Articles de revista
http://hdl.handle.net/2117/1256
20170920T05:57:49Z

The TUCAN3G project: wireless technologies for isolated rural communities in developing countries based on 3G smallcell deployments
http://hdl.handle.net/2117/106554
The TUCAN3G project: wireless technologies for isolated rural communities in developing countries based on 3G smallcell deployments
Martínez Fernández, Andrés; Vidal Manzano, José; Simó Reigadas, Javier; Prieto Egido, Ignacio; Agustín de Dios, Adrián; Paco, Juan; Rendón, Álvaro
Recent years have witnessed a massive penetration of cellular systems in developing countries. However, isolated rural areas (sparsely
inhabited by lowincome population) have been disregarded because classical access and backhaul technologies do not ensure the return on investment. This article presents innovative technoeconomical solutions to provide these areas with cellular voice and data services. We first analyze the general characteristics of isolated rural communities, and based on this information, lowcost solutions are designed for both access (using 3G access points) and backhaul networks (using noncarrier grade equipment as WiFi for long distances or WiMAX in nonlicensed bands). Subsequently, a study of populationdependent income vs. costs is presented, and a new business model is proposed involving mobile network operators, rural operators, and infrastructure providers. In order to test these solutions, we have built two demonstration platforms in the Peruvian jungle that have allowed validation of the technical feasibility of the solution, verifying the business model assumptions and the scalability of the initiative.
20170718T08:32:34Z
Martínez Fernández, Andrés
Vidal Manzano, José
Simó Reigadas, Javier
Prieto Egido, Ignacio
Agustín de Dios, Adrián
Paco, Juan
Rendón, Álvaro
Recent years have witnessed a massive penetration of cellular systems in developing countries. However, isolated rural areas (sparsely
inhabited by lowincome population) have been disregarded because classical access and backhaul technologies do not ensure the return on investment. This article presents innovative technoeconomical solutions to provide these areas with cellular voice and data services. We first analyze the general characteristics of isolated rural communities, and based on this information, lowcost solutions are designed for both access (using 3G access points) and backhaul networks (using noncarrier grade equipment as WiFi for long distances or WiMAX in nonlicensed bands). Subsequently, a study of populationdependent income vs. costs is presented, and a new business model is proposed involving mobile network operators, rural operators, and infrastructure providers. In order to test these solutions, we have built two demonstration platforms in the Peruvian jungle that have allowed validation of the technical feasibility of the solution, verifying the business model assumptions and the scalability of the initiative.

Joint user scheduling, precoder design, and transmit direction selection in MIMO TDD small cell networks
http://hdl.handle.net/2117/104756
Joint user scheduling, precoder design, and transmit direction selection in MIMO TDD small cell networks
Lagén Morancho, Sandra; Agustín de Dios, Adrián; Vidal Manzano, José
New shortlength singledirection frame structures are proposed for 5G time division duplex (TDD) systems, where the transmit direction [i.e., either downlink (DL) or uplink (UL)] can be independently chosen at each cell in every frame. Accordingly, high flexibility is provided to match the percell DL/UL traffic asymmetries and full exploitation of dynamic TDD is allowed. As a downside, interference management becomes crucial. In this regard, this paper proposes a procedure for dynamic TDD in dense multipleinput multipleoutput small cell networks, where the transmit direction selected per small cell (SC) is dynamically optimized together with the user scheduling and transmit precoding. We focus on the maximization of a general utility function that takes into account the DL/UL traffic asymmetries of each user and the interference conditions in the network. Although the problem is nonconvex, it is decomposed thanks to the interferencecost concept and then efficiently solved in parallel. Simulation results show gains in DL and UL average rates for different traffic asymmetries and SC/user densities as compared to existing dynamic TDD schemes thanks to the proposed joint optimization. The gains become more significant when there is high interference and limited number of antennas.
©2017 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.
20170523T10:34:26Z
Lagén Morancho, Sandra
Agustín de Dios, Adrián
Vidal Manzano, José
New shortlength singledirection frame structures are proposed for 5G time division duplex (TDD) systems, where the transmit direction [i.e., either downlink (DL) or uplink (UL)] can be independently chosen at each cell in every frame. Accordingly, high flexibility is provided to match the percell DL/UL traffic asymmetries and full exploitation of dynamic TDD is allowed. As a downside, interference management becomes crucial. In this regard, this paper proposes a procedure for dynamic TDD in dense multipleinput multipleoutput small cell networks, where the transmit direction selected per small cell (SC) is dynamically optimized together with the user scheduling and transmit precoding. We focus on the maximization of a general utility function that takes into account the DL/UL traffic asymmetries of each user and the interference conditions in the network. Although the problem is nonconvex, it is decomposed thanks to the interferencecost concept and then efficiently solved in parallel. Simulation results show gains in DL and UL average rates for different traffic asymmetries and SC/user densities as compared to existing dynamic TDD schemes thanks to the proposed joint optimization. The gains become more significant when there is high interference and limited number of antennas.

