimensional and continuous characteristics of the scheduler state space, the scheduling functions should be approximated. Moreover, the function approximations are learned through the interaction with the RRM environment. The Reinforcement Learning (RL) algorithms are used in this sense in order to evaluate and to refine the scheduling policies for the considered DSR-SMOO/CMOO optimization problems. The neural networks are used to train the non-linear mapping functions based on the interaction among the intelligent controller, the LTE packet scheduler and the RRM environment. In order to enhance the convergence in the feasible state and to reduce the scheduler state space dimension, meta-heuristic approaches are used for the channel statement aggregation. Simulation results show that the proposed aggregation scheme is able to outperform other heuristic methods. When the aggregation scheme of the channel statements is exploited, the proposed DSR-SMOO/CMOO problems focusing on different objectives which are solved by using various RL approaches are able to: increase the mean percentage of feasible TTIs, minimize the number of TTIs when the RL approaches punish the actions taken TTI-by-TTI, and minimize the variation of the performance indicators when different simulations are launched in parallel. This way, the obtained scheduling policies being focused on the multi-objective criteria are sustainable. Keywords: LTE, packet scheduling, scheduling rules, multi-objective optimization, reinforcement learning, channel, aggregation, scheduling policies, sustainable

LTE Optimization and Resource Management in Wireless Heterogeneous Networks

Mobile communication technology is evolving with a great pace. The development of the Long Term Evolution (LTE) mobile system by 3GPP is one of the milestones in this direction. This work highlights a few areas in the LTE radio access network where the proposed innovative mechanisms can substantially improve overall LTE system performance. In order to further extend the capacity of LTE networks, an integration with the non-3GPP networks (e.g., WLAN, WiMAX etc.) is also proposed in this work. Moreover, it is discussed how bandwidth resources should be managed in such heterogeneous networks. The work has purposed a comprehensive system architecture as an overlay of the 3GPP defined SAE architecture, effective resource management mechanisms as well as a Linear Programming based analytical solution for the optimal network resource allocation problem. In addition, alternative computationally efficient heuristic based algorithms have also been designed to achieve near-optimal performance

Design of static intercell interference coordination schemes for realistic lte-based cellular networks

