Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/1257
Thu, 11 Feb 2016 23:54:41 GMT2016-02-11T23:54:41ZList message passing algorithm for noiseless compressed sensing
http://hdl.handle.net/2117/82868
List message passing algorithm for noiseless compressed sensing
Ramírez Javega, Francisco; Lamarca Orozco, M. Meritxell
We propose a verification-based algorithm for noiseless Compressed Sensing that reconstructs the original signal operating on a sparse graph. The proposed scheme has affordable computational complexity and its performance is significantly better than previous verification-based algorithms and similar to AMP-based algorithms. We also show that the performance of a noiseless compressed sensing scheme when verification-based algorithms and a sparse matrix is employed to reconstruct the original signal can be upper bounded by the performance of a LDPC code employing the same parity matrix when correcting a codeword transmitted through a BEC.
Thu, 11 Feb 2016 15:48:12 GMThttp://hdl.handle.net/2117/828682016-02-11T15:48:12ZRamírez Javega, FranciscoLamarca Orozco, M. MeritxellWe propose a verification-based algorithm for noiseless Compressed Sensing that reconstructs the original signal operating on a sparse graph. The proposed scheme has affordable computational complexity and its performance is significantly better than previous verification-based algorithms and similar to AMP-based algorithms. We also show that the performance of a noiseless compressed sensing scheme when verification-based algorithms and a sparse matrix is employed to reconstruct the original signal can be upper bounded by the performance of a LDPC code employing the same parity matrix when correcting a codeword transmitted through a BEC.Simultaneous tracking and RSS model calibration by robust filtering
http://hdl.handle.net/2117/81159
Simultaneous tracking and RSS model calibration by robust filtering
Castro Arvizu, Juan Manuel; Vila Valls, Jordi; Closas, Pau; Fernández Rubio, Juan Antonio
Received Signal Strength (RSS) localization is widely
used due to its simplicity and availability in most mobile devices.
The RSS channel model is defined by the propagation losses
and the shadow fading. These parameters might vary over time
because of changes in the environment. In this paper, the problem
of tracking a mobile node by RSS measurements is addressed,
while simultaneously estimating a two-slope RSS model. The
methodology considers a Kalman filter with Interacting Multiple
Model architecture, coupled to an on-line estimation of the
observation’s variance. The performance of the method is shown
through numerical simulations in realistic scenarios.
Fri, 08 Jan 2016 14:09:57 GMThttp://hdl.handle.net/2117/811592016-01-08T14:09:57ZCastro Arvizu, Juan ManuelVila Valls, JordiClosas, PauFernández Rubio, Juan AntonioReceived Signal Strength (RSS) localization is widely
used due to its simplicity and availability in most mobile devices.
The RSS channel model is defined by the propagation losses
and the shadow fading. These parameters might vary over time
because of changes in the environment. In this paper, the problem
of tracking a mobile node by RSS measurements is addressed,
while simultaneously estimating a two-slope RSS model. The
methodology considers a Kalman filter with Interacting Multiple
Model architecture, coupled to an on-line estimation of the
observation’s variance. The performance of the method is shown
through numerical simulations in realistic scenarios.Harvesting management in multiuser MIMO systems with simultaneous wireless information and power transfer
http://hdl.handle.net/2117/81053
Harvesting management in multiuser MIMO systems with simultaneous wireless information and power transfer
Rubio López, Javier; Pascual Iserte, Antonio
In this paper, we focus on a broadcast multiuser multiple-input multiple-output (MIMO) system where we consider that some terminals harvest power and, thus, recharge their batteries through wireless power transfer from the transmitter, while others are simultaneously being served with data transmission. The weighted sum-rate of the terminals that are receiving information data is considered as the optimization policy where minimum energy harvesting constraints are taken into account. We propose a procedure for managing the minimum energy to be harvested by the terminals considering the effect in the target system performance.
