Articles de revista
http://hdl.handle.net/2117/1256
Wed, 25 May 2016 22:54:43 GMT
20160525T22:54:43Z

Robust nonlinear precoding for downlink multiuser multipleinput multipleoutput orthogonal frequencydivision multiplexing systems with limited feedback
http://hdl.handle.net/2117/87169
Robust nonlinear precoding for downlink multiuser multipleinput multipleoutput orthogonal frequencydivision multiplexing systems with limited feedback
Font Segura, Josep; Su, Y.; Wang, Xiaodong
The authors consider the robust Tomlinson–Harashima precoding (THP) for downlink multiuser multipleinput
multipleoutput orthogonal frequencydivision multiplexing systems with quantised feedback. The authors discuss vector
channel feedback strategies in the frequency and time domains, and develop a robust version of THP that takes into account
of error statistics of the channel state information, that consists of the optimal feedforward filters, feedback filters and the
receive filters. Feedback techniques are developed to exploit the spatial correlations in realistic 3GPP channel models by
applying dimension reduction and scalarquantisation. Extensive simulations results are provided to demonstrate the
performance of the proposed robust THP design as well as the channel feedback scheme.
Wed, 18 May 2016 15:24:43 GMT
http://hdl.handle.net/2117/87169
20160518T15:24:43Z
Font Segura, Josep
Su, Y.
Wang, Xiaodong
The authors consider the robust Tomlinson–Harashima precoding (THP) for downlink multiuser multipleinput
multipleoutput orthogonal frequencydivision multiplexing systems with quantised feedback. The authors discuss vector
channel feedback strategies in the frequency and time domains, and develop a robust version of THP that takes into account
of error statistics of the channel state information, that consists of the optimal feedforward filters, feedback filters and the
receive filters. Feedback techniques are developed to exploit the spatial correlations in realistic 3GPP channel models by
applying dimension reduction and scalarquantisation. Extensive simulations results are provided to demonstrate the
performance of the proposed robust THP design as well as the channel feedback scheme.

A diffusionbased em algorithm for distributed estimation in unreliable sensor networks
http://hdl.handle.net/2117/86785
A diffusionbased em algorithm for distributed estimation in unreliable sensor networks
Silva Pereira, Silvana; López Valcarce, Roberto; Pagès Zamora, Alba Maria
We address the problem of distributed estimation of
a parameter from a set of noisy observations collected by a sensor
network, assuming that some sensors may be subject to data failures
and report only noise. In such scenario, simple schemes such
as the Best Linear Unbiased Estimator result in an error floor in
moderate and high signaltonoise ratio (SNR), whereas previously
proposed methods based on hard decisions on data failure events
degrade as the SNR decreases. Aiming at optimal performance
within the whole range of SNRs, we adopt a Maximum Likelihood
framework based on the ExpectationMaximization (EM) algorithm.
The statistical model and the iterative nature of the EM
method allow for a diffusionbased distributed implementation,
whereby the information propagation is embedded in the iterative
update of the parameters. Numerical examples show that the proposed
algorithm practically attains the Cramer–Rao Lower Bound
at all SNR values and compares favorably with other approaches.
Mon, 09 May 2016 13:09:07 GMT
http://hdl.handle.net/2117/86785
20160509T13:09:07Z
Silva Pereira, Silvana
López Valcarce, Roberto
Pagès Zamora, Alba Maria
We address the problem of distributed estimation of
a parameter from a set of noisy observations collected by a sensor
network, assuming that some sensors may be subject to data failures
and report only noise. In such scenario, simple schemes such
as the Best Linear Unbiased Estimator result in an error floor in
moderate and high signaltonoise ratio (SNR), whereas previously
proposed methods based on hard decisions on data failure events
degrade as the SNR decreases. Aiming at optimal performance
within the whole range of SNRs, we adopt a Maximum Likelihood
framework based on the ExpectationMaximization (EM) algorithm.
The statistical model and the iterative nature of the EM
method allow for a diffusionbased distributed implementation,
whereby the information propagation is embedded in the iterative
update of the parameters. Numerical examples show that the proposed
algorithm practically attains the Cramer–Rao Lower Bound
at all SNR values and compares favorably with other approaches.

