Luis Miguel Ruiz Alonso - Academia.edu (original) (raw)
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Papers by Luis Miguel Ruiz Alonso
2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
In this paper we analyze the performance of a distributed queuing medium access control (MAC) pro... more In this paper we analyze the performance of a distributed queuing medium access control (MAC) protocol designed to execute cooperative ARQ (C-ARQ) schemes at the MAC layer. Due to the broadcast nature of the wireless channel, a user that receives a data packet with unrecoverable errors can request retransmission from any of the other users in the transmission range of the transmitter that overheard the original transmission. These users can act as spontaneous relays and provide the communication with cooperative diversity gains. Upon retransmission request, the relays have to contend for the access to the channel. The DQCOOP protocol has been proposed in the literature as a high-performance MAC protocol for this kind of scenario. In this paper we theoretically evaluate its performance. The analytical results are supported by computerbased simulation that show the accuracy of the analysis.
Ad Hoc Networks, 2012
The Distributed Point Coordination Function (DPCF) is presented in this paper as a novel Medium A... more The Distributed Point Coordination Function (DPCF) is presented in this paper as a novel Medium Access Control Protocol (MAC) for wireless ad hoc networks. DPCF extends the operation of the Point Coordination Function (PCF) defined in the IEEE 802.11 Standard to operate over wireless networks without infrastructure. In PCF, a central point coordinator polls the users to get access to the channel and data collisions are completely avoided, thus yielding high performance. In order to extend its high performance to networks without infrastructure, the DPCF is proposed in this paper as a combination of the Distributed Coordination Function (DCF) and the PCF. The general idea is to combine a dynamic, temporary, and spontaneous clustering mechanism based on DCF with the execution of PCF within each cluster. The backwards compatibility of DPCF with legacy 802.11 networks is also assessed in this paper. Comprehensive computer-based simulations demonstrate the high performance of this new protocol in both single-hop and multi-hop networks.
ABSTRACT Precise and spatially-explicit knowledge of leaf chlorophyll content (Chl) is crucial to... more ABSTRACT Precise and spatially-explicit knowledge of leaf chlorophyll content (Chl) is crucial to adequately interpret the chlorophyll fluorescence (ChF) signal from space. Accompanying information about the reliability of the Chl estimation becomes more important than ever. Recently, a new statistical method was proposed within the family of nonparametric Bayesian statistics, namely Gaussian Processes regression (GPR). GPR is simpler and more robust than their machine learning family members while maintaining very good numerical performance and stability. Other features include: i) GPR requires a relatively small training data set and can adopt very flexible kernels, ii) GPR identifies the relevant bands and observations in establishing relationships with a variable, and finally iii) along with pixelwise estimations GPR provides accompanying confidence intervals. We used GPR to retrieve Chl from hyperspectral reflectance data and evaluated the portability of the regression model to other images. Based on field Chl measurements from the SPARC dataset and corresponding spaceborne CHRIS spectra (acquired in 2003, Barrax, Spain), GPR developed a regression model that was excellently validated ( r 2: 0.96, RMSE: 3.82 μg/cm 2 ). The SPARC-trained GPR model was subsequently applied to CHRIS images (Barrax, 2003, 2009) and airborne CASI flightlines (Barrax 2009) to generate Chl maps. The accompanying confidence maps provided insight in the robustness of the retrievals. Similar confidences were achieved by both sensors, which is encouraging for upscaling Chl estimates from field to landscape scale. Because of its robustness and ability to deliver confidence intervals, GPR is evaluated as a promising candidate for implementation into ChF processing chains.
2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
In this paper we analyze the performance of a distributed queuing medium access control (MAC) pro... more In this paper we analyze the performance of a distributed queuing medium access control (MAC) protocol designed to execute cooperative ARQ (C-ARQ) schemes at the MAC layer. Due to the broadcast nature of the wireless channel, a user that receives a data packet with unrecoverable errors can request retransmission from any of the other users in the transmission range of the transmitter that overheard the original transmission. These users can act as spontaneous relays and provide the communication with cooperative diversity gains. Upon retransmission request, the relays have to contend for the access to the channel. The DQCOOP protocol has been proposed in the literature as a high-performance MAC protocol for this kind of scenario. In this paper we theoretically evaluate its performance. The analytical results are supported by computerbased simulation that show the accuracy of the analysis.
Ad Hoc Networks, 2012
The Distributed Point Coordination Function (DPCF) is presented in this paper as a novel Medium A... more The Distributed Point Coordination Function (DPCF) is presented in this paper as a novel Medium Access Control Protocol (MAC) for wireless ad hoc networks. DPCF extends the operation of the Point Coordination Function (PCF) defined in the IEEE 802.11 Standard to operate over wireless networks without infrastructure. In PCF, a central point coordinator polls the users to get access to the channel and data collisions are completely avoided, thus yielding high performance. In order to extend its high performance to networks without infrastructure, the DPCF is proposed in this paper as a combination of the Distributed Coordination Function (DCF) and the PCF. The general idea is to combine a dynamic, temporary, and spontaneous clustering mechanism based on DCF with the execution of PCF within each cluster. The backwards compatibility of DPCF with legacy 802.11 networks is also assessed in this paper. Comprehensive computer-based simulations demonstrate the high performance of this new protocol in both single-hop and multi-hop networks.
ABSTRACT Precise and spatially-explicit knowledge of leaf chlorophyll content (Chl) is crucial to... more ABSTRACT Precise and spatially-explicit knowledge of leaf chlorophyll content (Chl) is crucial to adequately interpret the chlorophyll fluorescence (ChF) signal from space. Accompanying information about the reliability of the Chl estimation becomes more important than ever. Recently, a new statistical method was proposed within the family of nonparametric Bayesian statistics, namely Gaussian Processes regression (GPR). GPR is simpler and more robust than their machine learning family members while maintaining very good numerical performance and stability. Other features include: i) GPR requires a relatively small training data set and can adopt very flexible kernels, ii) GPR identifies the relevant bands and observations in establishing relationships with a variable, and finally iii) along with pixelwise estimations GPR provides accompanying confidence intervals. We used GPR to retrieve Chl from hyperspectral reflectance data and evaluated the portability of the regression model to other images. Based on field Chl measurements from the SPARC dataset and corresponding spaceborne CHRIS spectra (acquired in 2003, Barrax, Spain), GPR developed a regression model that was excellently validated ( r 2: 0.96, RMSE: 3.82 μg/cm 2 ). The SPARC-trained GPR model was subsequently applied to CHRIS images (Barrax, 2003, 2009) and airborne CASI flightlines (Barrax 2009) to generate Chl maps. The accompanying confidence maps provided insight in the robustness of the retrievals. Similar confidences were achieved by both sensors, which is encouraging for upscaling Chl estimates from field to landscape scale. Because of its robustness and ability to deliver confidence intervals, GPR is evaluated as a promising candidate for implementation into ChF processing chains.