Wed, 23 Dec 2015 14:46:58 GMThttp://hdl.handle.net/2117/810532015-12-23T14:46:58ZRubio López, JavierPascual Iserte, AntonioIn this paper, we focus on a broadcast multiuser multiple-input multiple-output (MIMO) system where we consider that some terminals harvest power and, thus, recharge their batteries through wireless power transfer from the transmitter, while others are simultaneously being served with data transmission. The weighted sum-rate of the terminals that are receiving information data is considered as the optimization policy where minimum energy harvesting constraints are taken into account. We propose a procedure for managing the minimum energy to be harvested by the terminals considering the effect in the target system performance.Decentralized beamforming with coordinated sounding for inter-cell interference management
http://hdl.handle.net/2117/78778
Decentralized beamforming with coordinated sounding for inter-cell interference management
Lagén Morancho, Sandra; Agustín de Dios, Adrián; Vidal Manzano, José
This paper presents and evaluates a decentralized beamforming design for inter-cell interference management that is highly recommended in Time Division Duplex (TDD) cellular network deployments and interference limited scenarios. The inter-cell interference mitigation in the downlink (DL) is done in a decentralized manner by sensing the Sounding Reference Signals (SRS) sent by user equipments (UEs) associated to neighboring evolved Node Bs (eNBs). The proposed technique exploits the reciprocity of the propagation radio channels, an adequate link adaptation in the uplink and a wise coordination of the SRS transmissions. In this regard, multiple methods are proposed to implement the proposed Beamforming with Coordinated Sounding (BF-CoS) in a 3GPP LTE-Advanced based network. Simulation results show significant performance gains in terms of user packet throughput with respect to no coordination schemes, without increasing the overhead and complexity because of coordination. The largest relative gains are obtained for mediumto-high traffic loads and for denser deployments.
Wed, 04 Nov 2015 13:39:21 GMThttp://hdl.handle.net/2117/787782015-11-04T13:39:21ZLagén Morancho, SandraAgustín de Dios, AdriánVidal Manzano, JoséThis paper presents and evaluates a decentralized beamforming design for inter-cell interference management that is highly recommended in Time Division Duplex (TDD) cellular network deployments and interference limited scenarios. The inter-cell interference mitigation in the downlink (DL) is done in a decentralized manner by sensing the Sounding Reference Signals (SRS) sent by user equipments (UEs) associated to neighboring evolved Node Bs (eNBs). The proposed technique exploits the reciprocity of the propagation radio channels, an adequate link adaptation in the uplink and a wise coordination of the SRS transmissions. In this regard, multiple methods are proposed to implement the proposed Beamforming with Coordinated Sounding (BF-CoS) in a 3GPP LTE-Advanced based network. Simulation results show significant performance gains in terms of user packet throughput with respect to no coordination schemes, without increasing the overhead and complexity because of coordination. The largest relative gains are obtained for mediumto-high traffic loads and for denser deployments.Compressed spectrum sensing in the presence of interference: comparison of sparse recovery strategies
http://hdl.handle.net/2117/27585
Compressed spectrum sensing in the presence of interference: comparison of sparse recovery strategies
Lagunas Targarona, Eva; Nájar Martón, Montserrat
Existing approaches to Compressive Sensing (CS) of sparse spectrum has thus far assumed models contaminated with noise (either bounded noise or Gaussian with known power). In practical Cognitive Radio (CR) networks, primary users must be detected even in the presence of low-regulated transmissions from unlicensed systems, which cannot be taken into account in the CS model because of their non-regulated nature. In [1], the authors proposed an overcomplete dictionary that contains tuned spectral shapes of the primary user to sparsely represent the primary users' spectral support, thus allowing all frequency location hypothesis to be jointly evaluated in a global unified optimization framework. Extraction of the primary user frequency locations is then performed based on sparse signal recovery algorithms. Here, we compare different sparse reconstruction strategies and we show through simulation results the link between the interference rejection capabilities and the positive semidefinite character of the residual autocorrelation matrix.