NetworkMIMO for downlink inband relay transmissions
http://hdl.handle.net/2117/86775
NetworkMIMO for downlink inband relay transmissions
Lagén Morancho, Sandra; Agustín de Dios, Adrián; Vidal Manzano, José
With the objective of improving the spectral efficiency and coverage homogeneity of wireless cellular systems in the downlink, we investigate how to take advantage of two promising transmission technologies envisioned in current standards: networkMIMO and relay stations (RSs). It is assumed that halfduplex RSs are deployed in a cellular system, where the duration of the relayreceive and the relaytransmit phases is fixed beforehand for all cells. In order to reduce the spectral efficiency loses associated to halfduplex relaying, we propose the use of base station (BS) cooperation under a networkMIMO precoding strategy based on blockdiagonalization zeroforcing, and optimize radio resources under the convex performance criteria constrained by the perBS power, modulation and coding schemes and the transmission rate in the relaytransmit phase. By applying convex optimization techniques, the optimal precoding strategy is derived and a suboptimal low complexity solution is also proposed. The obtained solutions are evaluated at system level and compared to other cooperative and noncooperative BSbased schemes.
Mon, 09 May 2016 12:26:23 GMT
http://hdl.handle.net/2117/86775
20160509T12:26:23Z
Lagén Morancho, Sandra
Agustín de Dios, Adrián
Vidal Manzano, José
With the objective of improving the spectral efficiency and coverage homogeneity of wireless cellular systems in the downlink, we investigate how to take advantage of two promising transmission technologies envisioned in current standards: networkMIMO and relay stations (RSs). It is assumed that halfduplex RSs are deployed in a cellular system, where the duration of the relayreceive and the relaytransmit phases is fixed beforehand for all cells. In order to reduce the spectral efficiency loses associated to halfduplex relaying, we propose the use of base station (BS) cooperation under a networkMIMO precoding strategy based on blockdiagonalization zeroforcing, and optimize radio resources under the convex performance criteria constrained by the perBS power, modulation and coding schemes and the transmission rate in the relaytransmit phase. By applying convex optimization techniques, the optimal precoding strategy is derived and a suboptimal low complexity solution is also proposed. The obtained solutions are evaluated at system level and compared to other cooperative and noncooperative BSbased schemes.

Demandside management via distributed energy generation and storage optimization
http://hdl.handle.net/2117/86770
Demandside management via distributed energy generation and storage optimization
Atzeni, Italo; García Ordoñez, Luis; Scutari, Gesualdo; Palomar, Daniel P.; Rodríguez Fonollosa, Javier
Demandside management, together with the integration of distributed energy generation and storage, are considered increasingly essential elements for implementing the smart grid concept and balancing massive energy production from renewable sources. We focus on a smart grid in which the demandside comprises traditional users as well as users owning some kind of distributed energy sources and/or energy storage devices. By means of a dayahead optimization process regulated by an independent central unit, the latter users intend to reduce their monetary energy expense by producing or storing energy rather than just purchasing their energy needs from the grid. In this paper, we formulate the resulting grid optimization problem as a noncooperative game and analyze the existence of optimal strategies. Furthermore, we present a distributed algorithm to be run on the users' smart meters, which provides the optimal production and/or storage strategies, while preserving the privacy of the users and minimizing the required signaling with the central unit. Finally, the proposed dayahead optimization is tested in a realistic situation.
Mon, 09 May 2016 11:39:38 GMT
http://hdl.handle.net/2117/86770
20160509T11:39:38Z
Atzeni, Italo
García Ordoñez, Luis
Scutari, Gesualdo
Palomar, Daniel P.
Rodríguez Fonollosa, Javier
Demandside management, together with the integration of distributed energy generation and storage, are considered increasingly essential elements for implementing the smart grid concept and balancing massive energy production from renewable sources. We focus on a smart grid in which the demandside comprises traditional users as well as users owning some kind of distributed energy sources and/or energy storage devices. By means of a dayahead optimization process regulated by an independent central unit, the latter users intend to reduce their monetary energy expense by producing or storing energy rather than just purchasing their energy needs from the grid. In this paper, we formulate the resulting grid optimization problem as a noncooperative game and analyze the existence of optimal strategies. Furthermore, we present a distributed algorithm to be run on the users' smart meters, which provides the optimal production and/or storage strategies, while preserving the privacy of the users and minimizing the required signaling with the central unit. Finally, the proposed dayahead optimization is tested in a realistic situation.