Today, 3.5 and 4G systems including Long Term Evolution (LTE) and LTE-Advanced (LTE-A) support packet-based services and provide mobile broadband access for bandwidth-hungry applications. In this context of fast evolution, new and challenging technical issues must be e ectively addressed. The nal target is to achieve a signi cant step forward toward the improvement of the Quality of Experience (QoE). To that end, interference management has been recognized by the industry as a key enabler for cellular technologies based on OFDMA. Indeed, with a low frequency reuse factor, intercell interference (ICI) becomes a major concern since the Quality of Service (QoS) is not uniformly delivered across the network, it remarkably depends on user position. Hence, cell edge performance is an important issue in LTE and LTE-A. Intercell Interference Coordination (ICIC) encompasses strategies whose goal is to keep ICI at cell edges as low as possible. This alleviates the aforementioned situation. For this reason, the novelties presented in this Ph.D. thesis include not only developments of static ICIC mechanisms for data and control channels, but also e orts towards further improvements of the energy e ciency perspective. Based on a comprehensive review of the state of the art, a set of research opportunities were identi ed. To be precise, the need for exible performance evaluation methods and optimization frameworks for static ICIC strategies. These mechanisms are grouped in two families: the schemes that de ne constraints on the frequency domain and the ones that propose adjustments on the power levels. Thus, Soft- and Fractional Frequency Reuse (SFR and FFR, respectively) are identi ed as the base of the vast majority of static ICIC proposals. Consequently, during the rst part of this Ph.D. thesis, interesting insights into the operation of SFR and FFR were identi ed beyond well-known facts. These studies allow for the development of a novel statistical framework to evaluate the performance of these schemes in realistic deployments. As a result of the analysis, the poor performance of classic con gurations of SFR and FFR in real-world contexts is shown, and hence, the need for optimization is established. In addition, the importance of the interworking between static ICIC schemes and other network functionalities such as CSI feedback has also been identi ed. Therefore, novel CSI feedback schemes, suitable to operate in conjunction with SFR and FFR, have been developed. These mechanisms exploit the resource allocation pattern of these static ICIC techniques in order to improve the accuracy of the CSI feedback process. The second part is focused on the optimization of SFR and FFR. The use of multiobjective techniques is investigated as a tool to achieve e ective network-speci c optimization. The approach o ers interesting advantages. On the one hand, it allows for simultaneous optimization of several con icting criteria. On the other hand, the multiobjective nature results in outputs composed of several high quality (Pareto e cient) network con gurations, all of them featuring a near-optimal tradeo between the performance criteria. Multiobjective evolutionary algorithms allow employing complex mathematical structures without the need for relaxation, thus capturing accurately the system behavior in terms of ICI. The multiobjective optimization formulation of the problem aims at achieving e ective adjustment of the operational parameters of SFR and FFR both at cell level and network-wide. Moreover, the research was successfully extended to the control channels, both the PDCCH and ePDCCH. Finally, in an e ort to further improve the network energy e ciency (an aspect always considered throughout the thesis), the framework of Cell Switch O (CSO), having close connections with ICIC, is also introduced. By means of the proposed method, signi cant improvements with respect to traditional approaches, baseline con gurations, and previous proposals can be achieved. The gains are obtained in terms of energy consumption, network capacity, and cell edge performance.Actualmente los sistemas 3.5 y 4G tales como Long Term Evolution (LTE) y LTE-Advanced (LTE-A) soportan servicios basados en paquetes y proporcionan acceso de banda ancha m ovil para aplicaciones que requieren elevadas tasas de transmisi on. En este contexto de r apida evoluci on, aparecen nuevos retos t ecnicos que deben ser resueltos e cientemente. El objetivo ultimo es conseguir un salto cualitativo importante en la experiencia de usuario (QoE). Con tal n, un factor clave que ha sido reconocido en las redes celulares basadas en Orthogonal Frequency- Division Multiple Access (OFDMA) es la gesti on de interferencias. De hecho, la utilizaci on de un factor de reuso bajo permite una elevada e ciencia espectral pero a costa de una distribuci on de la calidad de servicio (QoS) que no es uniforme en la red, depende de la posici on del usuario. Por lo tanto, el rendimiento en los l mites de la celda se ve muy penalizado y es un problema importante a resolver en LTE y LTE-A. La coordinaci on de interferencias entre celdas (ICIC, del ingl es Intercell Interfe- rence Coordination) engloba las estrategias cuyo objetivo es mantener la interferencia intercelular (ICI) lo m as baja posible en los bordes de celda. Esto permite aliviar la situaci on antes mencionada. La contribuci on presentada en esta tesis doctoral incluye el dise~no de nuevos mecanismos de ICIC est atica para los canales de datos y control, as como tambi en mejoras desde el punto de vista de e ciencia energ etica. A partir de una revisi on completa del estado del arte, se identi caron una serie de retos abiertos que requer an esfuerzos de investigaci on. En concreto, la necesidad de m etodos de evaluaci on exibles y marcos de optimizaci on de las estrategias de ICIC est aticas. Estos mecanismos se agrupan en dos familias: los esquemas que de nen restricciones sobre el dominio de la frecuencia y los que proponen ajustes en los niveles de potencia. Es decir, la base de la gran mayor a de propuestas ICIC est aticas son la reutilizaci on de frecuencias de tipo soft y fraccional (SFR y FFR, respectivamente). De este modo, durante la primera parte de esta tesis doctoral, se han estudiado los aspectos m as importantes del funcionamiento de SFR y FFR, haciendo especial enfasis en las conclusiones que van m as all a de las bien conocidas. Ello ha permitido introducir un nuevo marco estad stico para evaluar el funcionamiento de estos sistemas en condiciones de despliegue reales. Como resultado de estos an alisis, se muestra el pobre desempe~no de SFR y FFR en despliegues reales cuando funcionan con sus con guraciones cl asicas y se establece la necesidad de