Fri, 24 Apr 2015 13:34:35 GMThttp://hdl.handle.net/2117/275852015-04-24T13:34:35ZLagunas Targarona, EvaNájar Martón, MontserratExisting approaches to Compressive Sensing (CS) of sparse spectrum has thus far assumed models contaminated with noise (either bounded noise or Gaussian with known power). In practical Cognitive Radio (CR) networks, primary users must be detected even in the presence of low-regulated transmissions from unlicensed systems, which cannot be taken into account in the CS model because of their non-regulated nature. In [1], the authors proposed an overcomplete dictionary that contains tuned spectral shapes of the primary user to sparsely represent the primary users' spectral support, thus allowing all frequency location hypothesis to be jointly evaluated in a global unified optimization framework. Extraction of the primary user frequency locations is then performed based on sparse signal recovery algorithms. Here, we compare different sparse reconstruction strategies and we show through simulation results the link between the interference rejection capabilities and the positive semidefinite character of the residual autocorrelation matrix.Decentralized widely linear precoding design for the MIMO interference channel
http://hdl.handle.net/2117/27068
Decentralized widely linear precoding design for the MIMO interference channel
Lagén Morancho, Sandra; Agustín de Dios, Adrián; Vidal Manzano, José
his paper addresses the interference management in a MIMO interference channel (MIMO-IC) by proposing a decentralized transmit and receive beamformer optimization using improper (or circularly asymmetric complex) Gaussian signaling. For the ease of exposition, the downlink (DL) of a cellular network is considered. In order to generate improper Gaussian signals, widely linear precoding (WLP) is adopted at transmission, while at reception we consider that users might apply either widely linear estimation (WLE) or linear estimation. The coordination between transmitters for WLP design is attained by taking into account the received signal in the uplink (UL), provided that propagation channel reciprocity can be assumed and that transmit filters in the UL are appropriately designed. In this way the estimation of the interfering channels is avoided, while we can take advantage of both DL transmit coordination to adjust transmit power and beamformers and the use of improper Gaussian signaling to exploit the real and imaginary dimensions of the MIMO channel. Simulations show that the proposed decentralized technique allows reducing the mean square error (MSE) and increasing user throughput in highly interfered scenarios
Thu, 26 Mar 2015 15:11:00 GMThttp://hdl.handle.net/2117/270682015-03-26T15:11:00ZLagén Morancho, SandraAgustín de Dios, AdriánVidal Manzano, Joséhis paper addresses the interference management in a MIMO interference channel (MIMO-IC) by proposing a decentralized transmit and receive beamformer optimization using improper (or circularly asymmetric complex) Gaussian signaling. For the ease of exposition, the downlink (DL) of a cellular network is considered. In order to generate improper Gaussian signals, widely linear precoding (WLP) is adopted at transmission, while at reception we consider that users might apply either widely linear estimation (WLE) or linear estimation. The coordination between transmitters for WLP design is attained by taking into account the received signal in the uplink (UL), provided that propagation channel reciprocity can be assumed and that transmit filters in the UL are appropriately designed. In this way the estimation of the interfering channels is avoided, while we can take advantage of both DL transmit coordination to adjust transmit power and beamformers and the use of improper Gaussian signaling to exploit the real and imaginary dimensions of the MIMO channel. Simulations show that the proposed decentralized technique allows reducing the mean square error (MSE) and increasing user throughput in highly interfered scenariosChannel training procedures for MIMO interfering point-to-multipoint channel
http://hdl.handle.net/2117/27067
Channel training procedures for MIMO interfering point-to-multipoint channel
Agustín de Dios, Adrián; Lagén Morancho, Sandra; Vidal Manzano, José
A precise knowledge of the MIMO channel
between the serving node and the user equipment (UE) is
important for attaining good data rates in downlink
transmissions (DL) in cellular systems. The interfering point-tomultipoint
(I-P2MP) channel, consisting of multiple transmitters
coexisting in the same area, where each transmitter is intended to
serve multiple users, is a model that subsumes most of the
scenarios that can be found in wireless cellular networks with a
dense deployment of small cells (SCs). In conventional channel
estimation procedures, resources allocated to each SC for
training tend to be orthogonal, negatively impacting in the
efficiency of the whole system. Reusing resources for training
allows releasing resources for data transmission, but at the cost
of degrading the channel estimation due to interference. We
propose a decentralized algorithm for interference management
that enforces the coordination among SCs in the design of the
training sequences for de DL. Results in this work elucidate how
to reuse resources for training and significantly improve the
throughput of the system.
