The Experts below are selected from a list of 15726 Experts worldwide ranked by ideXlab platform

Luc Vandendorpe - One of the best experts on this subject based on the ideXlab platform.

  • power control in networks with heterogeneous users a quasi variational inequality approach
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    This paper deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a noncooperative game in which the utility function changes according to each player’s nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the noncooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium points and to derive novel algorithms that allow the network to converge to these points in an iterative manner, both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

  • Power Control in Networks With Heterogeneous Users: A Quasi-Variational Inequality Approach
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    —This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium points and to derive novel algorithms that allow the network to converge to these points in an iterative manner, both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

  • Energy-Efficient Power Optimization in Heterogeneous Networks: A Quasi-Variational Inequality Approach
    IEEE Transactions on Signal Processing, 2014
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    —This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium (NE) points and to derive novel algorithms that allow the network to converge to these points in an iterative manner both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

Muriel Medard - One of the best experts on this subject based on the ideXlab platform.

  • Processing of wireless signals to preserve wireline network resources
    Wireless Communications and Networking Conference, 1999
    Co-Authors: Muriel Medard
    Abstract:

    In order increase the capacity in the wireless domain, the signals from several distributed receivers may be combined. The combining of these signals typically requires transmission over a wireline network. In the wireline domain, signals may be transmitted to a single Centralized Processing node or may be processed in a distributed fashion at several nodes in the network. We compare, for white Gaussian noise channels, the capacity gains that can be obtained from distributed Processing of wireline signals to the capacity gains obtained using maximum likelihood ratio combining at a single Processing node. We find that, by using optimal detection techniques, the bandwidth requirements in the wireline domain can be significantly reduced without reducing the capacity in the wireless domain. These gains in capacity are achieved by eliminating transmission of redundant information in the wireline network.

  • WCNC - Processing of wireless signals to preserve wireline network resources
    WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466), 1999
    Co-Authors: Muriel Medard
    Abstract:

    In order increase the capacity in the wireless domain, the signals from several distributed receivers may be combined. The combining of these signals typically requires transmission over a wireline network. In the wireline domain, signals may be transmitted to a single Centralized Processing node or may be processed in a distributed fashion at several nodes in the network. We compare, for white Gaussian noise channels, the capacity gains that can be obtained from distributed Processing of wireline signals to the capacity gains obtained using maximum likelihood ratio combining at a single Processing node. We find that, by using optimal detection techniques, the bandwidth requirements in the wireline domain can be significantly reduced without reducing the capacity in the wireless domain. These gains in capacity are achieved by eliminating transmission of redundant information in the wireline network.

Ivan Stupia - One of the best experts on this subject based on the ideXlab platform.

  • power control in networks with heterogeneous users a quasi variational inequality approach
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    This paper deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a noncooperative game in which the utility function changes according to each player’s nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the noncooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium points and to derive novel algorithms that allow the network to converge to these points in an iterative manner, both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

  • Power Control in Networks With Heterogeneous Users: A Quasi-Variational Inequality Approach
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    —This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium points and to derive novel algorithms that allow the network to converge to these points in an iterative manner, both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

  • Energy-Efficient Power Optimization in Heterogeneous Networks: A Quasi-Variational Inequality Approach
    IEEE Transactions on Signal Processing, 2014
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    —This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium (NE) points and to derive novel algorithms that allow the network to converge to these points in an iterative manner both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

Luca Sanguinetti - One of the best experts on this subject based on the ideXlab platform.