optimizaci on. Tambi en se pone de mani esto la importancia del funcionamiento conjunto entre esquemas ICIC est aticos y otras funcionalidades de la red radio, tales como la informaci on que env an los usuarios sobre el estado de su canal downlink (feedback del CSI, del ingl es Channel State Information). De este modo, se han propuesto diferentes esquemas de feedback apropiados para trabajar conjuntamente con SFR y FFR. Estos mecanismos explotan el patr on de asignaci on de recursos que se utiliza en ICIC est atico para mejorar la precisi on del proceso. La segunda parte se centra en la optimizaci on de SFR y FFR. Se ha investigado el uso de t ecnicas multiobjetivo como herramienta para lograr una optimizaci on e caz, que es espec ca para cada red. El enfoque ofrece ventajas interesantes, por un lado, se permite la optimizaci on simult anea de varios criterios contradictorios. Por otro lado, la naturaleza multiobjetivo implica obtener como resultado con guraciones de red de elevada calidad (Pareto e cientes), todas ellas con un equilibrio casi- optimo entre las diferentes m etricas de rendimiento. Los algoritmos evolucionarios multiobjetivo permiten la utilizaci on de estructuras matem aticas complejas sin necesidad de relajar el problema, de este modo capturan adecuadamente su comportamiento en t erminos de ICI. La formulaci on multiobjetivo consigue un ajuste efectivo de los par ametros operacionales de SFR y FFR, tanto a nivel de celda como a nivel de red. Adem as, la investigaci on se extiende con resultados satisfactorios a los canales de control, PDCCH y ePDCCH. Finalmente, en un esfuerzo por mejorar la e ciencia energ etica de la red (un aspecto siempre considerado a lo largo de la tesis), se introduce en el an alisis global el apagado inteligente de celdas, estrategia con estrechos v nculos con ICIC. A trav es del m etodo propuesto, se obtienen mejoras signi cativas con respecto a los enfoques tradicionales y propuestas previas. Las ganancias se obtienen en t erminos de consumo energ etico, capacidad de la red, y rendimiento en el l mite de las celdas.Actualment els sistemes 3.5 i 4G tals com Long Term Evolution (LTE) i LTE- Advanced (LTE-A) suporten serveis basats en paquets i proporcionen acc es de banda ampla m obil per a aplicacions que requereixen elevades taxes de transmissi o. En aquest context de r apida evoluci o, apareixen nous reptes t ecnics que han de ser resolts e cientment. L'objectiu ultim es aconseguir un salt qualitatiu important en l'experi encia d'usuari (QoE). Amb tal , un factor clau que ha estat reconegut a les xarxes cel lulars basades en Orthogonal Frequency-Division Multiple Access (OFDMA) es la gesti o d'interfer encies. De fet, la utilizaci o d'un factor de re us baix permet una elevada e ci encia espectral per o a costa d'una distribuci o de la qualitat de servei (QoS) que no es uniforme a la xarxa, dep en de la posici o de l'usuari. Per tant, el rendiment en els l mits de la cel la es veu molt penalitzat i es un problema important a resoldre en LTE i LTE-A. La coordinaci o d'interfer encies entre cel les (ICIC, de l'angl es Intercell Interfe- rence Coordination) engloba les estrat egies que tenen com a objectiu mantenir la interfer encia intercel lular (ICI) el m es baixa possible en les vores de la cel la. Aix o permet alleujar la situaci o abans esmentada. La contribuci o presentada en aquesta tesi doctoral inclou el disseny de nous mecanismes de ICIC est atica per als canals de dades i control, aix com tamb e millores des del punt de vista d'e ci encia energ etica. A partir d'una revisi o completa de l'estat de l'art, es van identi car una s erie de reptes oberts que requerien esfor cos de recerca. En concret, la necessitat de m etodes d'avaluaci o exibles i marcs d'optimitzaci o de les estrat egies de ICIC est atiques. Aquests mecanismes s'agrupen en dues fam lies: els esquemes que de neixen restriccions sobre el domini de la freq u encia i els que proposen ajustos en els nivells de pot encia. Es a dir, la base de la gran majoria de propostes ICIC est atiques s on la reutilitzaci o de freq u encies de tipus soft i fraccional (SFR i FFR, respectivament). D'aquesta manera, durant la primera part d'aquesta tesi doctoral, s'han estudiat els aspectes m es importants del funcionament de SFR i FFR, fent especial emfasi en les conclusions que van m es enll a de les ben conegudes. Aix o ha perm es introduir un nou marc estad stic per avaluar el funcionament d'aquests sistemes en condicions de desplegament reals. Com a resultat d'aquestes an alisis, es mostra el pobre acompliment de SFR i FFR en desplegaments reals quan funcionen amb les seves con guracions cl assiques i s'estableix la necessitat d'optimitzaci o. Tamb e es posa de manifest la import ancia del funcionament conjunt entre esquemes ICIC est atics i altres funcionalitats de la xarxa radio, tals com la informaci o que envien els usuaris sobre l'estat del seu canal downlink (feedback del CSI, de l'angl es Channel State Information). D'aquesta manera, s'han proposat diferents esquemes de feedback apropiats per treballar conjuntament amb SFR i FFR. Aquests mecanismes exploten el patr o d'assignaci o de recursos que s'utilitza en ICIC est atic per millorar la precisi o del proc es. La segona part se centra en l'optimitzaci o de SFR i FFR. S'ha investigat l' us de t ecniques multiobjectiu com a eina per aconseguir una optimitzaci o e ca c, que es espec ca per a cada xarxa. L'enfocament ofereix avantatges interessants, d'una banda, es permet l'optimitzaci o simult ania de diversos criteris contradictoris. D'altra banda, la naturalesa multiobjectiu implica obtenir com resultat con guracions de xarxa d'elevada qualitat (Pareto e cients), totes elles amb un equilibri gaireb e optim entre les diferents m etriques de rendiment. Els algorismes evolucionaris multiobjectiu permeten la utilitzaci o d'estructures matem atiques complexes sense necessitat de relaxar el problema, d'aquesta manera capturen adequadament el seu comportament en termes de ICI. La formulaci o multiobjectiu aconsegueix un ajust efectiu dels par ametres operacionals de SFR i FFR, tant a nivell de cel la com a nivell de xarxa. A m es, la recerca s'est en amb resultats satisfactoris als canals de control, PDCCH i ePDCCH. Finalment, en un esfor c per millorar l'e ci encia energ etica de la xarxa (un aspecte sempre considerat al llarg de la tesi), s'introdueix en l'an alisi global l'apagat intel ligent de cel les, estrat egia amb estrets vincles amb ICIC. Mitjan cant el m etode proposat, s'obtenen millores signi catives pel que fa als enfocaments tradicionals i propostes pr evies. Els guanys s'obtenen en termes de consum energ etic, capacitat de la xarxa, i rendiment en el l mit de les cel les