Thu, 26 Mar 2015 15:04:46 GMThttp://hdl.handle.net/2117/270672015-03-26T15:04:46ZAgustín de Dios, AdriánLagén Morancho, SandraVidal Manzano, JoséA precise knowledge of the MIMO channel
between the serving node and the user equipment (UE) is
important for attaining good data rates in downlink
transmissions (DL) in cellular systems. The interfering point-tomultipoint
(I-P2MP) channel, consisting of multiple transmitters
coexisting in the same area, where each transmitter is intended to
serve multiple users, is a model that subsumes most of the
scenarios that can be found in wireless cellular networks with a
dense deployment of small cells (SCs). In conventional channel
estimation procedures, resources allocated to each SC for
training tend to be orthogonal, negatively impacting in the
efficiency of the whole system. Reusing resources for training
allows releasing resources for data transmission, but at the cost
of degrading the channel estimation due to interference. We
propose a decentralized algorithm for interference management
that enforces the coordination among SCs in the design of the
training sequences for de DL. Results in this work elucidate how
to reuse resources for training and significantly improve the
throughput of the system.Joint scheduling of communication and computation resources in multiuser wireless application offloading
http://hdl.handle.net/2117/27061
Joint scheduling of communication and computation resources in multiuser wireless application offloading
Molina Pena, Marc; Muñoz Medina, Olga; Pascual Iserte, Antonio; Vidal Manzano, José
We consider a system where multiple users are
connected to a small cell base station enhanced with
computational capabilities. Instead of doing the computation
locally at the handset, the users offload the computation of full
applications or pieces of code to the small cell base station. In this
scenario, this paper provides a strategy to allocate the uplink,
downlink, and remote computational resources. The goal is to
improve the quality of experience of the users, while achieving
energy savings with respect to the case in which the applications
run locally at the mobile terminals. More specifically, we focus on
minimizing a cost function that depends on the latencies
experienced by the users and provide an algorithm to minimize
the latency experienced by the worst case user, under a target
energy saving constraint per user.
Thu, 26 Mar 2015 13:20:32 GMThttp://hdl.handle.net/2117/270612015-03-26T13:20:32ZMolina Pena, MarcMuñoz Medina, OlgaPascual Iserte, AntonioVidal Manzano, JoséWe consider a system where multiple users are
connected to a small cell base station enhanced with
computational capabilities. Instead of doing the computation
locally at the handset, the users offload the computation of full
applications or pieces of code to the small cell base station. In this
scenario, this paper provides a strategy to allocate the uplink,
downlink, and remote computational resources. The goal is to
improve the quality of experience of the users, while achieving
energy savings with respect to the case in which the applications
run locally at the mobile terminals. More specifically, we focus on
minimizing a cost function that depends on the latencies
experienced by the users and provide an algorithm to minimize
the latency experienced by the worst case user, under a target
energy saving constraint per user.Subset relay selection in wireless cooperative networks using sparsity-inducing norms
http://hdl.handle.net/2117/26951
Subset relay selection in wireless cooperative networks using sparsity-inducing norms
Blanco, Luis; Nájar Martón, Montserrat
This paper addresses the problem of multiple relay selection in a two-hop wireless cooperative network. In particular, the proposed technique selects the best subset of relays, in a distributed beamforming scheme, which maximizes the signal-to-noise ratio at the destination node subject to individual power constraints at the relays. The selection of the best subset of K relays out of a set of N potential relay nodes, under individual power constraints, is a hard combinatorial problem with a high computational burden. The approach considered herein consists in relaxing this problem into a convex one by considering a sparsity-inducing norm. The method exposed in this paper is based on the knowledge of the second-order statistics of the channels and achieves a near-optimal performance with a computational burden which is far less than the one needed in the combinatorial search. Furthermore, in the proposed technique, contrary to other approaches in the literature, the relays are not limited to cooperate with full power.
