This paper presents a simulation study of polar coverage signaling which can be applied to different current wireless communication systems. In particular, we use the Polar Radio Coverage feature of Radio Mobile software version 11.6.6 in... more
This paper presents a simulation study of polar coverage signaling which can be applied to different current wireless communication systems. In particular, we use the Polar Radio Coverage feature of Radio Mobile software version 11.6.6 in order to perform an empirical study in real geographical areas including Las Condes and Valparaiso which are two locations in Chile. In this predictive study, all parameters are configured for both the radio base stations (RBS) and mobile stations (MS) located in certain points of the proposed coverage area. This allows obtaining the signal strength and visualizing the range in the covered maps. Subsequently, the data is exported to Google Earth Pro in order to identify the areas without coverage where it is not possible to establish of a point-to-point link communication. Consequently, the establishment of coverage in a given area will guarantee certain signal levels in the receiving equipment while considering different values for the coverage radius and azimuth. Finally, the proposed approach can be applied in all wireless communications systems allowing additionally Path Loss and E-field strength analysis.
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In this work we present a comparison between two classical metaheuristic optimization algorithms to solve two different received signal strength (RSS) based fitness function formulations for 3-D visible light positioning systems. For this... more
In this work we present a comparison between two classical metaheuristic optimization algorithms to solve two different received signal strength (RSS) based fitness function formulations for 3-D visible light positioning systems. For this purpose, simulations have been carried out to analyze the performance of genetic algorithm (GA) and particle swarm optimization (PSO) methods for mobile node’s position determination. Based on simulation results, GA overcomes PSO. GA shows to be more robust than PSO and it is capable to provide feasible optimal solutions when no map information is added as constraints to the optimization problem. When map information is used as lower and upper bound constraints, GA and PSO methods increase their accuracy and precision significantly.
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In this paper, we propose a mixed integer linear programming (MILP) model for a telecommunication highway vehicle network to optimally locate roadside units (RSUs) at minimum costs. Our model is quite general and thus can be used in... more
In this paper, we propose a mixed integer linear programming (MILP) model for a telecommunication highway vehicle network to optimally locate roadside units (RSUs) at minimum costs. Our model is quite general and thus can be used in highway networks where emerging technologies related with Massive Multiple Input Multiple Output (MIMO) systems can be implemented. For this purpose, let graph G(V,E) represent a highway vehicle network with sets V and E denoting RSUs and connection links between them, respectively. The optimization problem consists of finding a subset of RSUs from V that satisfies a coverage vehicle flow and Hamiltonian backbone network constraints while spanning the highway at minimum cost. Then, we further propose an iterative greedy heuristic and a local search algorithm which allow feasible solutions to be obtained in significantly less CPU time than CPLEX solver requires to solve the MILP model. Preliminary numerical results indicate that our proposed model is able to solve network instances with up to 1500 RSUs to optimality in less than one hour. Whilst the proposed heuristic and local search algorithms allow to obtain near optimal solutions with gap values which are lower than 6% and 1%, respectively for most tested instances.
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This paper proposes two methods of separation of VLC signals, based on the stadistical variation 1) FastIca and 2) InfoMax, the first one based in the stadistical covariance of the negentrophy and the second one based in the artificial... more
This paper proposes two methods of separation of VLC signals, based on the stadistical variation 1) FastIca and 2) InfoMax, the first one based in the stadistical covariance of the negentrophy and the second one based in the artificial neural network for the analysis of covariance of the values from signals. This values are results of a simulation and experimental transference of information through Visible Light Communication, the simulation without noise, and the experimental process with noise.
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Visible light communication (VLC) technology has recently emerged as a new complementarity approach to radio frequency (RF) methods as it allows transmission data rates of significantly high orders of magnitude [3], [6]. Since power... more
Visible light communication (VLC) technology has recently emerged as a new complementarity approach to radio frequency (RF) methods as it allows transmission data rates of significantly high orders of magnitude [3], [6]. Since power transmission in a VLC network is directly affected by the quality of the channel between the emitter and receiver, it is highly necessary to find minimum slot schedules with minimum power cost while ensuring the whole connectivity of the network. Spatial Time Division Multiple Access (STDMA) protocol achieves full connectivity in wireless networks by allowing simultaneous data rate transmission of multiple nodes within each time slot [10]. In this paper, we propose a weighted mixed integer linear programming (MIP) model to minimize the total number of slots and power consumption in a VLC network. First, we solve the optimization problem assuming that the number of slots can be as large as the number of edges in the network. Then, as second strategy we fu...