Spectral feature detection with SubNyquist sampling for wideband spectrum sensing
http://hdl.handle.net/2117/103450
Spectral feature detection with SubNyquist sampling for wideband spectrum sensing
Lagunas Targarona, Eva; Nájar Martón, Montserrat
Compressive sensing (CS) has been successfully applied to alleviate the sampling bottleneck in wideband spectrum sensing leveraging the sparsity described by the low spectral occupancy of the licensed radios. However, the existence of interferences emanating from lowregulated transmissions, which cannot be taken into account in the CS model because of their nonregulated nature, greatly degrade the identification of licensed activity. This paper presents a featurebased technique for primary user's spectrum identification with interference immunity which works with a reduced amount of data. The proposed method not only detects which frequencies are occupied by primary users' but also identifies the primary users' transmitted power. The basic strategy is to compare the a priori known spectral shape of the primary user with the power spectral density of the received signal. This comparison ismade in terms of autocorrelation by means of a correlation matching, thus avoiding the computation of the power spectral density of the received signal. The essence of the novel interference rejection mechanism lies in preserving the positive semidefinite character of the residual correlation, which is inserted by means of a weighted formulation of the l(1)minimization. Simulation results show the effectiveness of the technique for interference suppression and primary user detection.
20170407T11:59:00Z
Lagunas Targarona, Eva
Nájar Martón, Montserrat
Compressive sensing (CS) has been successfully applied to alleviate the sampling bottleneck in wideband spectrum sensing leveraging the sparsity described by the low spectral occupancy of the licensed radios. However, the existence of interferences emanating from lowregulated transmissions, which cannot be taken into account in the CS model because of their nonregulated nature, greatly degrade the identification of licensed activity. This paper presents a featurebased technique for primary user's spectrum identification with interference immunity which works with a reduced amount of data. The proposed method not only detects which frequencies are occupied by primary users' but also identifies the primary users' transmitted power. The basic strategy is to compare the a priori known spectral shape of the primary user with the power spectral density of the received signal. This comparison ismade in terms of autocorrelation by means of a correlation matching, thus avoiding the computation of the power spectral density of the received signal. The essence of the novel interference rejection mechanism lies in preserving the positive semidefinite character of the residual correlation, which is inserted by means of a weighted formulation of the l(1)minimization. Simulation results show the effectiveness of the technique for interference suppression and primary user detection.

Sparse multiple relay selection for network beamforming with individual power constraints using semidefinite relaxation
http://hdl.handle.net/2117/101912
Sparse multiple relay selection for network beamforming with individual power constraints using semidefinite relaxation
Blanco, Luis; Nájar Martón, Montserrat
This paper deals with the multiple relay selection problem in twohop wireless cooperative networks with individual power constraints at the relays. In particular, it addresses the problem of selecting the best subset of K cooperative nodes and their corresponding beamforming weights so that the signaltonoise ratio (SNR) is maximized at the destination. This problem is computationally demanding and requires an exhaustive search over all the possible combinations. In order to reduce the complexity, a new suboptimal method is proposed. This technique exhibits a nearoptimal performance with a computational burden that is far less than the one needed in the combinatorial search. The proposed method is based on the use of the l1norm squared and the CharnesCooper transformation and naturally leads to a semidefinite programming relaxation with an affordable computational cost. Contrary to other approaches in the literature, the technique exposed herein is based on the knowledge of the secondorder statistics of the channels and the relays are not limited to cooperate with full power.
20170303T11:54:54Z
Blanco, Luis
Nájar Martón, Montserrat
This paper deals with the multiple relay selection problem in twohop wireless cooperative networks with individual power constraints at the relays. In particular, it addresses the problem of selecting the best subset of K cooperative nodes and their corresponding beamforming weights so that the signaltonoise ratio (SNR) is maximized at the destination. This problem is computationally demanding and requires an exhaustive search over all the possible combinations. In order to reduce the complexity, a new suboptimal method is proposed. This technique exhibits a nearoptimal performance with a computational burden that is far less than the one needed in the combinatorial search. The proposed method is based on the use of the l1norm squared and the CharnesCooper transformation and naturally leads to a semidefinite programming relaxation with an affordable computational cost. Contrary to other approaches in the literature, the technique exposed herein is based on the knowledge of the secondorder statistics of the channels and the relays are not limited to cooperate with full power.

