Spectrum Leasing as an Incentive towards Uplink Macrocell and Femtocell Cooperation

The concept of femtocell access points underlaying existing communication infrastructure has recently emerged as a key technology that can significantly improve the coverage and performance of next-generation wireless networks. In this paper, we propose a framework for macrocell-femtocell cooperation under a closed access policy, in which a femtocell user may act as a relay for macrocell users. In return, each cooperative macrocell user grants the femtocell user a fraction of its superframe. We formulate a coalitional game with macrocell and femtocell users being the players, which can take individual and distributed decisions on whether to cooperate or not, while maximizing a utility function that captures the cooperative gains, in terms of throughput and delay.We show that the network can selforganize into a partition composed of disjoint coalitions which constitutes the recursive core of the game representing a key solution concept for coalition formation games in partition form. Simulation results show that the proposed coalition formation algorithm yields significant gains in terms of average rate per macrocell user, reaching up to 239%, relative to the non-cooperative case. Moreover, the proposed approach shows an improvement in terms of femtocell users' rate of up to 21% when compared to the traditional closed access policy.Comment: 29 pages, 11 figures, accepted at the IEEE JSAC on Femtocell Network

Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining

The deployment of underlay small base stations (SBSs) is expected to significantly boost the spectrum efficiency and the coverage of next-generation cellular networks. However, the coexistence of SBSs underlaid to an existing macro-cellular network faces important challenges, notably in terms of spectrum sharing and interference management. In this paper, we propose a novel game-theoretic model that enables the SBSs to optimize their transmission rates by making decisions on the resource occupation jointly in the frequency and spatial domains. This procedure, known as interference draining, is performed among cooperative SBSs and allows to drastically reduce the interference experienced by both macro- and small cell users. At the macrocell side, we consider a modified water-filling policy for the power allocation that allows each macrocell user (MUE) to focus the transmissions on the degrees of freedom over which the MUE experiences the best channel and interference conditions. This approach not only represents an effective way to decrease the received interference at the MUEs but also grants the SBSs tier additional transmission opportunities and allows for a more agile interference management. Simulation results show that the proposed approach yields significant gains at both macrocell and small cell tiers, in terms of average achievable rate per user, reaching up to 37%, relative to the non-cooperative case, for a network with 150 MUEs and 200 SBSs

Interference Aware Cognitive Femtocell Networks

Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks. Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision. This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference

Game theoretical models for clustering and resource sharing in macro-femtocells networks

One of the main challenges of cellular network operators is to keep a good network quality for their users. In most cases, network quality decreases in indoor environments causing users to switch from one operator to another. A promising solution to cope with this issue is the deployment of femtocells that are used mainly at homes to enhance the mobile network coverage. In fact, higher penetration of broadband and mobile phones with high requirements of new applications such as video conferencing and internet games are promoting femtocell market. However, the deployment of femtocells in existing macrocell networks is a very challenging task due to the high complexity of the resource allocation. In this thesis, we focus on proposing several solutions to address the resource allocation problem in macro-femtocell networks with dense deployment of femtocells based on clustering techniques. Clustering techniques are used to reduce the resource allocation complexity of dense-femtocell networks since the resources are allocated locally within each cluster. Furthermore, a cluster head is responsible for the allocation of resources to femtocells within the cluster which avoids the co-tier interference. The clustering techniques have been widely used for distributed resource allocation in heterogeneous networks through the use of game theory models. In this work, three distributed resource allocation algorithms based on cooperative and evolutionary games are proposed. In the first part, we discuss the resource allocation problem for the non-dense deployment of femtocells. Toward this goal, a coalitional game is used to incentive femtocells in the formation of clusters. The approach decomposes in: (i) a base station selection algorithm for public users, (ii) a clustering algorithm based on cooperative game theory and (iii) a resource allocation within each cluster based on the PSO technique. Besides, an interference control mechanism enabled femtocells to leave its current cluster when the interference levels are higher than an interference threshold. In the second part, we focus on a fair allocation of resources for macro-femtocell networks. We develop a clustering algorithm based on a cooperative game for non-dense femtocell network. The Shapley value is applied to find the marginal contribution of every femtocell to all the possible groups of femtocells, thus, finding the fair amount of resources to be allocated to each femtocell within a cluster. This solution is only applied for non-dense femtocell deployment due to that the complexity of calculating the Shapley value increases significantly with a large number of femtocells. Stability criteria based on the ε-concept of game theory is utilized to find the set of stable clusters. Finally, the analysis of the resource allocation for dense-femtocell deployment is addressed through an evolutionary game theory (EGT) model. It is assumed that EGT requires bounded rationality from players, this reduces the complexity and allows the dense deployment of femtocells. In addition, we demonstrate that the set of clusters formed with EGT are stable by means of the replicator dynamics. The proposed model also includes system analysis for users with low mobility such as pedestrians and cyclists