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The aim of this paper is to offer an alternative signal analysis using Multiresolution Analysis (MRA), with the practical purpose of analyzing its performance in reducing the noise components. In a first part, a brief theoretical basis is... more
The aim of this paper is to offer an alternative signal analysis using Multiresolution Analysis (MRA), with the practical purpose of analyzing its performance in reducing the noise components. In a first part, a brief theoretical basis is shown for the Wavelets theory for signal analysis. Subsequently, simulations are carried out to reduce the noise through the multiresolution analysis of the Discrete Wavelet Transform and the they are compared with the results obtained through typical filters, such as Savitzky-Golay and Moving Average Filter.
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Following the recent advances in wireless communication leading to increased Internet of Things (IoT) systems, many security threats are currently ravaging IoT systems, causing harm to information. Considering the vast application areas... more
Following the recent advances in wireless communication leading to increased Internet of Things (IoT) systems, many security threats are currently ravaging IoT systems, causing harm to information. Considering the vast application areas of IoT systems, ensuring that cyberattacks are holistically detected to avoid harm is paramount. Machine learning (ML) algorithms have demonstrated high capacity in helping to mitigate attacks on IoT devices and other edge systems with reasonable accuracy. However, the dynamics of operation of intruders in IoT networks require more improved IDS models capable of detecting multiple attacks with a higher detection rate and lower computational resource requirement, which is one of the challenges of IoT systems. Many ensemble methods have been used with different ML classifiers, including decision trees and random forests, to propose IDS models for IoT environments. The boosting method is one of the approaches used to design an ensemble classifier. This ...
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In this paper, we propose two mixed integer linear programming (MILP) models for wireless networks (WNs) under star backbone topology configuration. For this purpose, let the graph $G(V,E)$ represent a WN with set of nodes V and edge set... more
In this paper, we propose two mixed integer linear programming (MILP) models for wireless networks (WNs) under star backbone topology configuration. For this purpose, let the graph $G(V,E)$ represent a WN with set of nodes V and edge set E. Set V represents all nodes (wireless devices) which can be part or not of the star backbone whereas set E represents the connection links between all pairs of nodes. Additionally, we consider a set K of users. Only, a subset of nodes from V should be active to form the star backbone and each user should be connected to a unique terminal (leaf) node. This problem represents a more general variant of a previous work reported in the literature where only a fixed number of nodes from V is required to be active. Our first model corresponds to a novel Miller-Tucker-Zemlin constrained version whilst the second one is a novel flow based formulation. Then, we further propose an iterative greedy algorithm that allows to obtain feasible solutions for the problem. Our preliminary numerical results indicate that the flow model allows one to obtain optimal solutions in less CPU time for Euclidean complete and disk graph instances. Whilst the greedy algorithm allows to obtain near optimal and optimal solutions in significantly less computational cost compared to the MILP models and with gap values which are lower than 2% for most tested instances.
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This work provides the design of fuzzy - PID controller for energy management over a hybrid propulsion system in unmanned aerial vehicle. The simulation model of propulsion system and propeller dynamics have been developed by... more
This work provides the design of fuzzy - PID controller for energy management over a hybrid propulsion system in unmanned aerial vehicle. The simulation model of propulsion system and propeller dynamics have been developed by MATLAB-Simulink environment and his Simscape library. The main controller is composing for three controllers: Electric motor controller, an engine controller and energy manager. The last deliver set point to individual controllers. All PID controllers have been tuned by root locus methodology. Performance results was made into a specific flight scenario. All controllers have performed good results, showing a correct use of energy sources into the unmanned aerial vehicle unmanned.
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In this paper, we consider the problem of maximizing the worst user signal to interference noise ratio (SINR) for Massive Multiple Input Multiple Output (MaMIMO) systems subject to antenna assignment and multiuser interference... more
In this paper, we consider the problem of maximizing the worst user signal to interference noise ratio (SINR) for Massive Multiple Input Multiple Output (MaMIMO) systems subject to antenna assignment and multiuser interference constraints. In particular, we aim to choose a subset of antennas from a larger set while imposing a maximum interference value allowed in the system. Notice that MaMIMO technology has recently been considered as a strong candidate for 5G wireless communications by the research community as it provides better performance in terms of data rate. It also allows to transmit in higher frequency bands with strong signal performance and reliability. In order to propose new optimization models for this problem, we model SINR by using Manhattan, Euclidean and Infinity distance norms. Thus, we obtain integer quadratic and linear programming models that allow to obtain optimal solutions for the problem. As such, the proposed models can be used as a source of comparison for any exact or approximation method to be developed as part of future research. Finally, we propose a local search algorithm that allows to obtain feasible solutions in short CPU time. Our preliminary numerical results indicate that the linear models are preferable and that the local search approach obtains better solutions than the quadratic model for some of the tested instances in significantly less CPU time.
