Fpga implementation of spectrum sensing techniques for cr standards

Radio spectrum is a limited and valuable natural resource in wireless communications. The conventional spectrum allocation policies are causing a serious problem of spectrum scarcity to the emerging wireless technologies. On the other hand, the studies reveal that most of the licensed spectrum is underutilized. For efficient spectrum utilization, FCC is allowing the sharing of the licensed spectrum with unlicensed users. Cognitive radio is a technology which addresses the issue of spectrum sharing with the help of dynamic spectrum access. Spectrum sensing is a fundamental and essential module in cognitive radio which detects the presence of licensed users in the spectrum. To avoid the harmful interference from an unlicensed user to the licensed user, cognitive radio (CR) has to sense the spectrum efficiently so the spectrum sensing has to be carried out effectively. In this thesis, different spectrum sensing methods are analyzed and amongst the energy detection method has been considered for FPGA implementation. The parameters such as probability of false alarm and probability of detection are analyzed from Receiver Operating Curves of energy detection method. The energy detection technique in both time domain and in frequency domain has been implemented. The time domain implementation consists of three modules such as energy detector, threshold estimation and a decision module. The complete energy detection module is downloaded onto Spartan-3E FPGA and the validity of functionality is verified through Chipscope Pro core analyzer .In frequency domain implementation the input samples are transformed into frequency domain using FFT IP core generator. A simple model of covariance based spectrum sensing is also been implemented using HDL design

Efficient multi-standard cognitive radios on FPGAs

Cognitive radios that support multiple standards and modify operation depending on environmental conditions are becoming more important as the demand for higher bandwidth and efficient spectrum use increases. Traditional implementations in custom ASICs cannot support such flexibility, with standards changing at a faster pace, while software baseband implementations fail to achieve the performance required. Hence, FPGAs offer an ideal platform bringing together flexibility, performance, and efficiency. This work explores the possible techniques for designing multi-standard radios on FPGAs, and explores how partial reconfiguration can be leveraged in a way that is amenable for domain experts with minimal FPGA knowledge

Development of self-organizing methods for radio spectrum sensing

A problem of wide-band radio spectrum analysis in real time was solved and presented in the dissertation. The goal of the work was to develop a spectrum sensing method for primary user emission detection in radio spectrum by investigating new signal feature extraction and intelligent decision making techniques. A solution of this problem is important for application in cognitive radio systems, where radio spectrum is analyzed in real time. In thesis there are reviewed currently suggested spectrum analysis methods, which are used for cognitive radio. The main purpose of these methods is to optimize spectrum description feature estimation in real-time systems and to select suitable classification threshold. For signal spectrum description analyzed methods used signal energy estimation, analyzed energy statistical difference in time and frequency. In addition, the review has shown that the wavelet transform can be used for signal pre-processing in spectrum sensors. For classification threshold selection in literature most common methods are based on statistical noise estimate and energy statistical change analysis. However, there are no suggested efficient methods, which let classification threshold to change adaptively, when RF environment changes. It were suggested signal features estimation modifications, which let to increase the efficiency of algorithm implementation in embedded system, by decreasing the amount of required calculations and preserving the accuracy of spectrum analysis algorithms. For primary signal processing it is suggested to use wavelet transform based features extraction, which are used for spectrum sensors and lets to increase accuracy of noisy signal detection. All primary user signal emissions were detected with lower than 1% false alarm ratio. In dissertation, there are suggested artificial neural network based methods, which let adaptively select classification threshold for the spectrum sensors. During experimental tests, there was achieved full signals emissions detection with false alarm ratio lower than 1%. It was suggested self organizing map structure modification, which increases network self-training speed up to 32 times. This self-training speed is achieved due to additional inner weights, which are added in to self organizing map structure. In self-training stage network structure changes especially fast and when topology, which is suited for given task, is reached, in further self-training iterations it can be disordered. In order to avoid this over-training, self-training process monitoring algorithms must be used. There were suggested original methods for self-training process control, which let to avoid network over-training and decrease self-training iteration quantity

Algorithmic Framework and Implementation of Spectrum Holes Detection for Cognitive Radios