Noncooperative and cooperative optimization of distributed energy generation and storage in the demandside of the smart grid
http://hdl.handle.net/2117/86708
Noncooperative and cooperative optimization of distributed energy generation and storage in the demandside of the smart grid
Atzeni, Italo; García Ordoñez, Luis; Scutari, Gesualdo; Palomar, Daniel P.; Rodríguez Fonollosa, Javier
The electric energy distribution infrastructure is undergoing a startling technological evolution with the development of the smart grid concept, which allows more interaction between the supplyand the demandside of the network and results in a great optimization potential. In this paper, we focus on a smart grid in which the demandside comprises traditional users as well as users owning some kind of distributed energy source and/or energy storage device. By means of a dayahead demandside management mechanism regulated through an independent central unit, the latter users are interested in reducing their monetary expense by producing or storing energy rather than just purchasing their energy needs from the grid. Using a general energy pricing model, we tackle the grid optimization design from two different perspectives: a useroriented optimization and an holisticbased design. In the former case, we optimize each user individually by formulating the grid optimization problem as a noncooperative game, whose solution analysis is addressed building on the theory of variational inequalities. In the latter case, we focus instead on the joint optimization of the whole system, allowing some cooperation among the users. For both formulations, we devise distributed and iterative algorithms providing the optimal production/storage strategies of the users, along with their convergence properties. Among all, the proposed algorithms preserve the users' privacy and require very limited signaling with the central unit.
Fri, 06 May 2016 14:01:19 GMT
http://hdl.handle.net/2117/86708
20160506T14:01:19Z
Atzeni, Italo
García Ordoñez, Luis
Scutari, Gesualdo
Palomar, Daniel P.
Rodríguez Fonollosa, Javier
The electric energy distribution infrastructure is undergoing a startling technological evolution with the development of the smart grid concept, which allows more interaction between the supplyand the demandside of the network and results in a great optimization potential. In this paper, we focus on a smart grid in which the demandside comprises traditional users as well as users owning some kind of distributed energy source and/or energy storage device. By means of a dayahead demandside management mechanism regulated through an independent central unit, the latter users are interested in reducing their monetary expense by producing or storing energy rather than just purchasing their energy needs from the grid. Using a general energy pricing model, we tackle the grid optimization design from two different perspectives: a useroriented optimization and an holisticbased design. In the former case, we optimize each user individually by formulating the grid optimization problem as a noncooperative game, whose solution analysis is addressed building on the theory of variational inequalities. In the latter case, we focus instead on the joint optimization of the whole system, allowing some cooperation among the users. For both formulations, we devise distributed and iterative algorithms providing the optimal production/storage strategies of the users, along with their convergence properties. Among all, the proposed algorithms preserve the users' privacy and require very limited signaling with the central unit.

Interference management in LTEbased HetNets: a practical approach
http://hdl.handle.net/2117/86431
Interference management in LTEbased HetNets: a practical approach
Font Bach, Oriol; Bartzoudis, Nikolaos; Pascual Iserte, Antonio; Payaró Llisterri, Miquel; Blanco, Luis; López Bueno, David; Molina Pena, Marc
Interference is a major obstacle in radio communications, especially when opportunistic frequency reuse is an inherent
requirement for maximising spectral ef¿ciency in heterogeneous networks. A typical example is encountered in cellular
communications where macrocelledge users receive interference from small cell transmissions that use the same radio
frequency band. Innovating interference management algorithms are employed towards this end, which because of their
interdependencies with numerous parameters of the target operating scenario and various lowlevel implementation
aspects, need to be prototyped in realtime signal processing platforms in order to be credibly veri¿ed. In this paper, we
present the development and experimental validation of a macrocell/femtocell coexistence scenario in close to reallife
conditions. The inclusion of an agile interference management scheme increased the signal processing complexity at
the physical layer. This overhead was appropriately addressed by engaging advanced parallel processing techniques,
optimisations of the arithmetic operations and intelligent reuse of logic and memory resources in the ¿eld programmable
gate array (FPGA)based baseband processing architecture
This is the peer reviewed version of the following article: [FontBach, O., Bartzoudis N., PascualIserte, A., Payaró M., Blanco L., López Bueno D., and Molina M. (2015) Interference management in LTEbased HetNets: a practical approach, Trans. Emerging Tel. Tech., 26, 195–215, doi: 10.1002/ett.2833.], which has been published in final form at [http://onlinelibrary.wiley.com/doi/10.1002/ett.2833/epdf]. This article may be used for noncommercial purposes in accordance with Wiley Terms and Conditions for SelfArchiving.
