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

Characteristics of Citizen-contributed Geographic Information

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Current Internet applications have been increasingly incorporating citizen-contributed geographic information (CCGI) with much heterogeneous characteristics. Nevertheless, despite their differences, several terms are often being used interchangeably to define CCGI types, in the existing literature. As a result, the notion of CCGI has to be carefully specified, in order to avoid vagueness, and to facilitate the choice of a suitable CCGI dataset to be used for a given application. To address the terminological ambiguity in the description of CCGI types, we propose a typology of GI and a theoretical framework for the evaluation of GI in terms of data quality, number and type of contributors and cost of data collection per observation. We distinguish between CCGI explicitly collected for scientific or socially-oriented purposes. We review 27 of the main Internet-based CCGI platforms and we analyse their characteristics in terms of purpose of the data collection, use of quality assurance and quality control (QA/QC) mechanisms, thematic category, and geographic extents of the collected data. Based on the proposed typology and the analysis of the platforms, we conclude that CCGI differs in terms of data quality, number of contributors, data collection cost and the application of QA/QC mechanisms, depending on the purpose of the data collection

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

Estimating population density distribution from network-based mobile phone data

In this study we address the problem of leveraging mobile phone network-based data for the task of estimating population density distribution at pan-European level. The primary goal is to develop a methodological framework for the collection and processing of network-based data that can be plausibly applied across multiple MNOs. The proposed method exploits more extensive network topology information than is considered in most state-of-the-art literature, i.e., (approximate) knowledge of cell coverage areas is assumed instead of merely cell tower locations. A distinguishing feature of the proposed methodology is the capability of taking in input a combination of cell-level and Location Area-level data, thus enabling the integration of data from Call Detail Records (CDR) with other network-based data sources, e.g., Visitor Location Register (VLR). Different scenarios are considered in terms of input data availability at individual MNOs (CDR only, VLR only, combinations of CDR and VLR) and for multi-MNO data fusion, and the relevant tradeoff dimensions are discussed. At the core of the proposed method lies a novel formulation of the population distribution estimation as a Maximum Likelihood estimation problem. The proposed estimation method is validated for consistency with synthetically generated data in a simplified simulation scenario.JRC.H.6-Digital Earth and Reference Dat

Cooperative Interference Alignment in Femtocell Networks

International audienceUnderlay femtocells have 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 novel approach for interference management that enables a number of femtocells to cooperate and improve their downlink rate, by sharing spectral resources and suppressing intra-tier interference using interference alignment. We formulate a coalitional game in partition form among the femtocells and propose a distributed algorithm for coalition formation. Using our approach, the femtocell access points can make individual decisions on whether to cooperate or not, while maximizing a utility function that captures the cooperative gains and the costs in terms of transmit power for information exchange. We show that, using the proposed coalition formation algorithm, the femtocells can self-organize into a network partition composed of disjoint femtocell coalitions, which constitutes the recursive core of the game. Simulation results show significant gains in terms of average payoff per femtocell, reaching up to 30% relative to the non-cooperative scheme

Cache-aware user association in backhaul-constrained small cell networks

International audienceAnticipating multimedia file requests via caching at the small cell base stations (SBSs) of a cellular network has emerged as a promising technique for optimizing the quality of service (QoS) of wireless user equipments (UEs). However, developing efficient caching strategies must properly account for specific small cell constraints, such as backhaul congestion and limited storage capacity. In this paper, we address the problem of devising a user-cell association, in which the SBSs exploit caching capabilities to overcome the backhaul capacity limitations and enhance the users' QoS. In the proposed approach, the SBSs individually decide on which UEs to service based on both content availability and on the data rates they can deliver, given the interference and backhaul capacity limitations. We formulate the problem as a one-to-many matching game between SBSs and UEs. To solve this game, we propose a distributed algorithm, based on the deferred acceptance scheme, that enables the players (i.e., UEs and SBSs) to self-organize into a stable matching, in a reasonable number of algorithm iterations. Simulation results show that the proposed cell association scheme yields significant gains, reaching up to 21% improvement compared to a traditional cell association techniques with no caching considerations

Power Distribution of Device-to-Device Communications in Underlaid Cellular Networks

Device-to-device (D2D) communications have recently emerged as a novel transmission paradigm in wireless cellular networks. D2D transmissions take place concurrently with the usual cellular connections, and thus, controlling the interference brought to the macro-cellular user equipment (UE) is of vital importance

Matching with Externalities for Context-Aware User-Cell Association in Small Cell Networks

In this paper, we propose a novel user-cell association approach for wireless small cell networks that exploits previously unexplored context information extracted from users' devices, i.e., user equipments (UEs). Beyond characterizing precise quality of service (QoS) requirements that accurately reflect the UEs' application usage, our proposed cell association approach accounts for the devices' hardware type (e.g., smartphone, tablet, laptop). This approach has the practical benefit of enabling the small cells to make better informed cell association decisions that handle practical device-specific QoS characteristics. We formulate the problem as a matching game between small cell base stations (SBSs) and UEs. In this game, the SBSs and UEs rank one another based on well-designed utility functions that capture composite QoS requirements, extracted from the context features (i.e., application in use, hardware type). We show that the preferences used by the nodes to rank one another are interdependent and influenced by the existing network-wide matching. Due to this unique feature of the preferences, we show that the proposed game can be classified as a many-to-one matching game with externalities. To solve this game, we propose a distributed algorithm that enables the players (i.e., UEs and SBSs) to self-organize into a stable matching that guarantees the required applications' QoS. Simulation results show that the proposed context-aware cell association scheme yields significant gains, reaching up to 52% improvement compared to baseline context-unaware approaches.Comment: 6 pages, 3 figures, conferenc