Nonuniform traffic distribution model in reverse link of multilaterate/multiservie WCDMA/based systems

This paper focuses on the modeling of the reverse link of a wideband code division multiple access system in a nonhomogeneous environment with a single cell. Multiple traffic spatial and service nonuniformities are considered in the analytical model, and then, expressions for required transmitted power and the associated outage probability and block error rate are derived. Special attention is also paid to the effect caused by different transmission bit rates and the spatial location of the traffic nonuniformities. From the presented expressions, it is possible to set appropriate load thresholds to control the desired error rate. Although the model considers a single cell, results in terms of maximum allowable load can also be applicable in multicell scenarios.Peer Reviewe

Using simulation to provide alternative solutions to the flowshop sequencing problem

In this paper we present SS-GNEH, a simulation-based algorithm for the Permutation Flowshop Sequencing Problem (PFSP). Given a PFSP instance, the SSGNEH algorithm incorporates a randomness criterion to the classical NEH heuristic and starts an iterative process in order to obtain a set of alternative solutions, each of which outperforms the NEH algorithm. Thus, a random but oriented local search of the space of solutions is performed, and a list of "good alternative solutions" is obtained. We can then consider several desired properties per solution other than maximum time employed, such as balanced idle times among machines, number of completed jobs at a given target time, etc. This allows the decision-maker to consider multiple solution characteristics other than just those defined by the aprioristic objective function. Therefore, our methodology provides flexibility during the sequence selection process, which may help to improve the scheduling process. Several tests have been performed to discuss the effectiveness of this approach. The results obtained so far are promising enough to encourage further developments on the algorithm and its applications in real-life scenariosPostprint (published version

Control y gestión de redes, septiembre 2013

Recurs d'aprenentatge de la Universitat Oberta de Catalunya.Recurso de aprendizaje de la "Universitat Oberta de Catalunya".Learning material of the "Universitat Oberta de Catalunya"

Control y gestión de redes, septiembre 2013

Recurs d'aprenentatge de la Universitat Oberta de Catalunya.Recurso de aprendizaje de la "Universitat Oberta de Catalunya".Learning material of the "Universitat Oberta de Catalunya"

Control i gestió de xarxes, setembre 2013

Recurs d'aprenentatge de la Universitat Oberta de Catalunya.Recurso de aprendizaje de la "Universitat Oberta de Catalunya".Learning material of the "Universitat Oberta de Catalunya"

Spectral Efficient and Energy Aware Clustering in Cellular Networks

The current and envisaged increase of cellular traffic poses new challenges to mobile network operators (MNO), who must densify their radio access networks (RAN) while maintaining low capital expenditure and operational expenditure to ensure long-Term sustainability. In this context, this paper analyzes optimal clustering solutions based on device-To-device communications to mitigate partially or completely the need for MNOs to carry out extremely dense RAN deployments. Specifically, a low-complexity algorithm that enables the creation of spectral efficient clusters among users from different cells, denoted as enhanced clustering optimization for resources' efficiency is presented. Due to the imbalance between uplink and downlink traffic, a complementary algorithm, known as clustering algorithm for load balancing, is also proposed to create nonspectral efficient clusters when they result in a capacity increase. Finally, in order to alleviate the energy overconsumption suffered by cluster heads, the clustering energy efficient algorithm (CEEa) is also designed to manage the tradeoff between the capacity enhancement and the early battery drain of some users. Results show that the proposed algorithms increase the network capacity and outperform existing solutions, while, at the same time, CEEa is able to handle the cluster heads energy overconsumption. © 1967-2012 IEEE

