Articles de revista
http://hdl.handle.net/2117/1256
20160504T18:01:26Z

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.
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.
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.
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.
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.
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.

On the performance of Hadamard ratio detectorbased spectrum sensing for cognitive radios
http://hdl.handle.net/2117/79165
On the performance of Hadamard ratio detectorbased spectrum sensing for cognitive radios
Sedighi, Saeid; Taherpour, Abbas; Sala Álvarez, José; Khattab, Tamer
We consider the problem of multiantenna spectrum sensing (SS) in cognitive radios (CRs) when the receivers are assumed to be uncalibrated across the antennas. The performance of the Hadamard Ratio Detector (HRD) is analyzed in such a scenario. Specifically, we first derive the exact distribution of the HRD statistic under the null hypothesis, which leads to an elaborate but closedform expression for the falsealarm probability. Then, we derive a simpler and tight closedform approximation for both the falsealarm and detection probabilities by using a momentbased approximation of the HRD statistical distribution under both hypotheses. Finally, the accuracy of the obtained results is verified by simulations.
20151112T15:42:12Z
Sedighi, Saeid
Taherpour, Abbas
Sala Álvarez, José
Khattab, Tamer
We consider the problem of multiantenna spectrum sensing (SS) in cognitive radios (CRs) when the receivers are assumed to be uncalibrated across the antennas. The performance of the Hadamard Ratio Detector (HRD) is analyzed in such a scenario. Specifically, we first derive the exact distribution of the HRD statistic under the null hypothesis, which leads to an elaborate but closedform expression for the falsealarm probability. Then, we derive a simpler and tight closedform approximation for both the falsealarm and detection probabilities by using a momentbased approximation of the HRD statistical distribution under both hypotheses. Finally, the accuracy of the obtained results is verified by simulations.

Nonuniform sampling walls in wideband signal detection
http://hdl.handle.net/2117/26802
Nonuniform sampling walls in wideband signal detection
Font Segura, Josep; Vázquez Grau, Gregorio; Riba Sagarra, Jaume
This work shows the existence of sampling walls in detection of wideband signals from Bernoulli nonuniform sampling (BNS) in the presence of noise uncertainty. A sampling wall is defined as the sampling density below which the target error probabilities, i.e., the missed detection and false alarm probabilities, cannot be guaranteed at a given signal to noise ratio (SNR) regardless the number of acquired samples. The BNS is adopted because it exhibits good tradeoff properties between complexity and performance. It is shown that BNS suffers from noise enhancement, which translates into a whitening effect in the correlation of the legacy signal. Contrarily to the existing literature, the signal detection problem is addressed without having to reconstruct neither the signal nor its spectrum. More specifically, the optimal low SNR detector is formulated as a generalized likelihood ratio test (GLRT) to exploit the available side information of the problem, i.e., the noise variance, the sampling density and the legacy signal autocorrelation. By deriving the asymptotic performance of the GLRT in the presence of noise uncertainty, explicit expressions for sampling walls are obtained as a function of the legacy signal occupancy, the SNR and the noise uncertainty. Further, numerical results are provided to assess the behavior of the sampling walls and signal detection performance.
20150318T12:50:40Z
Font Segura, Josep
Vázquez Grau, Gregorio
Riba Sagarra, Jaume
This work shows the existence of sampling walls in detection of wideband signals from Bernoulli nonuniform sampling (BNS) in the presence of noise uncertainty. A sampling wall is defined as the sampling density below which the target error probabilities, i.e., the missed detection and false alarm probabilities, cannot be guaranteed at a given signal to noise ratio (SNR) regardless the number of acquired samples. The BNS is adopted because it exhibits good tradeoff properties between complexity and performance. It is shown that BNS suffers from noise enhancement, which translates into a whitening effect in the correlation of the legacy signal. Contrarily to the existing literature, the signal detection problem is addressed without having to reconstruct neither the signal nor its spectrum. More specifically, the optimal low SNR detector is formulated as a generalized likelihood ratio test (GLRT) to exploit the available side information of the problem, i.e., the noise variance, the sampling density and the legacy signal autocorrelation. By deriving the asymptotic performance of the GLRT in the presence of noise uncertainty, explicit expressions for sampling walls are obtained as a function of the legacy signal occupancy, the SNR and the noise uncertainty. Further, numerical results are provided to assess the behavior of the sampling walls and signal detection performance.

The DoF of the 3User (p, p+1) MIMO Interference Channel
http://hdl.handle.net/2117/25955
The DoF of the 3User (p, p+1) MIMO Interference Channel
Torrellas Socastro, Marc; Agustín de Dios, Adrián; Vidal Manzano, José; Muñoz Medina, Olga
The degrees of freedom (DoF) of the 3user multipleinput multipleoutput (MIMO) interference channel (IC) with full channel state information and constant channel coefficients are investigated when (p, p + 1) antennas are deployed at the transmitters and receivers, respectively. The point of departure of this paper is the work of Wang et al., which conjectured but did not prove the DoF for the antenna settings with p > 1. Here the achievability of the DoF outer bound is formally proved using linear methods, thereby avoiding the use of the rational dimensions framework. The proposed transmission scheme exploits asymmetric complex signaling together with symbol extensions in time and space interference alignment concepts. While the paper deals with the p = 2, 3, ... , 6 cases, providing the specific transmit and receive filters, there are also provided the tools needed for proving the achievability of the optimal DoF for p > 6, whose DoF characterization is conjectured.
20150119T16:22:41Z
Torrellas Socastro, Marc
Agustín de Dios, Adrián
Vidal Manzano, José
Muñoz Medina, Olga
The degrees of freedom (DoF) of the 3user multipleinput multipleoutput (MIMO) interference channel (IC) with full channel state information and constant channel coefficients are investigated when (p, p + 1) antennas are deployed at the transmitters and receivers, respectively. The point of departure of this paper is the work of Wang et al., which conjectured but did not prove the DoF for the antenna settings with p > 1. Here the achievability of the DoF outer bound is formally proved using linear methods, thereby avoiding the use of the rational dimensions framework. The proposed transmission scheme exploits asymmetric complex signaling together with symbol extensions in time and space interference alignment concepts. While the paper deals with the p = 2, 3, ... , 6 cases, providing the specific transmit and receive filters, there are also provided the tools needed for proving the achievability of the optimal DoF for p > 6, whose DoF characterization is conjectured.