Business scenarios, technical challenges and system requirements - D2.1

Deliverable D2.1 del projecte Europeu OneFIT (ICT-2009-257385)Preprin

Cooperative Spectrum Sharing in Cognitive Radio Networking

Driven by the massive growth in communications data traffic as well as flourishing users' demands, we need to fully utilize the existing scarce spectrum resource. However, there have been several studies and reports over the years showing that a large portion of licensed spectrum is actually underutilized in both temporal and spatial domains. Moreover, aiming at facing the dilemma among the fixed spectrum allocation, the ever enormous increasing traffic demand and the limited spectrum resource, cognitive radio (CR) was proposed by Mitola to alleviate the under usage of spectrum. Thus, cognitive radio networking (CRN) has emerged as a promising paradigm to improve the spectrum efficiency and utilization by allowing secondary users (SUs) to utilize the spectrum hole of primary users (PUs). By using spectrum sensing, SUs can opportunistically access spectrum holes for secondary transmission without interfering the transmissions of the PUs and efficient spectrum utilization by multiple PUs and SUs requires reliable detection of PUs. Nevertheless, sensing errors such as false alarm and misdetection are inevitable in practical networks. Hence, the assumption that SUs always obtain the exact channel availability information is unreasonable. In addition, spectrum sensing must be carried out continuously and the SU must terminate its transmission as soon as it senses the re-occupancy by a PU. As a better alternative of spectrum sensing, cooperation has been leveraged in CRN, which is referred as cooperative cognitive radio networking (CCRN). In CCRN, in order to obtain the transmission opportunities, SUs negotiate with the PUs for accessing the spectrum by providing tangible service for PUs. In this thesis, we study cluster based spectrum sharing mechanism for CCRN and investigate on exploiting the cooperative technique in heterogeneous network. First, we develop cooperation protocols for CRN. Simultaneous transmission can be realized through quadrature signalling method in our proposed cooperation protocol. The optimal power allocation has been analyzed and closed-form solution has been derived for amplify and forward mode. Second, we study a cluster based spectrum sharing mechanism. The spectrum sharing is formulated as a combinatorial non-linear optimization problem which is NP-hard. Afterwards, we solve this problem by decomposing it into cluster allocation and time assignment, and we show that the result is close to the optimal solution. Third, we propose a macrocell-femtocell network cooperation scheme for heterogeneous networks under closed access mode. The cooperation between the femtocell network and macrocell network is investigated. By implementing the cooperation, not only the macrocell users' (MUEs') and femtocell users' (FUEs') utility can be improved compared with the non-cooperation case, but also the energy consumption as well as the interference from the femtocell network to the macrocell network can be reduced

Optimal and practical handover decision algorithms in heteregeneous marco-femto cellular networks

