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Keynote Presentation

2011: A Breakthrough Year for Signal Processing System Design in MATLAB

Don Orofino, MathWorks

Over the past year, tremendous growth has occurred within MATLAB to address the needs of signal processing and communications engineers. We have introduced capabilities to improve the development workflow by simplifying system design, implementation, and verification in MATLAB. This talk provides an overview of these advances, including system toolboxes, MATLAB Coder, desktop acceleration, and software radio support. We conclude by showing how these capabilities unite MATLAB and Simulink into a single graphical/textual design platform.

We explore the system toolboxes introduced in Release 2011a that provide over 300 System objects and corresponding Simulink blocks for signal, vision, and communications applications, including support for fixed point and code generation. System objects simplify and extend the use of MATLAB for data stream processing. Characterized by "in the loop" computation involving sensor signals, stream processing is central to many signal processing systems. System objects combine the architectural power of object-oriented design with the simplicity of use that made MATLAB the standard for signal processing.

MATLAB Coder, a new product for R2011a, generates standard ANSI C code that users can compile into standalone executables, integrate into existing C code programs, or deploy onto embedded devices. We explore the use of MATLAB Coder for simulation acceleration and system implementation, with a focus on signal processing systems. We also touch upon new technologies for GPU-, FPGA-, and cluster-enabled acceleration.

Other recent product advances include SimRF for the simulation of RF systems and combined digital/RF systems; Phased Array System Toolbox for radar and communications; custom FPGA design support; and the integration of software radio peripherals for real-time communications simulation in MATLAB and Simulink. These new features round out the design, verification, and implementation workflow for modern communications and radar systems.

Cross-Track Session

Generating C and C++ Code from MATLAB Using MATLAB Coder

Arvind Ananthan, MathWorks

In this session we demonstrate the workflow for generating readable and portable C and C++ code from your MATLAB algorithms using MATLAB Coder. Using the command line or the graphical project management tool, you can introduce implementation requirements to your algorithms written in MATLAB and generate readable source code, a standalone compiled executable, or a library that can be shared across your organization.

MathWorks engineers also show how you can automatically generate MEX-functions that can be used to verify the behavior of the generated code back in MATLAB or to accelerate computationally intensive portions of your MATLAB code by running it at compiled speed.

Communications and Electronics Track

Verification of High-Efficiency Power Amplifier Performance at Nujira

Sean Lynch, Nujira

This presentation describes the approaches and tools we have used to verify the operation of our modulator designs. We use MathWorks tools across the entire development life cycle of our products from research, through design, to verification and automated testing.

RF power amplifiers (PAs) ensure that the source radio frequency (RF) signal, such as a DVB, 3G, LTE, or 4G signals, is powerful enough for transmission. Because PAs use a fixed supply voltage, they draw maximum power whatever the amplitude of the signal, making them notoriously inefficient for amplitude modulated RF signals. Conventional PAs waste as much as 80% of the energy they consume as dissipated heat. The PAs in a cellular base station, for example, account for half the total power consumed.

Although envelope tracking was first described more than 60 years ago, it has not been applied commercially until recently, largely due to the difficulty of implementing a power supply modulator that meets the efficiency, bandwidth, and noise requirements of wideband signals such as multicarrier WCDMA, WiMAX, or DVB.

Nujira’s envelope tracking technology can double the efficiency of PAs and dramatically reduce power dissipation, which lowers energy bills and substantially reduces the amount of cooling required. It also enables higher device output power, allowing broadcasters to extend the range of existing broadcasting towers. Lastly, the wideband operation of Nujira’s technology enables broadcasters to use fewer PA designs to cover their target broadcast spectrum. For handset applications, the use of envelope tracking also improves PA linearity. This is achieved by dynamically modulating the amplifier’s supply voltage according to the RF signal passing through the device.

Nujira’s High Accuracy Tracking (HAT) technology, the first practical implementation of envelope tracking, is being used or evaluated for cellular infrastructure and terminals, broadcast transmitters, military communications, and other applications. It is featured in three product lines: Coolteq.L for mobile handsets, Coolteq.h for cellular base stations, and Coolteq.u for DVB transmitters.

