Studies in Software-Defined Radio System Implementation

Over the past decade, software-defined radios (SDRs) have an increasingly prevalent aspect of wireless communication systems. Different than traditional hardware radios which implement radio protocols using static electrical circuit, SDRs implement significant aspects of physical radio protocol using software programs running on a host processor. Because they use software to implement most of the radio functionality, SDRs are much more easily modified, edited, and upgraded than their hardware-defined counterparts. Consequently, researchers and developers have been developing previously hardware-defined radio systems within software. Thus, communication standards can be tested under different conditions or swapped out entirely by simply changing some code. Additionally, developers hope to implement more advanced functionality with SDRs such as cognitive radios that can sense the conditions of the environment and change parameters or protocol accordingly. This paper will outline the major aspects of SDRs including their explanation, advantages, and architecture. As SDRs have become more commonplace, many companies and organizations have developed hardware front-ends and software packages to help develop software radios. The most prominent hardware front-ends to date have been the USRP hardware boards. Additionally, many software packages exist for SDR development, including the open source GNU Radio and OSSIE and the closed source Simulink and Labview SDR packages. Using these development tools, researchers have developed many of the most relevant radio standards. This paper will explain the major hardware and software development tools for creating SDRs, and it will explain some of the most important SDR projects that have been implemented to date

Analysis of radio frequency spectrum usage using cognitive radio

This paper presents the analysis of radio frequency (RF) spectrum usage using cognitive radio. The aim was to determine the unused spectrum frequency bands for efficiently utilization. A program was written to reuse a range of vacant frequency with different model element working together to produce a spectrum sensing in MATLAB/Simulink environment. The developed Simulink model was interfaced with a register transfer level - software defined radio, which measures the estimated noise power of the received signal over a given time and bandwidth. The threshold estimation performed generates a 1\0 output for decision and prediction. It was observed that some spectrum, identified as vacant frequency, were underutilized in FM station in Benin City. The result showed that when cognitive radio displays “1” output, which is decision H1, the channel is occupied and cannot be used by the cognitive radio for communication. Conversely, when “0” output (decision H0) is displayed, the channel is unoccupied. There is a gradual decrease in the probability of detection (Pd), when the probability of false alarm (Pfa) is increased from 1% to 5%. In the presence of higher Pfa, the Pd of the receiver maintains a high stability. Hence, the analysis finds the spectrum hole and identifies how it can be reuse

Spectrum measurement, sensing, analysis and simulation in the context of cognitive radio

The radio frequency (RF) spectrum is a scarce natural resource, currently regulated locally by national agencies. Spectrum has been assigned to different services and it is very difficult for emerging wireless technologies to gain access due to rigid spectmm policy and heavy opportunity cost. Current spectrum management by licensing causes artificial spectrum scarcity. Spectrum monitoring shows that many frequencies and times are unused. Dynamic spectrum access (DSA) is a potential solution to low spectrum efficiency. In DSA, an unlicensed user opportunistically uses vacant licensed spectrum with the help of cognitive radio. Cognitive radio is a key enabling technology for DSA. In a cognitive radio system, an unlicensed Secondary User (SU) identifies vacant licensed spectrum allocated to a Primary User (PU) and uses it without harmful interference to the PU. Cognitive radio increases spectrum usage efficiency while protecting legacy-licensed systems. The purpose of this thesis is to bring together a group of CR concepts and explore how we can make the transition from conventional radio to cognitive radio. Specific goals of the thesis are firstly the measurement of the radio spectrum to understand the current spectrum usage in the Humber region, UK in the context of cognitive radio. Secondly, to characterise the performance of cyclostationary feature detectors through theoretical analysis, hardware implementation, and real-time performance measurements. Thirdly, to mitigate the effect of degradation due to multipath fading and shadowing, the use of -wideband cooperative sensing techniques using adaptive sensing technique and multi-bit soft decision is proposed, which it is believed will introduce more spectral opportunities over wider frequency ranges and achieve higher opportunistic aggregate throughput.Understanding spectrum usage is the first step toward the future deployment of cognitive radio systems. Several spectrum usage measurement campaigns have been performed, mainly in the USA and Europe. These studies show locality and time dependence. In the first part of this thesis a spectrum usage measurement campaign in the Humber region, is reported. Spectrum usage patterns are identified and noise is characterised. A significant amount of spectrum was shown to be underutilized and available for the secondary use. The second part addresses the question: how can you tell if a spectrum channel is being used? Two spectrum sensing techniques are evaluated: Energy Detection and Cyclostationary Feature Detection. The performance of these techniques is compared using the measurements performed in the second part of the thesis. Cyclostationary feature detection is shown to be more robust to noise. The final part of the thesis considers the identification of vacant channels by combining spectrum measurements from multiple locations, known as cooperative sensing. Wideband cooperative sensing is proposed using multi resolution spectrum sensing (MRSS) with a multi-bit decision technique. Next, a two-stage adaptive system with cooperative wideband sensing is proposed based on the combination of energy detection and cyclostationary feature detection. Simulations using the system above indicate that the two-stage adaptive sensing cooperative wideband outperforms single site detection in terms of detection success and mean detection time in the context of wideband cooperative sensing

An evaluation of low cost fpga-based software defined radios for education and research

The purpose of this study is to evaluate a low-cost Software Defined Radio (SDR) platform for educational and research purposes. An evaluation of existing SDR platforms and design techniques was performed, identifying low cost hardware and software suitable for a laboratory environment. The idea behind the project is to provide undergraduate students with a generic hardware platform so that they can perform simple radio communication experiments. This paper compares and evaluates the existing research projects and educational lab experiments done for SDR. Basic AM and FM radios are created and simulated on the hardware. The detailed procedure to create a design and download the design onto the hardware has been documented, and tutorials are created for step-by-step procedures to perform the experiments. With their ease of use and low cost, Spartan3E FPGA board and Simulink are the best choices for conducting low frequency radio communication experiments

RF channel characterization for cognitive radio using support vector machines

Cognitive Radio promises to revolutionize the ways in which a user interfaces with a communications device. In addition to connecting a user with the rest of the world, a Cognitive Radio will know how the user wants to connect to the rest of the world as well as how to best take advantage of unused spectrum, commonly called white space\u27. Through the concept of Dynamic Spectrum Acccess a Cognitive Radio will be able to take advantage of the white space in the spectrum by first identifying where the white space is located and designing a transmit plan for a particular white space. In general a Cognitive Radio melds the capabilities of a Software Defined Radio and a Cognition Engine. The Cognition Engine is responsible for learning how the user interfaces with the device and how to use the available radio resources while the SDR is the interface to the RF world. At the heart of a Cognition Engine are Machine Learning Algorithms that decide how best to use the available radio resources and can learn how the user interfaces to the CR. To decide how best to use the available radio resources, we can group Machine Learning Algorithms into three general categories which are, in order of computational cost: 1.) Linear Least Squares Type Algorithms, e.g. Discrete Fourier Transform (DFT) and their kernel versions, 2.) Linear Support Vector Machines (SVMs) and their kernel versions, and 3.) Neural Networks and/or Genetic Algorithms. Before deciding on what to transmit, a Cognitive Radio must decide where the white space is located. This research is focused on the task of identifying where the white space resides in the spectrum, herein called RF Channel Characterization. Since previous research into the use of Machine Learning Algorithms for this task has focused on Neural Networks and Genetic Algorithms, this research will focus on the use of Machine Learning Algorithms that follow the Support Vector optimization criterion for this task. These Machine Learning Algorithms are commonly called Support Vector Machines. Results obtained using Support Vector Machines for this task are compared with results obtained from using Least Squares Algorithms, most notably, implementations of the Fast Fourier Transform. After a thorough theoretical investigation of the ability of Support Vector Machines to perform the RF Channel Characterization task, we present results of using Support Vector Machines for this task on experimental data collected at the University of New Mexico.\u2

Assessing the Performance of a MIMO SDR Testbed with Dual Transceiver Implementation

Software Defined Radio testbeds are becoming increasingly used in the wireless networking community, given their feature of leaving wireless network designer full control of the PHY layer. On the other hand, SDR testbeds are formed of very complex software/hardware tools, in which implementation bugs are likely and difficult to identify. For this reason, assessment of the results provided by an SDR platform should be a fundamental, preliminary step in the performance evaluation process. In this paper, we provide a thorough assessment of the MIMONet SDR platform for network-level exploitation of MIMO technology. To assess the platform, we have used two different implementations of an OFDM transceiver: one based on Matlab, the other on the GNU Radio software. We have then crossvalidated performance by means of extensive measurements using the two alternative implementations. We have also designed and implemented a fine grained SNR and BER estimation methodology, that allowed us to carefully validate performance of the two software implementations against theoretical predictions. When collectively considered, the results of our measurements promote MIMONet as the first SDR testbed with carefully validated performance

PROPUESTA DE DISEÑO DE UN RADIO DEFINIDO PORSOFTWARE PARA LA CARACTERIZACIÓN DE LA BANDA IMT

En este artículo se define la propuesta de diseño de un radio definido por software para la caracterización o sensado de la banda de telecomunicaciones móviles celulares. Para ello, se definen los sistemas de radiocomunicaciones utilizados en los servicios inalámbricos. Con este fin se caracterizaron las bandas de espectro radioeléctrico denominadas IMT (Internacional Mobile Telecommunication) y se analizan  los sistemas de radio definido por software para posteriormente presentar la propuesta de diseño. En donde se definieron las etapas de diseño de la plataforma de gestión, diseño del radio definido por software y el procesamiento de señal que permitirán generar plataformas con sistemas de USPR (Universal Software Radio Peripheral) mediante herramientas como MATLAB y GNU Radio

An FPGA implementation of OFDM transceiver for LTE applications

The paper presents a real-time transceiver using an Orthogonal Frequency-Division Multiplexing (OFDM) signaling scheme. The transceiver is implemented on a Field- Programmable Gate Array (FPGA) through Xilinx System Generator for DSP and includes all the blocks needed for the transmission path of OFDM. The transmitter frame can be reconfigured for different pilot and data schemes. In the receiver, time-domain synchronization is achieved thr ough a joint maximum likelihood (ML) symbol arrival-time and carrier frequency offset (CFO) estimator through the redundant information contained in the cyclic prefix (CP). A least-squares channel estimation retrieves the channel state information and a simple zero-forcing scheme has been implemented for channel equalization. Results show that a rough implementation of the signal path can be impleme nted by using only Xilinx System Generator for DSP

Optimization of DSSS Receivers Using Hardware-in-the-Loop Simulations

Over the years, there has been significant interest in defining a hardware abstraction layer to facilitate code reuse in software defined radio (SDR) applications. Designers are looking for a way to enable application software to specify a waveform, configure the platform, and control digital signal processing (DSP) functions in a hardware platform in a way that insulates it from the details of realization. This thesis presents a tool-based methodolgy for developing and optimizing a Direct Sequence Spread Spectrum (DSSS) transceiver deployed in custom hardware like Field Programmble Gate Arrays (FPGAs). The system model consists of a tranmitter which employs a quadrature phase shift keying (QPSK) modulation scheme, an additive white Gaussian noise (AWGN) channel, and a receiver whose main parts consist of an analog-to-digital converter (ADC), digital down converter (DDC), image rejection low-pass filter (LPF), carrier phase locked loop (PLL), tracking locked loop, down-sampler, spread spectrum correlators, and rectangular-to-polar converter. The design methodology is based on a new programming model for FPGAs developed in the industry by Xilinx Inc. The Xilinx System Generator for DSP software tool provides design portability and streamlines system development by enabling engineers to create and validate a system model in Xilinx FPGAs. By providing hierarchical modeling and automatic HDL code generation for programmable devices, designs can be easily verified through hardware-in-the-loop (HIL) simulations. HIL provides a significant increase in simulation speed which allows optimization of the receiver design with respect to the datapath size for different functional parts of the receiver. The parameterized datapath points used in the simulation are ADC resolution, DDC datapath size, LPF datapath size, correlator height, correlator datapath size, and rectangular-to-polar datapath size. These parameters are changed in the software enviornment and tested for bit error rate (BER) performance through real-time hardware simualtions. The final result presents a system design with minimum harware area occupancy relative to an acceptable BER degradation