Achievable DoFdelay tradeoffs for the Kuser MIMO interference channel with delayed CSIT
http://hdl.handle.net/2117/100973
Achievable DoFdelay tradeoffs for the Kuser MIMO interference channel with delayed CSIT
Torrellas, Marc; Agustín de Dios, Adrián; Vidal Manzano, José
The degrees of freedom (DoFs) of the Kuser multipleinput multipleoutput (MIMO) interference channel are studied when perfect, but delayed channel state information is available at the transmitter side (delayed CSIT). Recent works have proposed schemes improving the DoF knowledge of the interference channel, but at the cost of developing transmission involving many channel uses (long delay), thus increasing the complexity at both transmitter and receiver side. This paper proposes three linear precoding strategies, limited to at most three phases, based on the concept of interference alignment, and built upon three main ingredients: delayed CSIT precoding, user scheduling, and redundancy transmission. In this respect, the interference alignment is realized by exploiting delayed CSIT to align the interference at the nonintended receivers along the spacetime domain. Moreover, a new framework is proposed where the number of transmitted symbols and duration of the phases is obtained as the solution of a maximization problem, and enabling the introduction of complexity constraints, which allows deriving the achievable DoF as a function of the transmission delay, i.e., the achievable DoFdelay tradeoff. Finally, the latter part of this paper settles that the assumption of timevarying channels common along all the literature on delayed CSIT is indeed unnecessary.
©2016 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.
20170214T12:34:54Z
Torrellas, Marc
Agustín de Dios, Adrián
Vidal Manzano, José
The degrees of freedom (DoFs) of the Kuser multipleinput multipleoutput (MIMO) interference channel are studied when perfect, but delayed channel state information is available at the transmitter side (delayed CSIT). Recent works have proposed schemes improving the DoF knowledge of the interference channel, but at the cost of developing transmission involving many channel uses (long delay), thus increasing the complexity at both transmitter and receiver side. This paper proposes three linear precoding strategies, limited to at most three phases, based on the concept of interference alignment, and built upon three main ingredients: delayed CSIT precoding, user scheduling, and redundancy transmission. In this respect, the interference alignment is realized by exploiting delayed CSIT to align the interference at the nonintended receivers along the spacetime domain. Moreover, a new framework is proposed where the number of transmitted symbols and duration of the phases is obtained as the solution of a maximization problem, and enabling the introduction of complexity constraints, which allows deriving the achievable DoF as a function of the transmission delay, i.e., the achievable DoFdelay tradeoff. Finally, the latter part of this paper settles that the assumption of timevarying channels common along all the literature on delayed CSIT is indeed unnecessary.