Scalable RAN virtualization in multitenant LTE-A heterogeneous networks

Cellular communications are evolving to facilitate the current and expected increasing needs of quality of service, high data rates, and diversity of offered services. Toward this direction, radio access network (RAN) virtualization aims at providing solutions of mapping virtual network elements onto radio resources of the existing physical network. This paper proposes the Resources nEgotiation for NEtwork Virtualization (RENEV) algorithm, which is suitable for application in heterogeneous networks in Long-Term Evolution Advanced (LTE-A) environments, consisting of a macro evolved Node B overlaid with small cells (SCs). By exploiting radio resource management principles, RENEV achieves slicing and on-demand delivery of resources. Leveraging the multitenancy approach, radio resources are transferred in terms of physical radio resource blocks among multiple heterogeneous base stations, which are interconnected via the X2 interface. The main target is to deal with traffic variations in geographical dimension. All signaling design considerations under the current Third-Generation Partnership Project LTE-A architecture are also investigated. Analytical studies and simulation experiments are conducted to evaluate RENEV in terms of the network's throughput and additional signaling overhead. Moreover, we show that RENEV can be applied independently on top of already proposed schemes for RAN virtualization to improve their performance. The results indicate that significant advantages are achieved both from the network's and users' perspective and that it is a scalable solution for different numbers of SCs

Scalable RAN virtualization in multitenant LTE-A heterogeneous networks

Cellular communications are evolving to facilitate the current and expected increasing needs of quality of service, high data rates, and diversity of offered services. Toward this direction, radio access network (RAN) virtualization aims at providing solutions of mapping virtual network elements onto radio resources of the existing physical network. This paper proposes the Resources nEgotiation for NEtwork Virtualization (RENEV) algorithm, which is suitable for application in heterogeneous networks in Long-Term Evolution Advanced (LTE-A) environments, consisting of a macro evolved Node B overlaid with small cells (SCs). By exploiting radio resource management principles, RENEV achieves slicing and on-demand delivery of resources. Leveraging the multitenancy approach, radio resources are transferred in terms of physical radio resource blocks among multiple heterogeneous base stations, which are interconnected via the X2 interface. The main target is to deal with traffic variations in geographical dimension. All signaling design considerations under the current Third-Generation Partnership Project LTE-A architecture are also investigated. Analytical studies and simulation experiments are conducted to evaluate RENEV in terms of the network's throughput and additional signaling overhead. Moreover, we show that RENEV can be applied independently on top of already proposed schemes for RAN virtualization to improve their performance. The results indicate that significant advantages are achieved both from the network's and users' perspective and that it is a scalable solution for different numbers of SCs

Spectral efficient and energy aware clustering in cellular networks

The current and envisaged increase of cellular traffic poses new challenges to mobile network operators (MNO), who must densify their radio access networks (RAN) while maintaining low capital expenditure and operational expenditure to ensure long-term sustainability. In this context, this paper analyzes optimal clustering solutions based on device-to-device communications to mitigate partially or completely the need for MNOs to carry out extremely dense RAN deployments. Specifically, a low-complexity algorithm that enables the creation of spectral efficient clusters among users from different cells, denoted as enhanced clustering optimization for resources' efficiency is presented. Due to the imbalance between uplink and downlink traffic, a complementary algorithm, known as clustering algorithm for load balancing, is also proposed to create nonspectral efficient clusters when they result in a capacity increase. Finally, in order to alleviate the energy overconsumption suffered by cluster heads, the clustering energy efficient algorithm (CEEa) is also designed to manage the tradeoff between the capacity enhancement and the early battery drain of some users. Results show that the proposed algorithms increase the network capacity and outperform existing solutions, while, at the same time, CEEa is able to handle the cluster heads energy overconsumption

Nonuniform traffic distribution model in reverse link of multilaterate/multiservie WCDMA/based systems

This paper focuses on the modeling of the reverse link of a wideband code division multiple access system in a nonhomogeneous environment with a single cell. Multiple traffic spatial and service nonuniformities are considered in the analytical model, and then, expressions for required transmitted power and the associated outage probability and block error rate are derived. Special attention is also paid to the effect caused by different transmission bit rates and the spatial location of the traffic nonuniformities. From the presented expressions, it is possible to set appropriate load thresholds to control the desired error rate. Although the model considers a single cell, results in terms of maximum allowable load can also be applicable in multicell scenarios.Peer Reviewe