Driven by the smart tablet/phone revolution and the proliferation of bandwidth hungry applications such as cloud computing and streaming video, the demand for high data rate wireless communication is increasing tremendously. In order to meet the increasing demand from subscribers, wireless operators are in the process of augmenting their macrocell network with supplemental infrastructure such as microcells, distributed antennas and relays. An alternative with lower upfront costs is to improve indoor coverage and capacity by using end-consumer installed femtocells. A femtocell is a low power, short range (up to 100 meters coverage radius) cellular wireless access point (AP), functioning in service provider owned licensed spectrum. Due to the proximity of end users to the femtocell access points, APs are able to provide higher end-user QoE and better spatial reuse of limited spectrum. Femtocells are useful in offloading the macro-cellular network as well as reducing the operating and capital expenditure costs for operators. Femtocells coexist with legacy cellular networks consisting of macrocells. In this emerging combined architecture, large number of Femtocell Application Point (FAPs) is randomly deployed in the coverage area of macro BSs. However, several problems related to MM (mobility management) and RM (resource management) in this combined architecture still remain to be solved. The ad hoc deployment of FAPs and asymmetric radio communication and call processing capabilities between macrofemto networks are the primary causes of these problems. Uncoordinated deployment of FAPs providing indoor oriented wireless access service within the macro coverage may cause severe interference problems that need to be mitigated and handled by RM/MM schemes. The MM decisions should take into account the resource constraints and UE mobility in order to prevent unnecessary or undesirable handovers towards femtocells. Ignoring these factors in MM decisions may lead to low customer satisfaction due to mismanagement of handover events in the combined macro-femto network, delayed signaling traffic and unsatisfactory call/connection quality. In order to address all of the aforementioned issues, the handover decision problem in combined femto-macro networks has been formulated as a multi-objective non-linear optimization problem. Since there are no known analytical solution to this problem, an MDP (Markov Decision Process) based heuristic has been proposed as a practical and optimal HO (handover) decision making scheme. This heuristic has been updated and improved in an iterative manner and has also been supported by a dynamic SON (Self Organizing Networks) algorithms that is based on heuristic's components. The performance results show that the final version of MDP based heuristic has signi cantly superior performance in terms offloading the macro network, minimizing the undesirable network events (e.g. outage and admission rejection) when compared to state-of-art handover algorithms