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Energy efficiency is a permanent concern in all types of production processes. The automation of machine tools using Computer Numerical Control (CNC) and the increasing introduction of manipulator robots mean a significant improvement in... more
Energy efficiency is a permanent concern in all types of production processes. The automation of machine tools using Computer Numerical Control (CNC) and the increasing introduction of manipulator robots mean a significant improvement in the efficient use of energy versus manual production methods, but there is still scope for improving efficiency and productivity. One of the methods to improve efficiency is the definition of optimal trajectories in the execution of automated tasks. In small and medium-scale flexible manufacturing systems, the tasks assigned to CNC machines are usually given in standardized formats, such as G-code, where the paths defined from the design software do not necessarily take into account the efficient use of the energy for a given machine. This problem is addressed in this paper from the need to optimize the use of energy in an articulated robot that performs a drilling task originally designed to be executed in a CNC drill. We propose a simple method to model the energy consumption of the robot as an optimization problem in the well-known form of a Traveler Salesman Problem (TSP), with which it is possible to use common software packages for its resolution. The proposed solution simplifies the approach of the optimization problem in relation to other proposals in the literature and is generalizable to other machining tasks and machining systems.
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This paper provides an alternative to digital filter based frequency detection for multi-frequency shift keying modulation (M-FSK) using field programmable gate array (FPGA) architectures, by providing a hamming space autocorrelation... more
This paper provides an alternative to digital filter based frequency detection for multi-frequency shift keying modulation (M-FSK) using field programmable gate array (FPGA) architectures, by providing a hamming space autocorrelation based detector that outperforms the use of digital filters by consuming only 4% of an equivalent filter’s logic resources and no DSP blocks at all, with a detection accuracy of 97% while being non-dependant on Hermitian symmetry, orthogonality or any other radio frequency (RF) signal condition. This detection method supports an inexpensive, reliable and accurate real time data demodulation strategy for flicker-free, high dimming range visible light communications (VLC) multi-user systems.
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This paper presents a methodology for the generation of detection and classification models of light emitters in digital video frames for indoor and outdoor visible light communication applications, including the generation of a user... more
This paper presents a methodology for the generation of detection and classification models of light emitters in digital video frames for indoor and outdoor visible light communication applications, including the generation of a user interface for the generation of Datasets of light emitter characteristics. Showing that is possible to analyze the frames of video by applying a classification model, allowing the development of new models to decrease the processing time per frame.
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For years, it has been a great challenge for Internet Service Providers (ISP) to predict traffic load or future demand, since each bit of traffic is an economic cost to operators. Additionally, more and more users are adopting the... more
For years, it has been a great challenge for Internet Service Providers (ISP) to predict traffic load or future demand, since each bit of traffic is an economic cost to operators. Additionally, more and more users are adopting the different telecommunication services as well as the ISP must provide more bandwidth and reliability. In this sense, the study focuses on forecasting with neural network techniques, specifically Long Short-Term Memory (LSTM) and Online-Sequential Extreme Learning Machine (OS-ELM), the real traffic of a Chile ISP. The results show that OS-ELM outperforms LSTM in terms of computational cost by a factor of 2300, and in terms of network prediction, OS-ELM effectively competes with LSTM.
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In this paper, we consider the problem of forming clusters of nodes in a wireless visible light communication (VLC for short) network. More precisely, let $G=(V,\ E)$ be a complete graph with a set of wireless devices $V$ (nodes) and a... more
In this paper, we consider the problem of forming clusters of nodes in a wireless visible light communication (VLC for short) network. More precisely, let $G=(V,\ E)$ be a complete graph with a set of wireless devices $V$ (nodes) and a set of connection links $E$ (edges) representing the VLC network. We consider the problem of partitioning $k\leq \vert V\vert$ vertices into disjoint cliques of size of at most $\lfloor\frac{k}{t}\rfloor+1$ nodes where $t < k (k, t\in \mathbb{Z}_{+})$ such that the total power received plus the residual energy of each of the $k$ chosen nodes is maximized. Recall that clustering the sensor nodes of a network allows handling efficiently problems related to scalability, and routing, to name a few. In order to achieve the grouping task optimally, we propose integer linear and quadratic programming models based on classical combinatorial optimization problems from the literature. In order to compare our proposed models, we assume that every node in the network can communicate through a direct line of sight (DLOS) VLC channel. Our preliminary numerical results indicate that the quadratic model together with its linearized counterpart are the best ones as they allow to solve to optimality all tested instances in significantly less computational effort.