Joint optimization of power and data transfer in multiuser MIMO systems
http://hdl.handle.net/2117/99198
Joint optimization of power and data transfer in multiuser MIMO systems
Rubio López, Javier; Pascual Iserte, Antonio; Palomar, Daniel P.; Goldsmith, Andrea
We present an approach to solve the nonconvex optimization problem that arises when designing the transmit covariance matrices in multiuser multipleinput multipleoutput (MIMO) broadcast networks implementing simultaneous wireless information and power transfer (SWIPT). The MIMO SWIPT problem is formulated as a general multiobjective optimization problem, in which data rates and harvested powers are optimized simultaneously. Two different approaches are applied to reformulate the (nonconvex) multiobjective problem. In the first approach, the transmitter can control the specific amount of power to be harvested by power transfer whereas in the second approach the transmitter can only control the proportion of power to be harvested among the different harvesting users. We solve the resulting formulations using the majorizationminimization (MM) approach. The solution obtained from the MM approach is compared to the classical blockdiagonalization (BD) strategy, typically used to solve the nonconvex multiuser MIMO network by forcing no interference among users. Simulation results show that the proposed approach improves over the BD approach both the system sum rate and the power harvested by users. Additionally, the computational times needed for convergence of the proposed methods are much lower than the ones required for classical gradientbased approaches.
20170113T09:41:19Z
Rubio López, Javier
Pascual Iserte, Antonio
Palomar, Daniel P.
Goldsmith, Andrea
We present an approach to solve the nonconvex optimization problem that arises when designing the transmit covariance matrices in multiuser multipleinput multipleoutput (MIMO) broadcast networks implementing simultaneous wireless information and power transfer (SWIPT). The MIMO SWIPT problem is formulated as a general multiobjective optimization problem, in which data rates and harvested powers are optimized simultaneously. Two different approaches are applied to reformulate the (nonconvex) multiobjective problem. In the first approach, the transmitter can control the specific amount of power to be harvested by power transfer whereas in the second approach the transmitter can only control the proportion of power to be harvested among the different harvesting users. We solve the resulting formulations using the majorizationminimization (MM) approach. The solution obtained from the MM approach is compared to the classical blockdiagonalization (BD) strategy, typically used to solve the nonconvex multiuser MIMO network by forcing no interference among users. Simulation results show that the proposed approach improves over the BD approach both the system sum rate and the power harvested by users. Additionally, the computational times needed for convergence of the proposed methods are much lower than the ones required for classical gradientbased approaches.

A framework for joint design of pilot sequence and linear precoder
http://hdl.handle.net/2117/99187
A framework for joint design of pilot sequence and linear precoder
Pastore, Adriano; Joham, Michael; Rodríguez Fonollosa, Javier
Most performance measures of pilotassisted multipleinput multipleoutput systems are functions of the linear precoder and the pilot sequence. A framework for the optimization of these two parameters is proposed, based on a matrixvalued generalization of the concept of effective signaltonoise ratio (SNR) introduced in the famous work by Hassibi and Hochwald. Our framework aims to extend the work of Hassibi and Hochwald by allowing for transmitside fading correlations, and by considering a class of utility functions of said effective SNR matrix, most notably including the wellknown capacity lower bound used by Hassibi and Hochwald. We tackle the joint optimization problem by recasting the optimization of the precoder (resp. pilot sequence) subject to a fixed pilot sequence (resp. precoder) into a convex problem. Furthermore, we prove that joint optimality requires that the eigenbases of the precoder and pilot sequence be both aligned along the eigenbasis of the channel correlation matrix. We finally describe how to wrap all studied subproblems into an iteration that converges to a local optimum of the joint optimization.
20170113T09:20:05Z
Pastore, Adriano
Joham, Michael
Rodríguez Fonollosa, Javier
Most performance measures of pilotassisted multipleinput multipleoutput systems are functions of the linear precoder and the pilot sequence. A framework for the optimization of these two parameters is proposed, based on a matrixvalued generalization of the concept of effective signaltonoise ratio (SNR) introduced in the famous work by Hassibi and Hochwald. Our framework aims to extend the work of Hassibi and Hochwald by allowing for transmitside fading correlations, and by considering a class of utility functions of said effective SNR matrix, most notably including the wellknown capacity lower bound used by Hassibi and Hochwald. We tackle the joint optimization problem by recasting the optimization of the precoder (resp. pilot sequence) subject to a fixed pilot sequence (resp. precoder) into a convex problem. Furthermore, we prove that joint optimality requires that the eigenbases of the precoder and pilot sequence be both aligned along the eigenbasis of the channel correlation matrix. We finally describe how to wrap all studied subproblems into an iteration that converges to a local optimum of the joint optimization.

