Design and implementation of an OFDM-based communication system for the GNU Radio platform

Projecte final de carrera fet en col.laboració amb Institut für Kommunikationsnetze und Rechnersysteme. Universität StuttgartCatalà: El processament de senyal en temps real mitjançant software és un camp que s'està expandint molt gràcies a la capacitat de processament dels ordinadors actuals. L'objectiu d'aquest treball ha estat el disseny i la implementació d'una Ràdio Definida en Software (SDR) que funcioni amb tecnologia OFDM, similar a la utilitzada en les comunicacions mòvils de 4a generació, per a la plataforma GNU Radio.Castellano: El procesado de señal en tiempo real mediante software es un campo en expansión gracias a la capacidad de computación de los ordenadores actuales. El objetivo de este trabajo ha sido el diseño y la implementación de una Radio Definida en Software (SDR) que funcione con tecnología OFDM, similar a la utilizada en las comunicaciones móviles de 4ª generación, para la plataforma GNU Radio.English: Software based real time signal processing is a field in expansion thanks to the computing capacity of actual personal computers. The objective of this work is the design and the implementation of a Software Defined Radio (SDR) that uses OFDM technology, which is the one used in the 4th generation of wireless communications

Design and implementation of an OFDM-based communication system for the GNU Radio platform

Projecte final de carrera fet en col.laboració amb Institut für Kommunikationsnetze und Rechnersysteme. Universität StuttgartCatalà: El processament de senyal en temps real mitjançant software és un camp que s'està expandint molt gràcies a la capacitat de processament dels ordinadors actuals. L'objectiu d'aquest treball ha estat el disseny i la implementació d'una Ràdio Definida en Software (SDR) que funcioni amb tecnologia OFDM, similar a la utilitzada en les comunicacions mòvils de 4a generació, per a la plataforma GNU Radio.Castellano: El procesado de señal en tiempo real mediante software es un campo en expansión gracias a la capacidad de computación de los ordenadores actuales. El objetivo de este trabajo ha sido el diseño y la implementación de una Radio Definida en Software (SDR) que funcione con tecnología OFDM, similar a la utilizada en las comunicaciones móviles de 4ª generación, para la plataforma GNU Radio.English: Software based real time signal processing is a field in expansion thanks to the computing capacity of actual personal computers. The objective of this work is the design and the implementation of a Software Defined Radio (SDR) that uses OFDM technology, which is the one used in the 4th generation of wireless communications

An architecture for converging reconfigurable radio systems

Since mobile telecommunication systems were rst introduced in the early 1980s they have become a pervasive part of modern life, with an estimated 85% of the global population believed to be in possession of a mobile communications device. To address the ever-increasing demand for fast ubiquitous provision of multimedia and data services, new Radio Access Technologies (RATs) capable of meeting those demands are constantly being developed and standardised. Currently the fourth generation of RATs is being deployed by network operators around the world, with standards bodies already working to develop and standardise even more advanced RATs. The introduction of any new, and often upgraded, RATs almost always requires network operators to purchase new hardware systems capable of supporting the new RATs, which must then be integrated with the plethora of RATs already present in the network operator's heterogeneous Radio Access Network (RAN). This process is costly and poses risks for network operators, as they must rst invest signi cant amounts of capital on new network hardware and then they have to convince their subscribers to purchase new mobile devices which are capable of supporting the new RAT. Recon gurable Radio Systems (RRSs) are a relatively new approach to developing, implementing and managing RATs within a RAN. A RRS di ers from a traditional radio system, in that each RAT is de ned in software which can be reused across multiple generic hardware platforms. Many RRSs also provide the functionality to manage and control the dynamic implementation of di erent RATs in network elements throughout a RAN. Although RRSs are the subject of numerous research e orts, there is currently no unifying approach or set of requirements for an RRS architecture or framework. In- stead various researchers focus their e orts on speci c topics relating to RRS, such as the recon gurable management system, or how RATs are modelled and implemented in software. This lack of formal standardisation or approach to developing RRSs represents a hindrance to the widespread adoption of RRSs