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In this paper, we consider the problem of maximizing the total number of users in a multi-cell wireless network subject to power and independent set constraints on the base stations (BSs). More precisely, we impose the condition that no... more
In this paper, we consider the problem of maximizing the total number of users in a multi-cell wireless network subject to power and independent set constraints on the base stations (BSs). More precisely, we impose the condition that no two adjacent BSs can operate simultaneously due to interference requirements. We propose equivalent mixed integer linear and quadratic programming formulations for this problem and compute upper and lower bounds as well as optimal solutions for instances with up to 2000 users and 30 BSs so far. The equivalent quadratic model is obtained by penalizing the independent set constraints leading to a quadratic problem with non-convex objective function that is hard to solve. To overcome this difficulty, we derive an equivalent quadratic concave objective function which allows to solve the problem to optimality using CPLEX. Finally, we propose an efficient greedy heuristic. In our numerical experiments, we consider realistic disk graph based network instances with radial transmission ranges of 40 to 10 ms for each base station. Network deployments are generated randomly within an area of 50*50 ms2. Our preliminary numerical results indicate that for different instances, either the linear or quadratic model allows to find the optimal solution more efficiently. Whilst the proposed greedy heuristic allows to obtain tight near optimal solutions for most part of the instances with gaps which are lower than 5% from the optimal solution in less than one second.
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Reconfigurable Intelligent Surface (RIS) has been considered as a promising technology that provides ultra-high speed for 5G beyond (5GB) and future 6G wireless communication systems. An RIS has boosted the concept of Smart Radio... more
Reconfigurable Intelligent Surface (RIS) has been considered as a promising technology that provides ultra-high speed for 5G beyond (5GB) and future 6G wireless communication systems. An RIS has boosted the concept of Smart Radio Environment (SRE) to enable Massive Connectivity with Massive MIMO System. RIS and Massive MIMO are both key enablers at the infrastructural level while millimeter wave (mm-Wave) and Tera Hertz (THz) communication are the key enablers at spectrum level for 5G and 6G. In this article, we discuss some potential candidate technologies and applications using mm-Wave Massive MIMO that can be well equipped with RIS in order to play a vital role in future wireless communication. The applications include Unnamed Aerial Vehicle and Visible Light Communications (VLC). In particular, we discuss and provide insights for VLC technology using RIS. As far as we know, these novel technologies have not been discussed and analyzed in a joint manner so far.
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This paper provides an alternative to digital filter based frequency detection for multi-frequency shift keying modulation (M-FSK) using field programmable gate array (FPGA) architectures, by providing a hamming space autocorrelation... more
This paper provides an alternative to digital filter based frequency detection for multi-frequency shift keying modulation (M-FSK) using field programmable gate array (FPGA) architectures, by providing a hamming space autocorrelation based detector that outperforms the use of digital filters by consuming only 4% of an equivalent filter’s logic resources and no DSP blocks at all, with a detection accuracy of 97% while being non-dependant on Hermitian symmetry or any other radio frequency (RF) signal condition. This detection method supports an inexpensive, reliable and accurate real time data demodulation strategy for flicker-free, high dimming range visible light communications (VLC) multi-user systems.
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In this paper, a novel method is presented for estimating the number of speakers based on the microphone arrays. Firstly, a 3D snowflake nested microphone array (SNMA) is proposed for recording the speech signals. In the following, the... more
In this paper, a novel method is presented for estimating the number of speakers based on the microphone arrays. Firstly, a 3D snowflake nested microphone array (SNMA) is proposed for recording the speech signals. In the following, the steered response power (SRP) algorithm is implemented on subbands in limited spaces conditions for all microphone pairs related to the subarrays. Therefore, a weighted averaging method is implemented on subband limited spaces SRPs (LSRP), and the final energy map is compared with the histogram of the maximums of the SRP function on different subbands for various time frames. The passed candidate points are categorized by unsupervised K-means clustering and the number of speakers is estimated by the silhouette criteria. The accuracy of the proposed method is compared with PENS, i-vector PLDA, and wavelet-GEVD algorithms. The results show the superiority of the proposed method in comparison with other previous research.
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This research presents a comparison between two blind separation techniques from sources, which are Fast independent component analysis (FastIca) and Maximization of Ica information (InfoMax). To do this, two audio signals are used, which... more
This research presents a comparison between two blind separation techniques from sources, which are Fast independent component analysis (FastIca) and Maximization of Ica information (InfoMax). To do this, two audio signals are used, which will be input to the two separation techniques of blind sources and finally the yield will be measured using the mean square error method.