Spectrum sharing and management techniques in mobile networks

Το φάσμα συχνοτήτων αποδεικνύεται σπάνιο κομμάτι για τους πόρους ενός κινητού δικτύου το οποίο πρέπει να ληφθεί υπόψιν στη σχεδίαση τηλεπικοινωνιακών συστημάτων 5ης γενιάς. Επιπλέον οι πάροχοι κινητών δικτύων θα πρέπει να επαναπροσδιορίσουν επιχειρησιακά μοντέλα τα οποία μέχρι τώρα δεν θεωρούνταν αναγκαία (π.χ., γνωσιακά ραδιοδίκτυα), ή να εξετάσουν την υιοθέτηση νέων μοντέλων που αναδεικνύονται (π.χ., αδειοδοτούμενη από κοινού πρόσβαση) ώστε να καλύψουν τις ολοένα αυξανόμενες ανάγκες για εύρος ζώνης. Ο μερισμός φάσματος θεωρείται αναπόφευκτος για συστήματα 5G και η διατριβή παρέχει λύση για προσαρμοστικό μερισμό φάσματος με πολλαπλά καθεστώτα εξουσιοδότησης, βάσει ενός καινοτόμου αρχιτεκτονικού πλαισίου το οποίο επιτρέπει στα δικτυακά στοιχεία να λαμβάνουν αποφάσεις για απόκτηση φάσματος. Η προτεινόμενη διαδικασία λήψης αποφάσεων είναι μία καινοτόμα τεχνική προσαρμοστικού μερισμού φάσματος βασιζόμενη σε ελεγκτές ασαφούς λογικής που καθορίζονν το καταλληλότερο σχήμα μερισμού φάσματος και σε ενισχυμένη μάθηση που ρυθμίζει τους κανόνες ασαφούς λογικής, στοχεύοντας να βρει τη βέλτιστη πολιτική που πρέπει να ακολουθεί ο πάροχος ώστε να προσφέρει την επιθυμητή ποιότητα υπηρεσιών στους χρήστες, διατηρώντας πόρους (οικονομικούς ή ραδιοπόρους) όπου είναι εφικτό. Η τελευταία συνεισφορά της διατριβής είναι ένας μηχανισμός που εξασφαλίζει δίκαιη πρόσβαση σε φάσμα ανάμεσα σε χρήστες σε σενάρια στα οποία η εκχώρηση άδειας χρήσης φάσματος δεν είναι προαπαιτούμενη.Radio spectrum has loomed out to be a scarce resource that needs to be carefully considered when designing 5G communication systems and Mobile Network Operators (MNOs) will need to revisit business models that were not of their prior interest (e.g. Cognitive Radio) or consider adopting new business models that emerge (e.g. Licensed Shared Access) so as to cover the extended capacity needs. Spectrum sharing is considered unavoidable for 5G systems and this thesis provides a solution for adaptive spectrum sharing under multiple authorization regimes based on a novel architecture framework that enables network elements to proceed in decisions for spectrum acquisition. The decision making process for spectrum acquisition proposed is a novel Adaptive Spectrum Sharing technique that uses Fuzzy Logic controllers to determine the most suitable spectrum sharing option and reinforcement learning to tune the fuzzy logic rules, aiming to find an optimal policy that MNO should follow in order to offer the desirable Quality of Service to its users, while preserving resources (either economical, or radio) when possible. The final contribution of this thesis is a mechanism that ensures fair access to spectrum among the users in scenarios in which conveying spectrum license is not prerequisite

