Caching multimedia files at the network edge has been identified as a key technology for enhancing users' quality-of-service (QoS), while reducing redundant transmissions over capacity-constrained backhauls. Nevertheless, in small cell networks, the efficiency of a caching policy depends on the ability of small base stations (SBSs) to anticipate the requests from the user equipments (UEs). In this paper, we propose a collaborative filtering (CF) scheme for estimating the required backhaul usage at each SBS, by mining the cacheability of UEs' file requests. In the proposed approach, each SBS has a two-fold objective: update the bandwidth allocation based on the estimated backhaul utilization, and, given the current bandwidth availability, identify which UEs to service. We formulate the problem as a one-to many matching game between SBSs and UEs, and we propose a novel cache-aware user association algorithm that minimizes the backhaul usage at each SBS, subject to individual QoS requirements. Simulation results, based on real-world service request logs, have shown that the proposed CF-based solution can yield significant gains in terms of backhaul efficiency and cache hit-ratio, reaching up to 25%, with a maximum gap of 9% to an optimal cache-aware association technique.

Anticipating 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.

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 a 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 SBS 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.

The use of small cells serviced by low-power base stations such as femtocells is envisioned to improve the spectrum efficiency and the coverage of next-generation mobile wireless networks. However, one of the major challenges in femtocell deployments is managing interference. In this paper, we propose a novel cooperative solution that enables femtocells to improve their achievable data rates, by suppressing intratier interference using the concept of interference alignment (IA). We model this cooperative behavior among the femtocells as a coalitional game in partition form and we propose a distributed algorithm for the coalition formation. The proposed algorithm allows the femtocell base stations to independently decide on whether to cooperate or not, while maximizing a utility function capturing both the gains and costs from cooperation. Using the proposed algorithm, the femtocells can self-organize into a stable network partition composed of disjoint femtocell coalitions and which constitutes the recursive core of the game. Inside every coalition, cooperative femtocells use advanced IA techniques to improve their downlink transmission rate. Simulation results show that the proposed coalition formation algorithm yields significant gains, in terms of average payoff per femtocell, reaching up to 30 percent relative to the noncooperative case for a network of N=300 femtocells.

The choice of a suitable backhaul constitutes one of the main performance bottlenecks in the emerging femtocell networks. In this paper, we study the impact of adopting a heterogenous backhaul (i.e., wired or over-the-air) with realistic quality-of-service requirements on coherent coordinated multipoint (CoMP) transmission in the downlink of femtocell networks. We formulate a cooperative game with continuum among the femtocell access points (FAPs) for performing CoMP in order to maximize the downlink rate while accounting for the constraints on the heterogeneous backhaul. In this respect, we propose a distributed algorithm that enables the FAPs to jointly decide on their cooperative partners as well as the choice of a backhaul strategy. In this respect, the proposed algorithm jointly addresses the problem of coalition formation as well as the optimization of the tradeoff between OTA and wired backhaul transmission modes, each of which is limited by a different factor such as delay or spectrum resources availability. We show that the proposed algorithm converges to a stable partition which constitutes the continuum core of the studied cooperative game. Simulation results show that our proposed scheme yields interesting gains in terms of the average downlink rate per FAP, reaching up to 26% relative to the classical of non-cooperative transmissions.

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 self-organize into a partition composed of disjoint coalitions which constitutes the recursive core of the game which is 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.

Underlay 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.

The sleeping strategy has become popular to reduce power consumption of base stations (BSs) by shutting down underutilized BSs in the management of green cellular networks. In this paper, we propose a novel solution for an energy efficient use of cellular networks, based on traffic load balancing. By modeling the power consumption for BSs connected to uniformly distributed users, the relationship between the optimal number of active (or shut down) BSs and the traffic load is then derived through the power ratio, which is the ratio between dynamic and fixed power part of BS power consumption. Both analytical and simulation results demonstrate that, in order to achieve significant energy savings, less BSs should be turned on at low traffic load while more BSs turned on at high traffic load.

Femtocells are envisioned to be deployed in indoor environments in order to improve both radio coverage and spectrum efficiency. This paper focuses on the self-organization of indoor femtocells, which includes mechanisms of cooperation. In this context, we propose a solution to automatically form cooperating groups among severely interfered femtocells in order to avoid interference. A hybrid access policy is proposed and compared to the closed and open policies. Results show that, as stated in the Braess Paradox, pervasive cooperation may be detrimental, when available resources are highly contended. Conversely, in particular cases, a marginal selfish behavior of femtocells can be preferable.

Overlaying low-power, low-cost, femtocells, over existing wireless networks has recently emerged as a means to significantly improve the coverage and performance of next-generation wireless networks. While most existing literature focuses on spectrum sharing and interference management among non-cooperative femtocells, in this paper, we propose a novel cooperative model that enables the femtocells to improve their performance by sharing spectral resources, minimizing the number of collisions, and maximizing the spatial reuse. We model the femtocell spectrum sharing problem as a coalitional game in partition form and we propose a distributed algorithm for coalition formation. Using the proposed algorithm, the femtocells can take autonomous decisions to cooperate and self-organize into a network partition composed of disjoint femtocell coalitions and that constitutes a stable partition which lies in the recursive core of the considered game. Whenever a coalition forms, the femtocells inside this coalition can cooperatively pool the occupied spectral resources. Additionally, the members of any given coalition jointly schedule their transmissions in order to avoid collisions, in a distributed way. Simulation results show that the proposed coalition formation algorithm yields a performance advantage, in terms of the average payoff (rate) per femtocell reaching up to 380% relative to the non-cooperative case.

This paper considers the use of predefined frequency-domain power profiles in downlink LTE-A aiming at making interference predictable across the Physical Resource Blocks, to be combined with fair resource allocation. In particular, the power profile structure is defined depending on the position of the users and fairness-oriented scheduling strategies are considered. Evaluations of the throughput and fairness achieved in the system depending on different scheduling algorithms are reported, as well as a comparison with scheduling strategies implementing power control techniques at similar complexity. Results show that, when resource allocation is SINR-based and focuses on cell-edge users, the highest sum rate and average per user rate is achieved without significant loss from the optimum fairness.

In this work, a mode identification system for superimposed signals in the same band is presented. More precisely, a pattern recognition approach, based on the Wigner distribution for features extraction and non parametric classifiers (k-nearest neighbors and Parzen) is proposed for identifying the transmission modes in an indoor wireless environment. A reconfigurable terminal, based on software defined radio technology, is considered aimed at the identification of the presence of two co-existent communication modes such as Bluetooth, based on frequency hopping - code division multiple access, and IEEE WLAN 802.11b, based on direct sequence - code division multiple access. Results in terms of error classification probability, expressed as relative error frequency, are provided with a comparison between the use of the two classifiers.