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Papers by Matteo Vincenzi

2017 IEEE International Conference on Communications (ICC), 2017

Facing the increasing energy demands associated with the perspective of fifth generation (5G) wir... more Facing the increasing energy demands associated with the perspective of fifth generation (5G) wireless networks, the Mobile Network Operators (MNOs) are motivated to gradually convert their traditional Radio Access Network (RAN) infrastructure to more flexible and power efficient centralized architectures, i.e., Cloud-RAN (C-RAN). Apart from their promising benefits in terms of management and network optimization, these new architectures further enable the sharing of spectrum and network elements, such as the Remote Radio Heads (RRHs) and the Baseband Units (BBUs), among multiple operators. In this paper, we introduce a novel scheme based on coalitional game theory to identify the potential room for cooperation among different MNOs that provide service to the same area. The proposed scheme sets the rules for profitable collaboration and identifies the core formation conditions (i.e., pricing) for various scenarios with different market and spectrum shares among three operators. Our results show that i) cooperation among subcoalitions of MNOs is always beneficial, yielding both higher revenues and enhanced Quality of Service (QoS) for the end users, and ii) the cooperation of all operators (grand coalition) is profitable for given user pricing in different scenarios.

IEEE Access, 2021

For guaranteeing the strict requirements foreseen for 5G, network slicing has been proposed as a ... more For guaranteeing the strict requirements foreseen for 5G, network slicing has been proposed as a dynamic and scalable mechanism for the allocation of customized resources to service providers. Many solutions have been proposed in the literature for the scenario where multiple service providers share the same pool of resources, while the exclusive allocation to different providers is still an open issue due to the associated complexity. In this work, we define a policy-based admission mechanism for exclusive intraservice slice allocation, at fine and adaptable timescales. In particular, we consider the case where optimal admission strategies are pre-computed offline for network state conditions that are representative of typical traffic loads and resource availability. This offline phase is also used to train a Machine learning algorithm; a neural network (NN) learns the best admission policies from a more computationally expensive mechanism in previously studied network conditions. Thus, the NN is used for providing near-optimal admission decisions at runtime under network conditions for which no optimal policy has been computed. The potential of the 5G marketplace in terms of revenue and quality of service is demonstrated for the particular case of services with strict latency constraints by means of a proof of concept tested over network traces from a real network operator. Different strategies are compared for the computation of the admission strategies and results are provided in terms of efficiency in resource utilization, fairness to the service providers, network owners' revenue and complexity. This study confirms the feasibility of a policy-based approach for exclusive intra-service resource allocation, especially if computationally-efficient mechanisms are adopted in the case of missing information about network states. INDEX TERMS 5G networks, mobile networks, network slicing, admission control, machine learning, neural networks, clustering, Markov processes, pricing.

IEEE Wireless Communications, 2017

The explosive data traffic demand in the context of the 5G revolution has stressed the need for n... more The explosive data traffic demand in the context of the 5G revolution has stressed the need for network capacity increase. As the network densification has almost reached its limits, mobile network operators are motivated to share their network infrastructure and the available resources through dynamic spectrum management. Although some initial efforts have been made to this direction by concluding sharing agreements at a coarse granularity (i.e., months or years), the 5G developments require fine timescale agreements, mainly enabled by network slicing. In this article, taking into account the radical changes foreseen for next generation networks, we provide a thorough discussion on the challenges that network slicing brings in the different network parts, while introducing a new entity capable of managing the end-to-end slicing in a coherent manner. In addition, according to the paradigm shift that operators share their resources in a common centralized pool, we design a cooperative game to study the potential cooperation aspects among the participants. The experimental results highlight the performance and financial gains achievable by operators through multi-tenant slicing, providing them with the necessary incentives for network upgrade towards 5G.

2014 IEEE Global Communications Conference, 2014

The increasing request of bandwidth for multimedia advanced services is one of the major issues o... more The increasing request of bandwidth for multimedia advanced services is one of the major issues of modern wireless systems. The spectrum shortage has been faced in several ways; among others the cognitive radio approach, aiming to exploit the unused spectrum resources already assigned to incumbent users, is maybe the most known. However, even if its application has been extensively proposed for wireless terrestrial communications, it remains a still unexplored area concerning Satellite Communications. The aim of this paper is to propose an Energy Detector based Radio Environment Mapping for the spectrum awareness functionality of a hybrid terrestrial/satellite scenario where the satellite components aim at exploiting the resources unused by terrestrial communications. The proposed approach allows to take advantage of cooperation between multiple sensing nodes evaluating spatial detection and false alarm probabilities besides their relationship with device detection and false alarm probabilities.