Modeling, Optimization, and Validation of Satellite Radio Signal Generators Using MATLAB

Cyril Iskander, Signal Processing Consultant

Averna's Universal Receiver Tester (URT) is a software-defined waveform generation platform used to test broadcast receivers for multiple radio and video standards. AM/FM car radios have been replaced by in-vehicle entertainment systems that support different broadcasting standards; rather than having one "box" for each standard to test, the URT allows switching between different radio standards by reconfiguring the same hardware system via a software user interface.

The URT supports the Sirius and XM satellite radio standards. Sirius and XM signals comprise terrestrial and satellite components (also termed "beams") that occupy 12.5 MHz of bandwidth for each standard. These signals must be generated in real time to comply with Sirius-XM testing specifications, while respecting guidelines for the quality of the produced waveforms. This presentation describes how MATLAB was used to model the generation process to obtain the necessary tradeoff between speed of execution and quality of waveform. The derived model was then validated using Averna's RF Signal Record and Playback system and a MATLAB API to generate the signal in real time and achieve lock on a production satellite radio receiver. The validated model was then used to benchmark the fixed-point implementation of the algorithm on an FPGA card.

FPGA-Based Sensing Algorithm Development Using Simulink and Third-Party Tools to Support Dynamic Spectrum Management

Alpaslan Demir, InterDigital

An increasing demand for high-throughput data services, network connectivity and mobility, and reliability is driving network operators to focus on developing wireless networks to provide a richer multimedia experience and new mobile broadband capabilities to serve billions of consumers globally. Using a holistic approach to meeting this demand, InterDigital is focused on three comprehensive areas of bandwidth innovations: spectrum optimization, cross-network connectivity and mobility, and intelligent data delivery techniques. As part of our efforts in spectrum optimization, we have been working on the development, simulation, and prototyping of architecture and algorithms with respect to the intelligent and efficient management of wireless spectrum commonly referred to as Dynamic Spectrum Management (DSM).

Since the environmental knowledge is essential to an intelligent DSM mechanism, the required information necessary to optimize spectrum utilization can be gathered from a global geo-location database that contains spectral information about the given location or through intelligent sensing techniques that gather sensing measurements from one or more nodes within the local area of the network. With the help of Simulink, InterDigital has developed sensing techniques that adhere to FCC requirements for operation of wireless devices in spectrum designated as TV White Space. InterDigital not only has used the tool to verify expected algorithm performance but was also able to generate code targeted to FPGA platforms based on the Xilinx® toolbox. This presentation describes the processes and methods used to develop both energy and feature-based sensing algorithms and also briefly describes the actual performance results gathered during the development of the MWC 2011 DSM prototype.

Modeling and Simulation of an All-Digital Phase-Locked Loop

Russell Mohn, Epoch Microelectronics

This presentation describes both a phase-domain model and time-domain model of an all-digital phase-locked loop (ADPLL). We emphasize using the models to derive specifications for PLL subblocks such as the phase-frequency detector and voltage-controlled oscillator. In addition, the models are to derive the specifications for an example fractional-N ADPLL covering 2 GHz to 3 GHz.

Technique for Phase Noise Reduction in Fractional-N PLLs for RF Applications

Henrik Jensen, Broadcom

This presentation showcases the unique ability of Simulink to perform highly accurate time-domain simulations of systems that contain a mixture of analog and digital signal processing including radio-frequency (RF) systems with gigahertz frequencies. The system being studied is a fractional-N phase-locked loop (PLL) frequency synthesizer incorporating a phase noise reduction scheme that largely eliminates the phase noise contributed by the quantization noise of the multimodulus divider (MMD) controller. This technique may be an enabling component for fast-settling, wideband fractional-N PLLs for applications such as Bluetooth, GSM, and wireless LAN.