Traffic offloading in future, heterogeneous mobile networks

The rise of third-party content providers and the introduction of numerous applications has been driving the growth of mobile data traffic in the past few years. In order to tackle this challenge, Mobile Network Operators (MNOs) aim to increase their networks' capacity by expanding their infrastructure, deploying more Base Stations (BSs). Particularly, the creation of Heterogeneous Networks (HetNets) and the application of traffic offloading through the dense deployment of low-power BSs, the small cells (SCs), is one promising solution to address the aforementioned explosive data traffic increase. Due to their financial implementation requirements, which could not be met by the MNOs, the emergence of third parties that deploy small cell networks creates new business opportunities. Thus, the investigation of frameworks that facilitate the implementation of outsourced traffic offloading, the collaboration and the transactions among MNOs and third-party small cell owners, as well as the provision of participation incentives for all stakeholders is essential for the deployment of the necessary new infrastructure and capacity expansion. The aforementioned emergence of third-party content providers and their applications not only drives the increase in mobile data traffic, but also create new Quality of Service (QoS) as well as Quality of Experience (QoE) requirements that the MNOs need to guarantee for the satisfaction of their subscribers. Moreover, even though the MNOs accommodate this traffic, they do not get any monetary compensation or subsidization for the required capacity expansion. On the contrary, their revenues reduce continuously. To that end, it is necessary to research and design network and economic functionalities adapted to the new requirements, such as QoE-aware Radio Resource Management and Dynamic Pricing (DP) strategies, which both guarantee the subscriber satisfaction and maximization the MNO profit (to compensate the diminished MNOs' revenues and the increasing deployment investment). Following a thorough investigation of the state-of-the-art, a set of research directions were identified. This dissertation consists of contributions on network sharing and outsourced traffic offloading for the capacity enhancement of MNO networks, and the design of network and economic functions for the sustainable deployment and use of the densely constructed HetNets. The contributions of this thesis are divided into two main parts, as described in the following. The first part of the thesis introduces an innovative approach on outsourced traffic offloading, where we present a framework for the Multi-Operator Radio Access Network (MORAN) sharing. The proposed framework is based on an auction scheme used by a monopolistic Small Cell Operator (SCO), through which he leases his SC infrastructure to MNOs. As the lack of information on the future offered load and the auction strategies creates uncertainty for the MNOs, we designed a learning mechanism that assists the MNOs in their bid-placing decisions. Our simulations show that our proposal almost maximizes the social welfare, satisfying the involved stakeholders and providing them with participation incentives. The second part of the thesis researches the use of network and economic functions for MNO profit maximization, while guaranteeing the users' satisfaction. Particularly, we designed a model that accommodates a plethora of services with various QoS and QoE requirements, as well as diverse pricing, that is, various service prices and different charging schemes. In this model, we proposed QoE-aware user association, resource allocation and joint resource allocation and dynamic pricing algorithms, which exploit the QoE-awareness and the network's economic aspects, such as the profit. Our simulations have shown that our proposals gain substantial more profit compared to traditional and state-of-the-art solutions, while providing a similar or even better network performance.El aumento de los proveedores de contenido de terceros y la introducción de numerosas aplicaciones ha impulsado el crecimiento del tráfico de datos en redes móviles en los últimos años. Para hacer frente a este desafío, los operadores de redes móviles (Mobile Network Operators, MNOs) apuntan a aumentar la capacidad de sus redes mediante la expansión de su infraestructura y el despliegue de más estaciones base (BS). Particularmente, la creación de Redes Heterogéneas (Heterogenous Networks, HetNets) y la aplicación de descarga de tráfico a través del despliegue denso de BSs de baja potencia, las células pequeñas (small cells, SCs), es una solución prometedora para abordar el aumento del tráfico de datos explosivos antes mencionado. Debido a sus requisitos de implementación financiera, que los MNO no pudieron cumplir, la aparición de terceros que implementan redes de células pequeñas crea nuevas oportunidades comerciales. Por lo tanto, la investigación de marcos que faciliten la implementación de la descarga tercerizada de tráfico, la colaboración y las transacciones entre MNOs y terceros propietarios de células pequeñas, así como la provisión de incentivos de participación para todas las partes interesadas esencial para el despliegue de la nueva infraestructura necesaria y la expansión de la capacidad. La aparición antes mencionada de proveedores de contenido de terceros y sus aplicaciones no solo impulsa el aumento del tráfico de datos móviles, sino también crea nuevos requisitos de calidad de servicio (Quality of Service, QoS) y calidad de la experiencia (Quality of Experience, QoE) que los operadores de redes móviles deben garantizar para la satisfacción de sus suscriptores. Además, a pesar de que los operadores de redes móviles adaptan este tráfico, no obtienen ninguna compensación monetaria o subsidio por la expansión de capacidad requerida. Por el contrario, sus ingresos se reducen continuamente. Para ello, es necesario investigar y diseñar funcionalidades económicas y de red adaptadas a los nuevos requisitos, tales como las estrategias QoE-conscientes de gestión de recursos de radio y de precios dinámicos (Dynamic Pricing, DP), que garantizan la satisfacción del abonado y la maximización de la ganancia de operador móvil (para compensar los ingresos de los MNOs disminuidos y la creciente inversión de implementación). Después de una investigación exhaustiva del estado del arte, se identificaron un conjunto de direcciones de investigación. Esta disertación consiste en contribuciones sobre el uso compartido de redes y la descarga tercerizada de tráfico para la mejora de la capacidad de redes MNO, y el diseño de funciones económicas y de red para el despliegue y uso sostenible de las HetNets densamente construidas. Las contribuciones de esta tesis se dividen en dos partes principales, como se describe a continuación. La primera parte de la tesis presenta un enfoque innovador sobre la descarga subcontratada de tráfico, en el que presentamos un marco para el uso compartido de la red de acceso de radio de múltiples operadores (Multi-Operator RAN, MORAN). El marco propuesto se basa en un esquema de subasta utilizado por un operador monopólico de celda pequeña (Small Cell Operator, SCO), a través del cual arrienda su infraestructura SC a MNOs. Como la falta de información sobre la futura carga de red y las estrategias de subasta creaban incertidumbre para los MNO, diseñamos un mecanismo de aprendizaje que asiste a los MNO en sus decisiones de colocación de pujas. Nuestras simulaciones muestran que nuestra propuesta casi maximiza el bienestar social, satisfaciendo a las partes interesadas involucradas y proporcionándoles incentivos de participación. La segunda parte de la tesis investiga el uso de las funciones económicas y de red para la maximización de los beneficios de los MNOs, al tiempo que garantiza la satisfacción de los usuarios. Particularmente, diseñamos un modelo que acomoda una gran cantidad de servicios con diversos requisitos de QoS y QoE, tanto como diversos precios, es decir, varios precios de servicio y diferentes esquemas de cobro. En este modelo, propusimos algoritmos QoE-conscientes para asociación de usuarios, asignación de recursos y conjunta asignación de recursos y de fijación dinámica de precios, que explotan la conciencia de QoE y los aspectos económicos de la red, como la ganancia. Nuestras simulaciones han demostrado que nuestras propuestas obtienen un beneficio sustancial en comparación con las soluciones tradicionales y del estado del arte, a la vez que proporcionan un rendimiento de red similar o incluso mejor.Postprint (published version