Software Defined Applications in Cellular and Optical Networks

abstract: Small wireless cells have the potential to overcome bottlenecks in wireless access through the sharing of spectrum resources. A novel access backhaul network architecture based on a Smart Gateway (Sm-GW) between the small cell base stations, e.g., LTE eNBs, and the conventional backhaul gateways, e.g., LTE Servicing/Packet Gateways (S/P-GWs) has been introduced to address the bottleneck. The Sm-GW flexibly schedules uplink transmissions for the eNBs. Based on software defined networking (SDN) a management mechanism that allows multiple operator to flexibly inter-operate via multiple Sm-GWs with a multitude of small cells has been proposed. This dissertation also comprehensively survey the studies that examine the SDN paradigm in optical networks. Along with the PHY functional split improvements, the performance of Distributed Converged Cable Access Platform (DCCAP) in the cable architectures especially for the Remote-PHY and Remote-MACPHY nodes has been evaluated. In the PHY functional split, in addition to the re-use of infrastructure with a common FFT module for multiple technologies, a novel cross functional split interaction to cache the repetitive QAM symbols across time at the remote node to reduce the transmission rate requirement of the fronthaul link has been proposed.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Fairness-Oriented and QoS-Aware Radio Resource Management in OFDMA Packet Radio Networks: Practical Algorithms and System Performance

During the last two decades, wireless technologies have demonstrated their importance in people’s personal communications but also as one of the fundamental drivers of economic growth, first in the form of cellular networks (2G, 3G and beyond) and more recently in terms of wireless computer networks (e.g. Wi-Fi,) and wireless Internet connectivity. Currently, the development of new packet radio systems is evolving, most notably in terms of 3GPP Long Term Evolution (LTE) and LTE-Advanced, in order to utilize the available radio spectrum as efficiently as possible. Therefore, advanced radio resource management (RRM) techniques have an important role in current and emerging future mobile networks. In all wireless systems, the data throughput and the average data delay performance, especially in case of best effort services, are greatly degraded when the traffic-load in the system is high. This is because the radio resources (time, frequency and space) are shared by multiple users. Another big problem is that the transmission performance can vary heavily between different users, since the channel state greatly depends on the communication environment and changes therein. To solve these challenges, new major technology innovations are needed. This thesis considers new practical fairness-oriented and quality-of-service (QoS) -aware RRM algorithms in OFDMA-based packet radio networks. Moreover, using UTRAN LTE radio network as application example, we focus on analyzing and enhancing the system-level performance by utilizing state-of-the-art waveform and radio link developments combined with advanced radio resource management methods. The presented solutions as part of RRM framework consist of efficient packet scheduling, link adaptation, power control, admission control and retransmission mechanisms. More specifically, several novel packet scheduling algorithms are proposed and analyzed to address these challenges. This dissertation deals specifically with the problems of QoS provisioning and fair radio resource distribution among users with limited channel feedback, admission and power control in best effort and video streaming type traffic scenarios, and the resulting system-level performance. The work and developments are practically-oriented taking aspects like finite channel state information (CSI), reporting delays and retransmissions into account. Consequently, the multi-user diversity gain with opportunistic frequency domain packet scheduling (FDPS) is further explored in spatial domain by taking the multiantenna techniques and spatial division multiplexing functionalities into account. Validation and analysis of the proposed solutions is performed through extensive system level simulations modeling the behavior and operation of a complete multiuser cell in the overall network. Based on the obtained performance results, it is confirmed that greatly improved fairness can be fairly easily built in to the scheduling algorithm and other RRM mechanisms without considerably degrading e.g. the average cell throughput. Moreover, effective QoS-provisioning framework in video streaming type traffic scenarios demonstrate the effectiveness of the presented solutions as increased system capacity measured in terms of the number of users or parallel streaming services supported simultaneously by the network

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig