The universal software radio peripheral (USRP) family of products has become a popular platform for hardware-based research and test bed validations conducted by universities in the software defined radio (SDR) and cognitive radio (CR) fields. With the recently released version of National Instruments (NI) LabVIEW, the USRP now offers a scalable, simpler, and easier to use combined platform. The new software support broadens the accessibility of the USRP platform for teaching applications and will spur further adoption within university communication systems classrooms, teaching laboratories, and their natural follow-on coursework. This paper will discuss the utilization of LabVIEW-based virtual instrumentation with the USRP to rapidly create real-time communication systems demonstrations for the classroom and/or laboratory settings. The combination of the USRP, LabVIEW, and Windows support enables implementation and exploration of both foundational and more advanced concepts related to signal processing and communications.

Modern communication systems comprise a variety of formats, protocols, and frequency ranges. Software defined radio (SDR) technology addresses these formats with the idea that a single platform can be reprogrammed to process a variety of waveforms. The SDR Forum and the IEEE have defined SDR as a radio in which some or all of the physical layer functions are defined in software [1].

The universal software radio peripheral (USRP) family of products has become a popular platform for hardware-based research and test bed validations conducted by universities in the software defined radio (SDR) and cognitive radio (CR) fields. With the recently released universal hardware driver (UHD) and related support for Microsoft Windows and National Instruments LabVIEW, the USRP now offers a scalable, simpler, and easier to use combined platform. The new software support broadens the accessibility of the USRP platform for teaching applications and will spur further adoption within university communication systems classrooms, teaching laboratories, and their natural follow-on coursework (e.g., SDR, CR, Digital Communications, Wireless Communications, and Satellite Communications).This paper will discuss the utilization of National Instruments (NI) LabVIEW-based virtual instrumentation with the USRP and a UHD-based software driver to rapidly create real-time communication systems demonstrations for the classroom and/ or laboratory settings. The combination of the USRP, UHD, LabVIEW, and Windows support enables implementation and exploration of both foundational and more advanced concepts related to signal processing and communications.

Digital Signal Processing technology has transformed our way of life. It has become a fundamental building block in the biomedical, automotive, aerospace, communications and entertainment industries just to mention a few. Ironically, while these systems require interfacing with real world signals, operate in real-time and dynamically interact and present useful information, the pedagogical methods are largely simulation based, off-line processing and static. This paper presents LabVIEW as an educational DSP platform that allows professors to teach and students to learn DSP and advanced concepts by interfacing hardware to live signals, leverage graphical data flow (block diagram) programming to develop and encapsulate signal processing concepts and engage students to interact and develop DSP-based systems by abstracting inherent complexities of low level programming without restricting them. Successful academic case studies of LabVIEW as a DSP platform for real-time FPGA audio processing and multimedia communications are presented.

Interactive software demonstrations and computer-based exercises are often applied in signal processing education to examine concepts such as complex numbers, signal representation, sampling theory, and digital filter specification. While engineering software development environments such as National Instruments LabVIEW simplify the creation of such software, it's clear that some do a better job of improving understanding, motivating learners, and connecting theory with practical concerns. This paper explores how design choices that consider the interactive experience of the learner can have a clear role in determining the success for a demo in meeting these goals. We examine several demonstrations created by the authors, considering the development process and looking at some of the design and implementation choices intended to enhance learning.

This paper presents a set of inexpensive signal processing experiments that can be used as projects or hands-on demos to supplement signals and systems courses. Signals and systems concepts tend to be very mathematical and abstract, and students who prefer more practical material are at a disadvantage in these courses. The experiments are performed on the LEGO MINDSTORMS NXT platform, which is portable, relatively inexpensive, and rugged enough so that students can perform the experiments at home or in the classroom. Experiments introduced in this paper highlight fundamental concepts such as sampling, aliasing, digital filtering, frequency analysis, system identification, and control design. Projects, programs, and additional hints for instructors are posted on a website for free use.

Consider, for example, digital signal processing (DSP) and the ways in which it relates to instrumentation. A digital signal processor (DSP) is a microprocessor designed to perform mathematical operations on a digital sampled data stream in real-time. To process an analogue signal using a DSP, an anti-aliasing filter and analogue-to-digital converter (ADC) first digitise an analogue signal and pass the data stream to the DSP. The DSP may then modify the data stream in some way and then convert the signal back to an analogue signal via a digitalto-analogue converter (DAC) and anti-imaging filter. Traditional, stand-alone instruments like oscilloscopes typically use custom, fixed, vendordesigned embedded DSP systems. Alternatively, oscilloscope functionality could be implemented using the power of modern personal computer (PC) technology using plug-in PC hardware to digitise the real-world input signal, and then using the PC host processor to process the signal. This modular approach, known as virtual instrumentation, relies on software that you can develop and execute on a PC to provide userdefined instrumentation functionality.

Spectral analysis is often much more than applying an FFF (Fast Fourier Transform) to a time-domain signal. The raw output (the array of values) of an FFT does not necessarily yield accurate results for the measurement of a prominent tone frequency, amplitude, or phase. National Instruments have recently implemented a patent-pending tone-detection scheme based on curve fitting, a new addition to LabVIEW 6i. This feature describes how it can be applied to frequency analysis for an improved method of tone detection.

Fast Fourier transform-based implementations of the discrete Fourier transform have proven themselves the workhorses of discrete-time spectral analysis. Although these algorithms find widespread use, they have limitations. One problem is that frequency resolution is dependent on the number of samples available. For a given sampling frequency, the longer the data record, the better the frequency resolution. An alternative approach, model-based spectral analysis, is now being employed, as it derives a higher-resolution spectral detail from fewer samples. This approach was used by National Instruments Corp. in a portion of the design of a portable analyzer for the telephony industry. The analyzer is intended for technicians to use in diagnosing and locating faults on a standard twisted pair copper (plain old telephone system) line. In the software design phase, one option considered and tested for feasibility was employing model-based spectral analysis (MBSA) to decode a calling number delivery signal (better known as Caller ID). Not just applicable in this analyzer example, MBSA works in a variety of circumstances and offers a valuable addition to an engineer's toolbox of software-based methods for spectral analysis. The technique might find an application wherever there is a lack of data, as in the case of analysis of a short time event, or where a restriction is imposed to ensure that the spectral characteristics of a signal do not change over the duration of a data set.

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Designing Effective User Interfaces for Software Simulations to Teach Signal Processing Concepts Abstract Educators have embraced software simulations as a tool for teaching signal processing concepts. Simulations allow students to interact with abstract concepts such as convolution, difference equations, filtering, sampling theory and many more. Software simulations strive to achieve learning objectives by presenting an interactive user interface that gives students the ability to interactively explore relationships. Such interaction seeks to improve learning by fostering an intuitive feel for the relationship between parameters and the results. It is evident that the design of the user interface plays a key role in success or failure. For instance, students can easily be distracted by elements of the software or activities that are not directly related to the subject at hand. This paper presents user interface design advice that works toward development of software simulations and related student activities for teaching signal processing that successfully achieve learning objectives. Interactive software demonstrations developed using NI LabVIEW provide examples that support the discussion. Software for Signal Processing Education Educators have long realized the value of the PC for signal processing education1-6. A standard desktop or laptop PC offers a hardware platform for exploration and design that is widely accessible. Engineering software environments such as National Instruments LabVIEW7 enable educators and students to create, modify, and interact with custom educational software applications that explore linearity, time invariance, signal representation, transforms, digital filters, sampling theory, convolution, and other signal processing concepts. Such software can act as a tool to demonstrate a concept or as the basis for student exercises. It can be distributed in a variety of ways; on DVDs or through the Internet, sometimes through a convenient browser- based interface8-9. This paper focuses on signal processing concept software with graphical user interface (GUI) elements for interactivity. Such software can enable interactive examination of concepts through experimentation in which students specify trials by manipulating controls on the user interface such as knobs, dials, digital controls, switches, and buttons. As the input parameters are changed, the software shows the result by updating indicators on the user interface such as graphs, plots, numeric displays, and LEDs.

is a Senior Product Manager for Signal Processing and Communications at National Instruments (Austin, TX

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Communication Systems Laboratory Projects Featuring Interactive Simulation and Visualization Abstract Engineering communication systems courses rely heavily on mathematical descriptions that can be difficult for students to quickly grasp. Hands-on laboratory projects and interactive simulation are two well-established methods to help students develop an intuitive understanding of a knowledge domain. Constructing a tangible physical system helps students connect the mathematically-expressed concepts to something real. Moreover, building an interactive simulation fosters intuition, provided the simulation itself can be constructed quickly and efficiently. We have developed a set of laboratory projects that leverage the unique interactive visualization and simulation capabilities of the LabVIEW graphical dataflow programming environment. With LabVIEW, students quickly transform mathematical models, algorithms, and block diagrams into real-time systems whose dynamics can be experienced visually and aurally with an interactive graphical user interface. The laboratory projects guide students as they assemble working simulations and interact with the finished result. Each project presents required background theory as a mini-lecture embodied by a combination of text, diagrams, and streaming video screencasts, detailed specifications for subsystems to be built supported by video screencasts of relevant LabVIEW coding techniques, and suggested experiments to study and interact with the finished system. Hosted on the Connexions web-based open publishing resource, the projects are openly available and suitable as a turn-key solution for faculty who wish to enhance an existing communication systems course with little effort. What’s more, the modularity of the project materials and availability of Connexions editing tools enable faculty to modify and extend the projects. Project topics cover fundamental concepts such as bit error rate (BER) vs. Eb/No performance measure, coherent detection, baseband modulation, inter-symbol interference (ISI) and eye diagrams, and block coding. More advanced projects explore bandpass modulation schemes using the computer soundcard and speaker-air-microphone (SAM) channel; students visualize the signals as they pass through each subsystem and listen to the modulated waveforms, and quickly develop an appreciation for interrelationships between carrier frequency, channel bandwidth, bit rate, and noise level. Practical projects such as text messaging over the SAM channel and Caller ID signal decoding motivate student interest to further study of communication systems. Introduction Communication systems constitute an important part of all electrical engineering curricula. Introductory communication systems courses rely heavily on mathematical exposition to convey concepts, and traditional textbooks likewise feature mathematical derivations and proofs to explain fundamental concepts. The importance of a mathematical framework cannot be denied,

He teaches courses in digital systems, circuits, image processing, and electronic music synthesis, and his research interests include technology-enabled education, image processing, and FPGA-based signal processing.