Mon, 23 Mar 2015 14:53:30 GMThttp://hdl.handle.net/2117/269512015-03-23T14:53:30ZBlanco, LuisNájar Martón, MontserratThis paper addresses the problem of multiple relay selection in a two-hop wireless cooperative network. In particular, the proposed technique selects the best subset of relays, in a distributed beamforming scheme, which maximizes the signal-to-noise ratio at the destination node subject to individual power constraints at the relays. The selection of the best subset of K relays out of a set of N potential relay nodes, under individual power constraints, is a hard combinatorial problem with a high computational burden. The approach considered herein consists in relaxing this problem into a convex one by considering a sparsity-inducing norm. The method exposed in this paper is based on the knowledge of the second-order statistics of the channels and achieves a near-optimal performance with a computational burden which is far less than the one needed in the combinatorial search. Furthermore, in the proposed technique, contrary to other approaches in the literature, the relays are not limited to cooperate with full power.Spatial sparsity based direct positioning for IR-UWB in IEEE 802.15.4a channels
http://hdl.handle.net/2117/26902
Spatial sparsity based direct positioning for IR-UWB in IEEE 802.15.4a channels
Lagunas Targarona, Eva; Navarro, Mònica; Closas Gómez, Pau; Nájar Martón, Montserrat
In this paper, we focus on the application of Compressive Sensing (CS) techniques to Impulse Radio (IR) Ultra-WideBand (UWB) positioning systems under indoor propagation environments. Direct Position Estimation (DPE) approaches can potentially improve the position estimation accuracy of conventional two-step techniques by directly estimating the position coordinates from the observed signal in a single step. Furthermore, DPE does not require a threshold selection upon which accuracy of two-step approaches depend on. Although in the presence of multipath the actual gains are not straight forward, recent evaluation of DPE positioning in IR-UWB system proved accurate positioning estimate gains. However it comes at a cost of higher computational complexity. This paper exploits the sparseness of the problem to reduce the computational load of the positioning estimation process and relax the requirements of the Analog to Digital Converter (ADC) when sampling UWB signals. Based on the fact that the number of unknown targets is small in the discrete spatial domain, this paper incorporates the multiple location hypotheses into an overcomplete basis, which highlights the sparseness of the spatial domain. This fact motivates the use of CS-based sampling and sparsity-based reconstruction techniques to jointly evaluate all possible hypotheses, thus avoiding the traditional position-by-position scanning where the multiple location hypotheses are evaluated independently. In so doing, we not only achieve a significant reduction in computational time but also we relax the sampling requirements.
Fri, 20 Mar 2015 13:59:36 GMThttp://hdl.handle.net/2117/269022015-03-20T13:59:36ZLagunas Targarona, EvaNavarro, MònicaClosas Gómez, PauNájar Martón, MontserratIn this paper, we focus on the application of Compressive Sensing (CS) techniques to Impulse Radio (IR) Ultra-WideBand (UWB) positioning systems under indoor propagation environments. Direct Position Estimation (DPE) approaches can potentially improve the position estimation accuracy of conventional two-step techniques by directly estimating the position coordinates from the observed signal in a single step. Furthermore, DPE does not require a threshold selection upon which accuracy of two-step approaches depend on. Although in the presence of multipath the actual gains are not straight forward, recent evaluation of DPE positioning in IR-UWB system proved accurate positioning estimate gains. However it comes at a cost of higher computational complexity. This paper exploits the sparseness of the problem to reduce the computational load of the positioning estimation process and relax the requirements of the Analog to Digital Converter (ADC) when sampling UWB signals. Based on the fact that the number of unknown targets is small in the discrete spatial domain, this paper incorporates the multiple location hypotheses into an overcomplete basis, which highlights the sparseness of the spatial domain. This fact motivates the use of CS-based sampling and sparsity-based reconstruction techniques to jointly evaluate all possible hypotheses, thus avoiding the traditional position-by-position scanning where the multiple location hypotheses are evaluated independently. In so doing, we not only achieve a significant reduction in computational time but also we relax the sampling requirements.