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Hybrid digital and analog beamforming are today widely research topics in massive MIMO systems due to low cost and low power consumption as compared to conventional fully digital beamforming method. The beamforming matrix consists of... more
Hybrid digital and analog beamforming are today widely research topics in massive MIMO systems due to low cost and low power consumption as compared to conventional fully digital beamforming method. The beamforming matrix consists of analog radio frequency (RF) precoder and it is implemented by using phase shifters and baseband digital precoder. Carrier aggregation (CA) is a technology that allows bandwidth expansion to improve data capacity by combining two or more carriers in the same or different frequency bands. The digital baseband precoder is the main challenge and can be adapted to the channel of each carrier in the frequency domain while the same analog RF precoder must be applied to all carriers simultaneously in the time domain. The main goal of our research is to combine CA technology with hybrid digital and analog beamforming architecture to provide an improved system performance with less penalty. This paper proposes a hybrid precoding algorithm to support two carriers aggregated that are based on this scenario. We present numerical results that prove theoretical expressions and give practical explanation of the proposed method demonstrating its superiority when compared to the traditional hybrid beamforming design.
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This paper seeks to reduce the noise in signals present in a wireless channel using Multiresolution Analysis (MRA). The noise reduction is performed by applying the MRA to signals obtained from a wireless channel such as a VLC (Visible... more
This paper seeks to reduce the noise in signals present in a wireless channel using Multiresolution Analysis (MRA). The noise reduction is performed by applying the MRA to signals obtained from a wireless channel such as a VLC (Visible Light Communication) channel. The work is carried out by means of software that allows to apply MRA for the respective noise reduction. The effectiveness of the MRA will depend on the level of signal decomposition, as well as the detail and approximation components that are subsequently used for the reconstruction of the signal itself. The results obtained are favorable in the opinion of the authors. Finally obtaining a significant noise reduction.
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There is an increasing interest in planning sensor networks by considering both the impact of distances among sensors and the risk that power consumption leads to a very small network lifetime. A sensor failure can affect sensors in its... more
There is an increasing interest in planning sensor networks by considering both the impact of distances among sensors and the risk that power consumption leads to a very small network lifetime. A sensor failure can affect sensors in its neighborhood and compromise the network data communication. Weather conditions may cause the power consumption of data communication to vary with uncertainty. This work introduces a compact probabilistic optimization approach to handle this problem while considering jointly or separately dependence among power consumption of the links of the network in a unified framework. We explore the concept of copulas in a dominating arborescence (DA) model for directed graphs, extended accordingly to handle the uncertain parameters. We give a proof of the DA model correctness and show that it can solve to optimality some benchmark instances of the deterministic dominating tree problem. Numerical results for the probabilistic approach show that our model tackles randomly generated instances with up to 120 nodes.
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ABSTRACT In this paper, we compare individual and joint probabilistic constraints for a resource allocation problem in an uplink (UL) wireless OFDMA network. For this purpose, we formulate the problem as a stochastic linear programming... more
ABSTRACT In this paper, we compare individual and joint probabilistic constraints for a resource allocation problem in an uplink (UL) wireless OFDMA network. For this purpose, we formulate the problem as a stochastic linear programming (SLP) problem. Then, we transform this model into equivalent deterministic Second-Order Cone Programming (SOCP) problems. All models are intended to maximize the bit rates throughput of the network subject to subcarrier and power user constraints. Our preliminary numerical results show that the joint chance constraint formulation is slightly conservative than the individual probabilistic one. Finally, we show that our approximation of the deterministic joint probabilistic model is very tight.
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This paper proposes two binary quadratic formulations for minimizing power subject to bit rate and sub-carrier allocation constraints over wireless downlink (DL) Orthogonal Frequency Division Multiple Access (OFDMA). The rst model... more
This paper proposes two binary quadratic formulations for minimizing power subject to bit rate and sub-carrier allocation constraints over wireless downlink (DL) Orthogonal Frequency Division Multiple Access (OFDMA). The rst model represents a restricted case in which users are allowed to use only one modulation size in each sub-carrier while the second, a more exible real case in which they can use any size. We propose two semidenite programming relaxations (SDP) and compare with the linear programs (LP) obtained by applying Fortet linearization method to the quadratic models. Numerical results show a total average tightness gain of 42.78 % and 97.17 % in the rst and second case, respectively. Moreover we get near optimal bounds, in average, of 1 % for the second model over realistic data.