Fri, 29 Apr 2016 14:03:22 GMT
http://hdl.handle.net/2117/86431
20160429T14:03:22Z
Font Bach, Oriol
Bartzoudis, Nikolaos
Pascual Iserte, Antonio
Payaró Llisterri, Miquel
Blanco, Luis
López Bueno, David
Molina Pena, Marc
Interference is a major obstacle in radio communications, especially when opportunistic frequency reuse is an inherent
requirement for maximising spectral ef¿ciency in heterogeneous networks. A typical example is encountered in cellular
communications where macrocelledge users receive interference from small cell transmissions that use the same radio
frequency band. Innovating interference management algorithms are employed towards this end, which because of their
interdependencies with numerous parameters of the target operating scenario and various lowlevel implementation
aspects, need to be prototyped in realtime signal processing platforms in order to be credibly veri¿ed. In this paper, we
present the development and experimental validation of a macrocell/femtocell coexistence scenario in close to reallife
conditions. The inclusion of an agile interference management scheme increased the signal processing complexity at
the physical layer. This overhead was appropriately addressed by engaging advanced parallel processing techniques,
optimisations of the arithmetic operations and intelligent reuse of logic and memory resources in the ¿eld programmable
gate array (FPGA)based baseband processing architecture

Coexisting linear and widely linear transceivers in the MIMO interference
http://hdl.handle.net/2117/85426
Coexisting linear and widely linear transceivers in the MIMO interference
Lagén Morancho, Sandra; Agustín de Dios, Adrián; Vidal Manzano, José
Recent results have shown the benefits of widely
linear precoding (WLP) in the MIMO interference channel
(MIMO IC) assuming that all transmitters can follow the same
strategy. Motivated by a transitional scenario where legacy linear
transmitters coexist with widely linear ones, this work investigates
the general Kuser MIMO IC in a heterogeneous (linear and
widely linear) transmitter deployment. In particular, we address
the maximization of the weighted sumrate (WSR) for (widely)
linear transmit filters design through the use of the complexvalued
formulation. Since the maximum WSR problem is nonconvex,
and thus difficult to be solved, we formulate an equivalent
minimum weighted mean square error problem that allows
deriving closedform expressions for (widely) linear transceivers.
Then an iterative procedure is proposed, which is proven to reach
a stationary point of the maximum WSR problem. Simulations
show that the proposed procedure allows increasing the sumrate
as compared to coordinated linear transceiver schemes. The
gains are larger and significant in two different nonexclusive
conditions: as the interference level increases or when the number
of antennas is low.
©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Fri, 08 Apr 2016 12:04:34 GMT
http://hdl.handle.net/2117/85426
20160408T12:04:34Z
Lagén Morancho, Sandra
Agustín de Dios, Adrián
Vidal Manzano, José
Recent results have shown the benefits of widely
linear precoding (WLP) in the MIMO interference channel
(MIMO IC) assuming that all transmitters can follow the same
strategy. Motivated by a transitional scenario where legacy linear
transmitters coexist with widely linear ones, this work investigates
the general Kuser MIMO IC in a heterogeneous (linear and
widely linear) transmitter deployment. In particular, we address
the maximization of the weighted sumrate (WSR) for (widely)
linear transmit filters design through the use of the complexvalued
formulation. Since the maximum WSR problem is nonconvex,
and thus difficult to be solved, we formulate an equivalent
minimum weighted mean square error problem that allows
deriving closedform expressions for (widely) linear transceivers.