2017 IEEE International Conference on Communications (ICC), 2017

Facing the increasing energy demands associated with the perspective of fifth generation (5G) wir... more Facing the increasing energy demands associated with the perspective of fifth generation (5G) wireless networks, the Mobile Network Operators (MNOs) are motivated to gradually convert their traditional Radio Access Network (RAN) infrastructure to more flexible and power efficient centralized architectures, i.e., Cloud-RAN (C-RAN). Apart from their promising benefits in terms of management and network optimization, these new architectures further enable the sharing of spectrum and network elements, such as the Remote Radio Heads (RRHs) and the Baseband Units (BBUs), among multiple operators. In this paper, we introduce a novel scheme based on coalitional game theory to identify the potential room for cooperation among different MNOs that provide service to the same area. The proposed scheme sets the rules for profitable collaboration and identifies the core formation conditions (i.e., pricing) for various scenarios with different market and spectrum shares among three operators. Our results show that i) cooperation among subcoalitions of MNOs is always beneficial, yielding both higher revenues and enhanced Quality of Service (QoS) for the end users, and ii) the cooperation of all operators (grand coalition) is profitable for given user pricing in different scenarios.

IEEE Access, 2021

For guaranteeing the strict requirements foreseen for 5G, network slicing has been proposed as a ... more For guaranteeing the strict requirements foreseen for 5G, network slicing has been proposed as a dynamic and scalable mechanism for the allocation of customized resources to service providers. Many solutions have been proposed in the literature for the scenario where multiple service providers share the same pool of resources, while the exclusive allocation to different providers is still an open issue due to the associated complexity. In this work, we define a policy-based admission mechanism for exclusive intraservice slice allocation, at fine and adaptable timescales. In particular, we consider the case where optimal admission strategies are pre-computed offline for network state conditions that are representative of typical traffic loads and resource availability. This offline phase is also used to train a Machine learning algorithm; a neural network (NN) learns the best admission policies from a more computationally expensive mechanism in previously studied network conditions. Thus, the NN is used for providing near-optimal admission decisions at runtime under network conditions for which no optimal policy has been computed. The potential of the 5G marketplace in terms of revenue and quality of service is demonstrated for the particular case of services with strict latency constraints by means of a proof of concept tested over network traces from a real network operator. Different strategies are compared for the computation of the admission strategies and results are provided in terms of efficiency in resource utilization, fairness to the service providers, network owners' revenue and complexity. This study confirms the feasibility of a policy-based approach for exclusive intra-service resource allocation, especially if computationally-efficient mechanisms are adopted in the case of missing information about network states. INDEX TERMS 5G networks, mobile networks, network slicing, admission control, machine learning, neural networks, clustering, Markov processes, pricing.

IEEE Wireless Communications, 2017

The explosive data traffic demand in the context of the 5G revolution has stressed the need for n... more The explosive data traffic demand in the context of the 5G revolution has stressed the need for network capacity increase. As the network densification has almost reached its limits, mobile network operators are motivated to share their network infrastructure and the available resources through dynamic spectrum management. Although some initial efforts have been made to this direction by concluding sharing agreements at a coarse granularity (i.e., months or years), the 5G developments require fine timescale agreements, mainly enabled by network slicing. In this article, taking into account the radical changes foreseen for next generation networks, we provide a thorough discussion on the challenges that network slicing brings in the different network parts, while introducing a new entity capable of managing the end-to-end slicing in a coherent manner. In addition, according to the paradigm shift that operators share their resources in a common centralized pool, we design a cooperative game to study the potential cooperation aspects among the participants. The experimental results highlight the performance and financial gains achievable by operators through multi-tenant slicing, providing them with the necessary incentives for network upgrade towards 5G.

2014 IEEE Global Communications Conference, 2014

The increasing request of bandwidth for multimedia advanced services is one of the major issues o... more The increasing request of bandwidth for multimedia advanced services is one of the major issues of modern wireless systems. The spectrum shortage has been faced in several ways; among others the cognitive radio approach, aiming to exploit the unused spectrum resources already assigned to incumbent users, is maybe the most known. However, even if its application has been extensively proposed for wireless terrestrial communications, it remains a still unexplored area concerning Satellite Communications. The aim of this paper is to propose an Energy Detector based Radio Environment Mapping for the spectrum awareness functionality of a hybrid terrestrial/satellite scenario where the satellite components aim at exploiting the resources unused by terrestrial communications. The proposed approach allows to take advantage of cooperation between multiple sensing nodes evaluating spatial detection and false alarm probabilities besides their relationship with device detection and false alarm probabilities.