Single and multifrequency wideband spectrum sensing with sideinformation
http://hdl.handle.net/2117/25065
Single and multifrequency wideband spectrum sensing with sideinformation
Font Segura, Josep; Vázquez Grau, Gregorio; Riba Sagarra, Jaume
This study addresses the optimal spectrum sensing detection based on the complete or partial sideinformation on the signal and noise statistics. The use of the generalisedlikelihood ratio test (GLRT) involves maximumlikelihood (ML) estimation of the nuisances. ML estimation of the unknowns is especially challenging for wideband cognitive radio because closedform solutions are often not available. Based on the equivalence between the wideband regime and the lowsignaltonoise ratio regime, this study provides a general kernel framework for GLRT spectrum sensing. It is shown that any GLRT detector exclusively depends on the projection of the sample covariance matrix of the data onto a given underlying kernel that reflects the available sideinformation in the problem. The kernels in several scenarios of interest are derived, including the widespread single and multifrequency channelisation cases. Theoretical interpretations and numerical results show the tradeoff between detection performance and the degree of sideinformation on the most informative statistics for detection, that is, the modulation format and spectrum distribution of the primary users.
20141217T15:46:43Z
Font Segura, Josep
Vázquez Grau, Gregorio
Riba Sagarra, Jaume
This study addresses the optimal spectrum sensing detection based on the complete or partial sideinformation on the signal and noise statistics. The use of the generalisedlikelihood ratio test (GLRT) involves maximumlikelihood (ML) estimation of the nuisances. ML estimation of the unknowns is especially challenging for wideband cognitive radio because closedform solutions are often not available. Based on the equivalence between the wideband regime and the lowsignaltonoise ratio regime, this study provides a general kernel framework for GLRT spectrum sensing. It is shown that any GLRT detector exclusively depends on the projection of the sample covariance matrix of the data onto a given underlying kernel that reflects the available sideinformation in the problem. The kernels in several scenarios of interest are derived, including the widespread single and multifrequency channelisation cases. Theoretical interpretations and numerical results show the tradeoff between detection performance and the degree of sideinformation on the most informative statistics for detection, that is, the modulation format and spectrum distribution of the primary users.

Asymptotically optimal linear shrinkage of sample LMMSE and MVDR filters
http://hdl.handle.net/2117/24612
Asymptotically optimal linear shrinkage of sample LMMSE and MVDR filters
Serra, Jordi; Nájar Martón, Montserrat
Conventional implementations of the linearminimum meansquare (LMMSE) and minimum variance distortionless response (MVDR) estimators rely on the sample matrix inversion (SMI) technique, i.e., on the sample covariance matrix (SCM). This approach is optimal in the large sample size regime. Nonetheless, in small sample size situations, those sample estimators suffer a large performance degradation. Thus, the aim of this paper is to propose corrections of these sample methods that counteract their performance degradation in the small sample size regime and keep their optimality in large sample size situations. To this aim, a twofold approach is proposed. First, shrinkage estimators are considered, as they are known to be robust to the small sample size regime. Namely, the proposed methods are based on shrinking the sample LMMSE or sample MVDR filters towards a variously called matched filter or conventional (Bartlett) beamformer in array processing. Second, random matrix theory is used to obtain the optimal shrinkage factors for large filters. The simulation results highlight that the proposed methods outperform the sample LMMSE and MVDR. Also, provided that the sample size is higher than the observation dimension, they improve classical diagonal loading (DL) and LedoitWolf (LW) techniques, which counteract the small sample size degradation by regularizing the SCM. Finally, compared to stateoftheart DL, the proposed methods reduce the computational cost and the proposed shrinkage of the LMMSE obtains performance gains.
20141107T15:44:05Z
Serra, Jordi
Nájar Martón, Montserrat
Conventional implementations of the linearminimum meansquare (LMMSE) and minimum variance distortionless response (MVDR) estimators rely on the sample matrix inversion (SMI) technique, i.e., on the sample covariance matrix (SCM). This approach is optimal in the large sample size regime. Nonetheless, in small sample size situations, those sample estimators suffer a large performance degradation. Thus, the aim of this paper is to propose corrections of these sample methods that counteract their performance degradation in the small sample size regime and keep their optimality in large sample size situations. To this aim, a twofold approach is proposed. First, shrinkage estimators are considered, as they are known to be robust to the small sample size regime. Namely, the proposed methods are based on shrinking the sample LMMSE or sample MVDR filters towards a variously called matched filter or conventional (Bartlett) beamformer in array processing. Second, random matrix theory is used to obtain the optimal shrinkage factors for large filters. The simulation results highlight that the proposed methods outperform the sample LMMSE and MVDR. Also, provided that the sample size is higher than the observation dimension, they improve classical diagonal loading (DL) and LedoitWolf (LW) techniques, which counteract the small sample size degradation by regularizing the SCM. Finally, compared to stateoftheart DL, the proposed methods reduce the computational cost and the proposed shrinkage of the LMMSE obtains performance gains.