Then an iterative procedure is proposed, which is proven to reach
a stationary point of the maximum WSR problem. Simulations
show that the proposed procedure allows increasing the sumrate
as compared to coordinated linear transceiver schemes. The
gains are larger and significant in two different nonexclusive
conditions: as the interference level increases or when the number
of antennas is low.

Correlated multiple antennas spectrum sensing under calibration uncertainty
http://hdl.handle.net/2117/83853
Correlated multiple antennas spectrum sensing under calibration uncertainty
Pourgharehkhan, Zahra; Taherpour, Abbas; Sala Álvarez, José; Khattab, Tamer
We address the problem of spectrum sensing in cognitive radios (CRs) when the secondary user (SU) is equipped with a multiantenna receiver. We consider scenarios with correlation between the received channels at different antennas and unequal perantenna noise variances to accommodate calibration errors. First, we derive the exact as well as the asymptotic performance of the genieaided (benchmark) detector with perfect knowledge of the antenna correlation coefficients, the primary user (PU) signal power and the noise covariance matrix. Then, we consider the sensing problem in which the SU is noncognizant of the perantenna noise variances, the PU signal power and the correlation of channel gains, starting with a specific treatment of the twoantenna case. For a general multiantenna receiver, we propose combining the derived test statistics among all antenna pairs. The related optimization problem to obtain the optimum combination weights is analyzed, which requires the analytical performance characterization of the constituent twoantenna detector. Thus, we compute the exact performance of the proposed detector in a special case (a particular case of the Hadamard ratio test) in terms of its detection and false alarm probabilities. Performance analyses are verified with simulations, showing that the proposed detector outperforms several recentlyproposed multiantenna detectors for CR in the scenarios considered.
Fri, 04 Mar 2016 17:12:14 GMT
http://hdl.handle.net/2117/83853
20160304T17:12:14Z
Pourgharehkhan, Zahra
Taherpour, Abbas
Sala Álvarez, José
Khattab, Tamer
We address the problem of spectrum sensing in cognitive radios (CRs) when the secondary user (SU) is equipped with a multiantenna receiver. We consider scenarios with correlation between the received channels at different antennas and unequal perantenna noise variances to accommodate calibration errors. First, we derive the exact as well as the asymptotic performance of the genieaided (benchmark) detector with perfect knowledge of the antenna correlation coefficients, the primary user (PU) signal power and the noise covariance matrix. Then, we consider the sensing problem in which the SU is noncognizant of the perantenna noise variances, the PU signal power and the correlation of channel gains, starting with a specific treatment of the twoantenna case. For a general multiantenna receiver, we propose combining the derived test statistics among all antenna pairs. The related optimization problem to obtain the optimum combination weights is analyzed, which requires the analytical performance characterization of the constituent twoantenna detector. Thus, we compute the exact performance of the proposed detector in a special case (a particular case of the Hadamard ratio test) in terms of its detection and false alarm probabilities. Performance analyses are verified with simulations, showing that the proposed detector outperforms several recentlyproposed multiantenna detectors for CR in the scenarios considered.

Decentralized coordinated precoding for dense TDD small cell networks
http://hdl.handle.net/2117/81143
Decentralized coordinated precoding for dense TDD small cell networks
Lagén Morancho, Sandra; Agustín de Dios, Adrián; Vidal Manzano, José
Cellular networks need the densification of small eNBs (SeNBs) to face the tremendous data traffic demand growth, implying an interference increase and making transmit coordination a key enabler. This article proposes a decentralized coordinated precoding (DCoP) for downlink (DL) weighted sumrate maximization in dense MIMO TDD small cell networks (SCNs). Each SeNB designs its own precoding matrices based on channel state information (CSI) of the served users and knowledge of the interferencecost matrix that allows managing interference towards unintended users. A protocol is proposed to acquire the interferencecost matrix by processing the uplink (UL) received signal provided that: 1) channel reciprocity can be assumed and 2) all users participating in DL can transmit in UL with an adequate transmit filter. In contrast to existing transmit coordination techniques, DCoP is fully scalable, avoids estimation of the interfering channels, and does not require information exchange between SeNBs. In case all parameters are perfectly acquired, an iterative algorithm is presented with demonstrated monotonic convergence when all SeNBs update its transmit precoders simultaneously. Further, the problem is reformulated in order to derive a robust DCoP under imperfect CSI conditions. Finally, simulations in 3GPP LTEAdvanced SCNs show significant user packet throughput gains, without increasing the complexity associated to transmit coordination. Robustness to imperfect CSI and nonideal channel reciprocity is shown through simulations.