Communication System over Gnu Radio and OSSIE

GNU Radio and OSSIE (Open-Source SCA (Software communication architecture) Implementation-Embedded) are two open source software toolkits for SDR (Software Defined Radio) developments, both of them can be supported by USRP (Universal Software Radio Peripheral). In order to compare the performance of these two toolkits, an FM receiver over GNU Radio and OSSIE are tested in my thesis, test results are showed in Chapter 4 and Chapter 5. Results showed that the FM receiver over GNU Radio has better performance, due to the OSSIE is lack of synchronization between USRP interface and the modulation /demodulation components. Based on this, the SISO (Single Input Single Output) communication system over GNU Radio is designed to transmit and receive sound or image files between two USRP equipped with RFX2400 transceiver at 2.45G frequency. Now, GNU Radio and OSSIE are widely used for academic research, but the future work based on GNU Radio and OSSIE can be designed to support MIMO, sensor network, and real time users etc

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system

Agricultural Monitoring System using Images through a LPWAN Network

Internet of things (IoT) has turned into an opportunity to connect millions of devices through communication networks in digital environments. Inside IoT and mainly in the technologies of communication networks, it is possible to find Low Power Wide Area Networks (LPWAN). Within these technologies, there are service platforms in unlicensed frequency bands such as the LoRa Wide Area Network (LoRaWAN). It has features such as low power consumption, long-distance operation between gateway and node, and low data transport capacity. LPWAN networks are not commonly used to transport high data rates as in the case of agricultural images. The main goal of this research is to present a methodology to transport images through LPWAN networks using LoRa modulation. The methodology presented in this thesis is composed of three stages mainly. The first one is image processing and classification process. This stage allows preparing the image in order to give the information to the classifier and separate the normal and abnormal images; i.e. to classify the images under the normal conditions of its representation in contrast with the images that can represent some sick or affectation with the consequent presence of a particular pathology. For this activity. it was used some techniques were used classifiers such as Support Vector Machine SVM, K-means clustering, neuronal networks, deep learning and convolutional neuronal networks. The last one offered the best results in classifying the samples of the images. The second stage consists in a compression technique and reconstruction algorithms. In this stage, a method is developed to process the image and entails the reduction of the high amount of information that an image has in its normal features with the goal to transport the lowest amount of information. For this purpose, a technique will be presented for the representation of the information of an image in a common base that improves the reduction process of the information. For this activity, the evaluated components were Wavelet, DCT-2D and Kronecker algorithms. The best results were obtained by Wavelet Transform. On the other hand, the compres- sion process entails a series of iterations in the vector information, therefore, each iteration is a possibility to reduce that vector until a value with a minimum PSNR (peak signal to noise ratio) that allows rebuilding the original vector. In the reconstruction process, Iterative Hard Thresholding (IHT), Ortogonal MAtching Pur- suit (OMP), Gradient Projection for Sparse Reconstruction (GPSR)and Step Iterative Shrinage/Thresholding (Twist) algorithms were evaluated. Twist showed the best performance in the results. Finally, in the third stage, LoRa modulation is implemented through the creation of LoRa symbols in Matlab with the compressed information. The symbols were delivered for transmission to Software Defined Radio (SDR). In the receptor, a SDR device receives the signal, which is converted into symbols that are in turn converted in an information vector. Then, the reconstruction process is carried out following the description in the last part of stage 2 - compression technique and reconstruction algorithms, which is described in more detailed in chapter 3, section 3.2. Finally, the image reconstructed is presented. The original image and the result image were compared in order to find the differences. This comparison used Peak Signal-to-Noise Ratio (PSNR) feature in order to get the fidelity of the reconstructed image with respect of the original image. In the receptor node, it is possible to observe the pathology of the leaf. The methodology is particularly applied for monitoring abnormal leaves samples in potato crops. This work allows finding a methodology to communicate images through LPWAN using the LoRa modulation technique. In this work, a framework was used to classify the images, then, to process them in order to reduce the amount of data, to establish communication between a transmitter and a receiver through a wireless communication system and finally, in the receptor, to obtain a picture that shows the particularity of the pathology in an agricultural crop.Gobernación de Boyacá, Colfuturo, Colciencias, Universidad Santo Tomás, Pontificia Universidad JaverianaInternet of things (IoT) has turned into an opportunity to connect millions of devices through communication networks in digital environments. Inside IoT and mainly in the technologies of communication networks, it is possible to find Low Power Wide Area Networks (LPWAN). Within these technologies, there are service platforms in unlicensed frequency bands such as the LoRa Wide Area Network (LoRaWAN). It has features such as low power consumption, long-distance operation between gateway and node, and low data transport capacity. LPWAN networks are not commonly used to transport high data rates as in the case of agricultural images. The main goal of this research is to present a methodology to transport images through LPWAN networks using LoRa modulation. The methodology presented in this thesis is composed of three stages mainly. The first one is image processing and classification process. This stage allows preparing the image in order to give the information to the classifier and separate the normal and abnormal images; i.e. to classify the images under the normal conditions of its representation in contrast with the images that can represent some sick or affectation with the consequent presence of a particular pathology. For this activity. it was used some techniques were used classifiers such as Support Vector Machine SVM, K-means clustering, neuronal networks, deep learning and convolutional neuronal networks. The last one offered the best results in classifying the samples of the images. The second stage consists in a compression technique and reconstruction algorithms. In this stage, a method is developed to process the image and entails the reduction of the high amount of information that an image has in its normal features with the goal to transport the lowest amount of information. For this purpose, a technique will be presented for the representation of the information of an image in a common base that improves the reduction process of the information. For this activity, the evaluated components were Wavelet, DCT-2D and Kronecker algorithms. The best results were obtained by Wavelet Transform. On the other hand, the compres- sion process entails a series of iterations in the vector information, therefore, each iteration is a possibility to reduce that vector until a value with a minimum PSNR (peak signal to noise ratio) that allows rebuilding the original vector. In the reconstruction process, Iterative Hard Thresholding (IHT), Ortogonal MAtching Pur- suit (OMP), Gradient Projection for Sparse Reconstruction (GPSR)and Step Iterative Shrinage/Thresholding (Twist) algorithms were evaluated. Twist showed the best performance in the results. Finally, in the third stage, LoRa modulation is implemented through the creation of LoRa symbols in Matlab with the compressed information. The symbols were delivered for transmission to Software Defined Radio (SDR). In the receptor, a SDR device receives the signal, which is converted into symbols that are in turn converted in an information vector. Then, the reconstruction process is carried out following the description in the last part of stage 2 - compression technique and reconstruction algorithms, which is described in more detailed in chapter 3, section 3.2. Finally, the image reconstructed is presented. The original image and the result image were compared in order to find the differences. This comparison used Peak Signal-to-Noise Ratio (PSNR) feature in order to get the fidelity of the reconstructed image with respect of the original image. In the receptor node, it is possible to observe the pathology of the leaf. The methodology is particularly applied for monitoring abnormal leaves samples in potato crops. This work allows finding a methodology to communicate images through LPWAN using the LoRa modulation technique. In this work, a framework was used to classify the images, then, to process them in order to reduce the amount of data, to establish communication between a transmitter and a receiver through a wireless communication system and finally, in the receptor, to obtain a picture that shows the particularity of the pathology in an agricultural crop.Doctor en IngenieríaDoctoradohttps://orcid.org/0000-0002-3554-1531https://scholar.google.com/citations?user=5_dx9REAAAAJ&hl=eshttps://scienti.minciencias.gov.co/cvlac/EnRecursoHumano/query.d