Optimization models for resource management in two-tier cellular networks

Macro-femtocell network is the most promising two-tier architecture for the cellular network operators because it can improve their current network capacity without additional costs. Nevertheless, the incorporation of femtocells to the existing cellular networks needs to be finely tuned in order to enhance the usage of the limited wireless resources, because the femtocells operate in the same spectrum as the macrocell. In this thesis, we address the resource optimization problem for the OFDMA two-tier networks for scenarios where femtocells are deployed using hybrid access policy. The hybrid access policy is a technique that could provide different levels of service to authorized users and visitors to the femtocell. This method reduces interference received by femtocell subscribers by granting access to nearby public users. These approaches should find a compromise between the level of access granted to public users and the impact on the subscribers satisfaction. This impact should be reduced in terms of performance or through economic compensation. In this work, two specific issues of an OFDMA two-tier cellular network are addressed. The first is the trade-off between macrocell resource usage efficiency and the fairness of the resource distribution among macro mobile users and femtocells. The second issue is the compromise between interference mitigation and granting access to public users without depriving the subscriber downlink transmissions. We tackle these issues by developing several resource allocation models for non-dense and dense femtocell deployment using Linear Programming and one evolutionary optimization method. In addition, the proposed resource allocation models determine the best suitable serving base station together with bandwidth and transmitted power per user in order to enhance the overall network capacity. The first two parts of this work cope with the resource optimization for non-dense deployment using orthogonal and co-channel allocation. Both parts aim at the maximization of the sum of the weighted user data rates. In the first part, several set of weights are introduced to prioritize the use of femtocells for subscribers and public users close to femtocells. In addition, macrocell power control is incorporated to enhance the power distribution among the active downlink transmissions and to improve the tolerance to the environmental noise. The second part enables the spectral reuse and the power adaptation is a three-folded solution that enhances the power distribution over the active downlink transmissions, improves the tolerance to the environmental noise and a given interference threshold, and achieves the target Quality of Service (QoS). To reduce the complexity of the resource optimization problem for dense deployment, the third part of this work divides the optimization problem into subproblems. The main idea is to divide the user and FC sets into disjoint sets taking into account their locations. Thus, the optimization problem can be solved independently in each OFDMA zone. This solution allows the subcarriers reuse among inner macrocell zones and femtocells located in outer macrocell zones and also between femtocells belonging to different clusters if they are located in the same zone. Macrocell power control is performed to avoid the cross-tier interference among macrocell inner zones and inside femtocells located in outer zones. Another well known method used to reduce the complexity of the resource optimization problem is the femtocell clustering. However, finding the optimal cluster configuration together with the resource allocation is a complex optimization problem due to variable number related to the possible cluster configurations. Therefore, the part four of this work deals with a heuristic cluster based resource allocation model and a motivation scheme for femtocell clustering through the allocation of extra resources for subscriber and “visitor user” transmissions. The cluster based resource allocation model maximizes the network throughput while keeping balanced clusters and minimizing the inter-cluster interference. Finally, the proposed solutions are evaluated through extensive numerical simulations and the numerical results are presented to provide a comparison with the related works found in the literature

A comprehensive survey on radio resource management in 5G HetNets: current solutions, future trends and open issues

The 5G network technologies are intended to accommodate innovative services with a large influx of data traffic with lower energy consumption and increased quality of service and user quality of experience levels. In order to meet 5G expectations, heterogeneous networks (HetNets) have been introduced. They involve deployment of additional low power nodes within the coverage area of conventional high power nodes and their placement closer to user underlay HetNets. Due to the increased density of small-cell networks and radio access technologies, radio resource management (RRM) for potential 5G HetNets has emerged as a critical avenue. It plays a pivotal role in enhancing spectrum utilization, load balancing, and network energy efficiency. In this paper, we summarize the key challenges i.e., cross-tier interference, co-tier interference, and user association-resource-power allocation (UA-RA-PA) emerging in 5G HetNets and highlight their significance. In addition, we present a comprehensive survey of RRM schemes based on interference management (IM), UA-RA-PA and combined approaches (UA-RA-PA + IM). We introduce a taxonomy for individual (IM, UA-RA-PA) and combined approaches as a framework for systematically studying the existing schemes. These schemes are also qualitatively analyzed and compared to each other. Finally, challenges and opportunities for RRM in 5G are outlined, and design guidelines along with possible solutions for advanced mechanisms are presented