The ability to dynamically discover portions of unused radio spectrum (spectrum holes) is an important ability of cognitive radio systems. Spectrum holes present a potential opportunity for wireless communication. Detection of holes and signals allows cognitive radios to dynamically access and share the spectrum with minimal interference. This work steps through the design, implementation, and analysis of a spectrum holes detector for cognitive radios. Energy detection and cyclostationary detection algorithms for detecting spectrum holes are compared through computer simulations. Ultimately an energy detection algorithm is proposed which performs better than the cyclostationary detection algorithm and requires no a-priori knowledge of noise power. The energy detection algorithm is implemented on the bladeRF x115 software-defined radio for wideband detection, leveraging on-board FPGA hardware and field-programmable analog hardware to scan a gigahertz-order range of frequencies and discover spectrum holes in real time. Resource utilization and requirements of the implementation are analyzed, and a utilization of 8.8% of the FPGA\u27s logic resources is reported. Experiments are performed on the implementation to measure its detection performance and demonstrate its ability to detect holes over a wide bandwidth with reasonable latency

Banco de testes para monitoramento sub-Nyquist de espectro de banda larga

Radioelectric spectrum management is a concern for today’s world, mainly due to the misuse that has been given to this resource through the years, especially on the UHF band. To address this problem, a testbed for sub-Nyquist Wideband Spectrum Monitoring was built, that includes a web interface to remotely measure occupancy of the UHF band. To achieve the above, an RF interface that allows tuning UHF frequencies with an instantaneous bandwidth of 95 MHz was built. Afterwards, a Random Demodulator was connected, and then an embedded system performed sub--Nyquist sampling and spectrum recovery. The embedded system connected to an information system that serves a web page, through which remote users can perform UHF band monitoring. Experimental results showed that spectrum sensing can be achieved by using different algorithms on certain sparse spectra. In addition, the aforementioned web interface allowed simultaneous user connections, in order to perform independent measurements by sharing a hardware subsystem.La gestión del espectro radioeléctrico es una preocupación en la actualidad, hecho derivado, ante todo, del mal uso que se ha dado a este recurso a través de los años, especialmente en la banda de UHF. Para afrontar este problema, se construyó un banco de pruebas para la supervisión del espectro de banda ancha a través de muestreo sub-Nyquist, el cual incluye una interfaz web para medir de forma remota la ocupación de la banda UHF. Para lograr esto, se construyó una interfaz RF que permitiría sintonizar frecuencias UHF con un ancho de banda instantáneo de 95 MHz. Después, se conectó un demodulador aleatorio; y luego, un sistema embebido realizaría el muestreo sub-Nyquist y la recuperación del espectro. Este se conectaría, a su turno, con un sistema de información que sirve una página web, a través de la cual los usuarios remotos pueden realizar la supervisión de la banda de UHF. Los resultados muestran que la detección del espectro se puede lograr mediante diferentes algoritmos en ciertos espectros dispersos. Además, la interfaz web permitió que existiesen conexiones de usuario simultáneas, de tal manera que se realizaran mediciones independientes compartiendo el subsistema de hardware.O gerenciamento do espectro radioelétrico é uma preocupação na atualidade, fato derivado, inicialmente, do mau uso que se tem dado a esse recurso através dos anos, especialmente na banda de UHF. Para enfrentar esse problema, construiu-se um banco de testes para a supervisão do espectro de banda larga por meio de amostragem sub-Nyquist, a qual inclui uma interface web para medir de forma remota a ocupação da banda UHF. Para isso, construiu-se uma interface RF que permitiria sintonizar frequências UHF com uma largura de banda instantânea de 95 MHz. Em seguida, ligou-se um demodulador aleatório; logo, um sistema embebido realizaria a amostragem sub-Nyquist e a recuperação do espectro. Este se ligaria, por sua vez, com um sistema de informação que serve um site, através do qual os usuários remotos podem realizar a supervisão da banda de UHF. Os resultados mostram que a detecção do espectro pode ser conseguida mediante diferentes algoritmos em certos espectros dispersos. Além disso, a interface web permitiu que existissem conexões de usuário simultâneas, de tal maneira que se realizassem medidas independentes compartilhando o subsistema de hardware.&nbsp

Communication Subsystems for Emerging Wireless Technologies

The paper describes a multi-disciplinary design of modern communication systems. The design starts with the analysis of a system in order to define requirements on its individual components. The design exploits proper models of communication channels to adapt the systems to expected transmission conditions. Input filtering of signals both in the frequency domain and in the spatial domain is ensured by a properly designed antenna. Further signal processing (amplification and further filtering) is done by electronics circuits. Finally, signal processing techniques are applied to yield information about current properties of frequency spectrum and to distribute the transmission over free subcarrier channels