Implementation of OFDM Encryption and a New Frequency Hopping System

As the rapid growth of wireless communication, physical layer security becomes important recently. Unlike wired transmissions, the nature of wireless transmissions makes the transmitted signals over the channel easily to be eavesdropped and jammed by malicious adversaries. The eavesdropper posts a significant threat to the privacy of public people, and the jamming attack blocks the wireless transmission. Therefore, privacy and reliability of the wireless communication system are easily compromised compared to the wired communication system. Consequently, wireless network security has attracted public attention in the recent years. Wireless networks can be secured in all layers of a network protocol stack which include application, transport, network, data link and physical layers. This thesis focuses on the physical layer security in wireless communication. Specifically, the physical layer security we are focusing on has two significant branches which are orthogonal frequency-division multiplexing (OFDM) related security system and frequency hopping (FH) system. The former one is to prevent transmitting information from stealing, and the latter one focuses on preventing jamming attacks. It is commonly known that OFDM is widely used in wireless communication systems, including WIFI and cellular system. In the first part of this thesis, we use software defined radio to implement an existing OFDM encryption scheme called OFDM Enc in IEEE 802.11a standard, and the implementations are done in microwave anechoic chamber and laboratory environment separately. Based on the implementation performed in the GNU radio, we find a multipath boundary in the OFDM Enc. In the second part of this thesis, we propose a new FH system named randomly selective m-sequence based BLADES system. Specifically, the collision properties of two distinct binary primitive polynomials of the same degree for the new FH system have been analysed and simulated