©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Fri, 08 Jan 2016 13:02:58 GMT
http://hdl.handle.net/2117/81143
20160108T13:02:58Z
Lagén Morancho, Sandra
Agustín de Dios, Adrián
Vidal Manzano, José
Cellular networks need the densification of small eNBs (SeNBs) to face the tremendous data traffic demand growth, implying an interference increase and making transmit coordination a key enabler. This article proposes a decentralized coordinated precoding (DCoP) for downlink (DL) weighted sumrate maximization in dense MIMO TDD small cell networks (SCNs). Each SeNB designs its own precoding matrices based on channel state information (CSI) of the served users and knowledge of the interferencecost matrix that allows managing interference towards unintended users. A protocol is proposed to acquire the interferencecost matrix by processing the uplink (UL) received signal provided that: 1) channel reciprocity can be assumed and 2) all users participating in DL can transmit in UL with an adequate transmit filter. In contrast to existing transmit coordination techniques, DCoP is fully scalable, avoids estimation of the interfering channels, and does not require information exchange between SeNBs. In case all parameters are perfectly acquired, an iterative algorithm is presented with demonstrated monotonic convergence when all SeNBs update its transmit precoders simultaneously. Further, the problem is reformulated in order to derive a robust DCoP under imperfect CSI conditions. Finally, simulations in 3GPP LTEAdvanced SCNs show significant user packet throughput gains, without increasing the complexity associated to transmit coordination. Robustness to imperfect CSI and nonideal channel reciprocity is shown through simulations.

Optimization of radio and computational resources for energy efficiency in latencyconstrained application offloading
http://hdl.handle.net/2117/79500
Optimization of radio and computational resources for energy efficiency in latencyconstrained application offloading
Muñoz Medina, Olga; Pascual Iserte, Antonio; Vidal Manzano, José
Providing femto access points (FAPs) with computational capabilities will allow (either total or partial) offloading of highly demanding applications from smartphones to the socalled femtocloud. Such offloading promises to be beneficial in terms of battery savings at the mobile terminal (MT) and/or in latency reduction in the execution of applications. However, for this promise to become a reality, the energy and/or the time required for the communication process must be compensated by the energy and/or the time savings that result from the remote computation at the FAPs. For this problem, we provide in this paper a framework for the joint optimization of the radio and computational resource usage exploiting the tradeoff between energy consumption and latency. Multiple antennas are assumed to be available at the MT and the serving FAP. As a result of the optimization, the optimal communication strategy (e.g., transmission power, rate, and precoder) is obtained, as well as the optimal distribution of the computational load between the handset and the serving FAP. This paper also establishes the conditions under which total or no offloading is optimal, determines which is the minimum affordable latency in the execution of the application, and analyzes, as a particular case, the minimization of the total consumed energy without latency constraints.
Thu, 19 Nov 2015 17:46:50 GMT
http://hdl.handle.net/2117/79500
20151119T17:46:50Z
Muñoz Medina, Olga
Pascual Iserte, Antonio
Vidal Manzano, José
Providing femto access points (FAPs) with computational capabilities will allow (either total or partial) offloading of highly demanding applications from smartphones to the socalled femtocloud. Such offloading promises to be beneficial in terms of battery savings at the mobile terminal (MT) and/or in latency reduction in the execution of applications. However, for this promise to become a reality, the energy and/or the time required for the communication process must be compensated by the energy and/or the time savings that result from the remote computation at the FAPs. For this problem, we provide in this paper a framework for the joint optimization of the radio and computational resource usage exploiting the tradeoff between energy consumption and latency. Multiple antennas are assumed to be available at the MT and the serving FAP. As a result of the optimization, the optimal communication strategy (e.g., transmission power, rate, and precoder) is obtained, as well as the optimal distribution of the computational load between the handset and the serving FAP. This paper also establishes the conditions under which total or no offloading is optimal, determines which is the minimum affordable latency in the execution of the application, and analyzes, as a particular case, the minimization of the total consumed energy without latency constraints.