On the superiority of improper Gaussian signaling in wireless interference MIMO scenarios
http://hdl.handle.net/2117/98936
On the superiority of improper Gaussian signaling in wireless interference MIMO scenarios
Lagén Morancho, Sandra; Agustín de Dios, Adrián; Vidal Manzano, José
Recent results have elucidated the benefits of using improper Gaussian signaling (IGS) as compared to conventional proper Gaussian signaling (PGS) in terms of achievable rate for interferencelimited conditions. This paper exploits majorization
theory tools to formally quantify the gains of IGS along with widely linear transceivers for MIMO systems in interferencelimited scenarios. The MIMO pointtopoint channel with interference (P2PI) is analyzed, assuming that received interference can be either proper or improper, and we demonstrate that the
use of the optimal IGS when received interference is improper strictly outperforms (in terms of achievable rate and mean square error) the use of the optimal PGS when interference is proper.
Then, these results are extended to two practical situations. First, the MIMO Zinterference channel (ZIC) is investigated, where a tradeoff arises: with IGS we could increase the achievable rate of the interfered user while gracefully degrading the rate of the noninterfered user. Second, these concepts are applied to a
twotier heterogeneous cellular network (HCN) where macrocells and smallcells coexist and multiple MIMO ZIC appear.
©2016 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.
20170110T10:35:27Z
Lagén Morancho, Sandra
Agustín de Dios, Adrián
Vidal Manzano, José
Recent results have elucidated the benefits of using improper Gaussian signaling (IGS) as compared to conventional proper Gaussian signaling (PGS) in terms of achievable rate for interferencelimited conditions. This paper exploits majorization
theory tools to formally quantify the gains of IGS along with widely linear transceivers for MIMO systems in interferencelimited scenarios. The MIMO pointtopoint channel with interference (P2PI) is analyzed, assuming that received interference can be either proper or improper, and we demonstrate that the
use of the optimal IGS when received interference is improper strictly outperforms (in terms of achievable rate and mean square error) the use of the optimal PGS when interference is proper.
Then, these results are extended to two practical situations. First, the MIMO Zinterference channel (ZIC) is investigated, where a tradeoff arises: with IGS we could increase the achievable rate of the interfered user while gracefully degrading the rate of the noninterfered user. Second, these concepts are applied to a
twotier heterogeneous cellular network (HCN) where macrocells and smallcells coexist and multiple MIMO ZIC appear.

A polynomial rooting approach for synchronization in multipath channels using antenna arrays
http://hdl.handle.net/2117/98478
A polynomial rooting approach for synchronization in multipath channels using antenna arrays
Seco Granados, Gonzalo; Swindlehurst, A K; Fernández Rubio, Juan Antonio
The estimation of the delay of a known training signal received
by an antenna array in a multipath channel is addressed.
The effect of the cochannel interference is taken
into account by including a term with unknown spatial correlation.
The channel is modeled as an unstructured FIR
filter. The exact maximum likelihood (ML) solution for
this problem is derived, but it does not have a simple dependence
on the delay. An approximate estimator that is
asymptotically equivalent to the exact one is presented. Using
an appropriate reparameterization, it is shown that the
delay estimate is obtained by rooting a loworder polynomial,
which may be of interest in applications where fast
feedforward synchronization is needed.
20161216T14:53:06Z
Seco Granados, Gonzalo
Swindlehurst, A K
Fernández Rubio, Juan Antonio
The estimation of the delay of a known training signal received
by an antenna array in a multipath channel is addressed.
The effect of the cochannel interference is taken
into account by including a term with unknown spatial correlation.
The channel is modeled as an unstructured FIR
filter. The exact maximum likelihood (ML) solution for
this problem is derived, but it does not have a simple dependence
on the delay. An approximate estimator that is
asymptotically equivalent to the exact one is presented. Using
an appropriate reparameterization, it is shown that the
delay estimate is obtained by rooting a loworder polynomial,
which may be of interest in applications where fast
feedforward synchronization is needed.

Guest editorial: adaptive antennas in wireless communications
http://hdl.handle.net/2117/98356
Guest editorial: adaptive antennas in wireless communications
Rodríguez Fonollosa, Javier
20161215T14:51:02Z
Rodríguez Fonollosa, Javier