Aerospace and Defense Track

Modeling Electronic Interference Scenarios

Jason Bryan, MathWorks

This session demonstrates how to model the effects of an electronic interferer on an end-to-end communication system using MATLAB and Simulink. The example shows how to interactively select different interfering signal types, power levels, and locations and then see the effects on system-level metrics such as bit error rate. It also shows how to include mitigation algorithms such as adaptive beam-forming.

Application of Model-Based Design Techniques to the Development of Antenna Control, SDR Waveform, and Radar Systems

David Alfred Haessig Jr., BAE Systems

Model-Based Design techniques for development of real-time embedded systems have been shown to provide several advantages over traditional methods. These advantages include the early detection and the reduction of defects, the shortening of development time, the facilitation of code reuse (i.e., model reuse), productivity enhancement. This presentation describes a series of projects that have benefited from the application of Model-Based Design. These projects span the fields of wireless communications, antenna control, and radar.

First, an on-the-move satcom antenna control system developed with Simulink Coder and xPC Target is discussed. A case study comparing model-based to traditional FPGA code development is also reviewed, highlighting where productivity enhancements were realized, and how to best adopt these new techniques within existing design teams. In this study the physical layer of a satcom waveform was constructed using both traditional and model-based methods, with quantitative metrics recorded for comparison. Finally, the presentation describes a radar system. An enhancement to BAE's Obstacle Avoidance and Cable Detection System (OACDS) was rapidly prototyped on a mixed DSP/FPGA platform integrated with MathWorks and Xilinx code generation tools. The presentation discusses the toolset features that enabled the rapid development and successful flight testing of this platform.

Approved for Release; No Export Controlled Information

Analysis of End-to-End Latencies for the Ares I Vehicle

Kerry Alexander, TriVector Services

This presentation is a case study of the use of Model-Based Design to analyze the time latency of health and status information for communications systems aboard NASA’s Ares I rocket. Engineers from TriVector Services modeled packet-level communications, ran discrete-event simulations, and assessed end-to-end latencies to confirm that functional requirements were sound and could be met. As a result of the project, requirements were able to be analyzed and validated one year earlier than would have otherwise been possible — even before hardware was available. Timing specification problems were uncovered and corrected, and latency analysis results could be summarized, graphed, and communicated visually.

Measurement and Analysis Techniques for Wireless Systems

Mike Donovan, MathWorks

Engineers working on wireless systems face many technical challenges, including capturing wireless signals, making custom measurements, and implementing digital signal processing algorithms. In this presentation, we demonstrate several tools that can help wireless engineers address these challenges more effectively.

The presentation uses as an example the Mode S IFF standard, which commercial aircraft use to transmit their aircraft ID, altitude, and position to air traffic controllers. These signals are captured by a Tektronix® Spectrum Analyzer, and the captured data is exported to MATLAB to be analyzed and decoded. We also show how to use a simple software radio to generate test signals when live signals are not available. Featured products include MATLAB, Communications System Toolbox, Mapping Toolbox, Parallel Computing Toolbox, and Instrument Control Toolbox.

Automating FPGA/ASIC Design Workflow with MATLAB

Richard Cagley, Toyon

With a syntactical style specifically designed for digital signal processing as well as sophisticated data generation and processing capabilities, MATLAB is the dominant language for signal processing research and development in the aerospace community. While there are various ways to initiate design entry for firmware implementation, many individuals on the cutting edge of algorithm development choose to start with MATLAB. This fact motivates the question that if MATLAB is the dominant language for advanced signal processing R&D, can it also be the entry point for firmware development? In this presentation, we argue that with its syntactical richness and advanced simulation capabilities, MATLAB is the ideal entry point for FPGA/ASIC designs when a holistic view of hardware development is considered. To demonstrate this point, we will illustrate the rapid development of a wireless physical layer waveform using MATLAB as the principal form of language entry. Specifically, having a MATLAB model as the golden reference that can be used for generation and verification of both fixed-point C code and RTL enables a tremendous degree of automation in hardware development.