  • Energy-aware competitive power allocation for heterogeneous networks under QoS constraints
    IEEE Transactions on Wireless Communications, 2015
    Co-Authors: Giacomo Bacci, E. Veronica Belmega, Panayotis Mertikopoulos, Luca Sanguinetti
    Abstract:

    This work proposes a distributed power allocation scheme for maximizing energy efficiency in the uplink of OFDMA-based HetNets where a macro-tier is augmented with small cell access points. Each user equipment (UE) in the network is modeled as a rational agent that engages in a non-cooperative game and allocates its available transmit power over the set of assigned subcarriers to maximize its individual utility (defined as the user's throughput per Watt of transmit power) subject to a target rate requirement. In this framework, the relevant solution concept is that of Debreu equilibrium, a generalization of the concept of Nash equilibrium. Using techniques from fractional programming, we provide a characterization of equilibrial power allocation profiles. In particular, Debreu equilibria are found to be the fixed points of a water-filling best response operator whose water level is a function of rate constraints and circuit power. Moreover, we also describe a set of sufficient conditions for the existence and uniqueness of Debreu equilibria exploiting the contraction properties of the best response operator. This analysis provides the necessary tools to derive a power allocation scheme that steers the network to equilibrium in an iterative and distributed manner without the need for any Centralized Processing. Numerical simulations are used to validate the analysis and assess the performance of the proposed algorithm as a function of the system parameters.

  • power control in networks with heterogeneous users a quasi variational inequality approach
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    This paper deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a noncooperative game in which the utility function changes according to each player’s nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the noncooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium points and to derive novel algorithms that allow the network to converge to these points in an iterative manner, both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

  • Power Control in Networks With Heterogeneous Users: A Quasi-Variational Inequality Approach
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    —This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium points and to derive novel algorithms that allow the network to converge to these points in an iterative manner, both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

  • Energy-Efficient Power Optimization in Heterogeneous Networks: A Quasi-Variational Inequality Approach
    IEEE Transactions on Signal Processing, 2014
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    —This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium (NE) points and to derive novel algorithms that allow the network to converge to these points in an iterative manner both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

Giacomo Bacci - One of the best experts on this subject based on the ideXlab platform.

  • Energy-aware competitive power allocation for heterogeneous networks under QoS constraints
    IEEE Transactions on Wireless Communications, 2015
    Co-Authors: Giacomo Bacci, E. Veronica Belmega, Panayotis Mertikopoulos, Luca Sanguinetti
    Abstract:

    This work proposes a distributed power allocation scheme for maximizing energy efficiency in the uplink of OFDMA-based HetNets where a macro-tier is augmented with small cell access points. Each user equipment (UE) in the network is modeled as a rational agent that engages in a non-cooperative game and allocates its available transmit power over the set of assigned subcarriers to maximize its individual utility (defined as the user's throughput per Watt of transmit power) subject to a target rate requirement. In this framework, the relevant solution concept is that of Debreu equilibrium, a generalization of the concept of Nash equilibrium. Using techniques from fractional programming, we provide a characterization of equilibrial power allocation profiles. In particular, Debreu equilibria are found to be the fixed points of a water-filling best response operator whose water level is a function of rate constraints and circuit power. Moreover, we also describe a set of sufficient conditions for the existence and uniqueness of Debreu equilibria exploiting the contraction properties of the best response operator. This analysis provides the necessary tools to derive a power allocation scheme that steers the network to equilibrium in an iterative and distributed manner without the need for any Centralized Processing. Numerical simulations are used to validate the analysis and assess the performance of the proposed algorithm as a function of the system parameters.

  • power control in networks with heterogeneous users a quasi variational inequality approach
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    This paper deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a noncooperative game in which the utility function changes according to each player’s nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the noncooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium points and to derive novel algorithms that allow the network to converge to these points in an iterative manner, both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

  • Power Control in Networks With Heterogeneous Users: A Quasi-Variational Inequality Approach
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    —This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium points and to derive novel algorithms that allow the network to converge to these points in an iterative manner, both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.

  • Energy-Efficient Power Optimization in Heterogeneous Networks: A Quasi-Variational Inequality Approach
    IEEE Transactions on Signal Processing, 2014
    Co-Authors: Ivan Stupia, Luca Sanguinetti, Giacomo Bacci, Luc Vandendorpe
    Abstract:

    —This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium (NE) points and to derive novel algorithms that allow the network to converge to these points in an iterative manner both with and without the need for a Centralized Processing. Numerical results are used to validate the proposed solutions in different operating conditions.