Embedded Signal Processing Prof. Brian L. Evans http://www.ece.utexas.edu http://www.wncg.org http://signal.ece.utexas.edu http://www.cps.utexas.edu November 21, 2003 On My Way to Austin… Signals and Systems Pack 1987-1993 Symbolic analysis of signals and systems.
Download ReportTranscript Embedded Signal Processing Prof. Brian L. Evans http://www.ece.utexas.edu http://www.wncg.org http://signal.ece.utexas.edu http://www.cps.utexas.edu November 21, 2003 On My Way to Austin… Signals and Systems Pack 1987-1993 Symbolic analysis of signals and systems.
Embedded Signal Processing Prof. Brian L. Evans http://www.ece.utexas.edu http://www.wncg.org http://signal.ece.utexas.edu http://www.cps.utexas.edu November 21, 2003 On My Way to Austin… Signals and Systems Pack 1987-1993 Symbolic analysis of signals and systems in Mathematica By product of my PhD work On market since 1995 Ptolemy Classic Mixes models of computation 1993-1996 Untimed dataflow Process network Discrete-event Untimed dataflow synthesis Source code powers Agilent Advanced Design System 2 Embedded Signal Processing Lab Develop and Disseminate Theoretical bounds on signal/image quality Optimal and low-complexity algorithms using bounds Algorithm suites and fixed-point, real-time prototypes Analog/Digital IIR Filter Design for Implementation Butterworth and Chebyshev filters are special cases of Elliptic filters Minimum order does not always give most efficient implementation Control quality factors 3 Students & Alumni ADSL/VDSL Transceiver Design Ph.D. students: Dogu Arifler Ming Ding Ph.D. graduates: Güner Arslan (Cicada) Biao Lu (Schlumberger) Milos Milosevic (Schlumberger) Real-Time Imaging Ph.D. students: Gregory E. Allen (UT Applied Research Labs) Serene Banerjee MS students: Vishal Monga Ph.D. graduates: Thomas D. Kite (Audio Precision) Niranjan Damera-Venkata (HP Labs) MS graduates: Young Cho (UCLA) Wireless Communications Ph.D. students: Kyungtae Han Zukang Shen MS students: Ian Wong (NI Summer Intern) Ph.D. graduate: Murat Torlak (UT Dallas) MS graduates: Srikanth K. Gummadi (TI) Amey A. Deosthali (TI) Wireless Networking and Comm. Group: http://www.wncg.org Image Analysis Ph.D. graduates: Dong Wei (SBC Research) K. Clint Slatton (University of Florida) Wade C. Schwartzkopf (Integrity Applications) Center for Perceptual Systems: http://www.cps.utexas.edu 4 Senior Real-time DSP Lab Elective Lab #6: Quadrature Amplitude Modulation Transmitter an d[n] Serial/parallel converter 1 J Map to 2-D constellation Bit stream a*(t) Impulse modulator Impulse modulator bn b*(t) Pulse shaper gT(t) FIR filter Delay s(t) + Transmitted signal FIR filter Local Oscillator 90o FIR filter Pulse shaper gT(t) 5 Senior Real-time DSP Lab Elective Deliverable: V.22bis Voiceband Modem Reference Design in LabVIEW Allows Students To Explore communication performance tradeoffs vs. parameters See relationships among modem subsystems in block diagram LabVIEW DSP Integration Toolkit 2.0 for Spring 2004 Design of sinusoidal generators, filters, etc. Program in C on TI DSP processor using Code Composer Studio Test implementation with spectrum analyzers, etc. Interacts with Code Composer Studio for real-time debugging info Enables all test and measurement to be performed on desktop PC Course alumni Prethi Gopinath and Newton Petersen at NI 6 LabVIEW Interface Control Panel QAM Passband Signal Eye diagram 7 Multicarrier Modulation Divide broadband channel into narrowband subchannels No inter-symbol interference if constant subchannel gain and ideal sampling Based on fast Fourier transform (FFT) pulse -w c Standardized in ADSL/VDSL (wired) and IEEE 802.11a/g & 802.16a (wireless) wc DTFT-1 sinc w k sin w c k k magnitude channel carrier In ADSL/VDSL, each subchannel is 4.3 kHz wide and carries a QAM encoded subsymbol subchannel frequency 8 ADSL Transceiver: Data Transmission N/2 subchannels N real samples Bits 00110 S/P quadrature amplitude modulation (QAM) encoder mirror data and N-IFFT add cyclic prefix D/A + transmit filter P/S TRANSMITTER channel RECEIVER N/2 subchannels P/S QAM demod decoder invert channel = frequency domain equalizer N real samples N-FFT and remove mirrored data remove S/P cyclic prefix time domain equalizer (FIR filter) conventional ADSL equalizer structure receive filter + A/D 9 Contributions by Research Group New Time-Domain Equalizer Design Methods Maximum Bit Rate gives an upper bound Minimum Inter-Symbol Interference method (amenable to real-time, fixed-point implementation) Minimum Inter-Symbol Interference Method Reduces number of TEQ taps by a factor of ten over Minimum Mean Squared Error method for same bit rate Implemented in real-time on Motorola 56300, TI TMS320C6200 and TI TMS320C5000 DSPs http://www.ece.utexas.edu/~bevans/projects/adsl 10 Wireless Multicarrier Modulation Bits 00110 S/P quadrature amplitude modulation (QAM) encoder N-point inverse FFT add cyclic prefix P/S TRANSMITTER D/A + transmit filter multipath channel RECEIVER P/S QAM demod decoder freq. domain equalizer N-point FFT remove S/P cyclic prefix receive filter + A/D Orthogonal frequency division multiplexing (OFDM) 11 OFDM Simulation in LabVIEW IEEE 802.16a Standard Fixed broadband wireless system High speed wireless access from home or office IEEE 802.16a Simulation Physical layer communication Realistic channel models Channel estimation Authored by Alden Doyle, Kyungtae Han, Ian Wong www.ece.utexas.edu/~iwong/Research.htm 12 Possible LabVIEW Extensions Add communication system design/simulation support for Text-based algorithm design environment Drop down and “click to configure” communication building blocks Multicarrier systems and error control coding Performance visualization mechanisms for communication systems performance analysis (BER curves, eye diagrams, etc.) For quick calculations and parameter calculations Implement a text-to-VI translation tool, e.g. convert math script “x = [1:10]; y = fft(x)” to a VI implementation Improve optimization toolkit Make it easier to use Add supports for more extensive set of algorithms 13 Fixed-Point Wordlength Optimization Problem: Manual floating-to-fixed point conversion for digital hardware implementation Goal: Develop fast algorithm to optimize fixed-point wordlengths Design time grows exponentially with number of variables Time consuming Error prone Optimum wordlength Error [1/performance] Complexity Minimize hardware complexity Maximize application performance Solution: Simulation-based search Determine minimum wordlength Greedy search algorithm Complexity-and-distortion measure Wordlength(w) 14 Design Wordlength Optimization In LabVIEW Use broadband wireless access demodulator design Pick four variables and build fixed-point type Manually estimate maximum and minimum values of these variables for integer wordlength determination Optimize these variables using Greedy search algorithm with complexity-and-distortion measure Data Source OFDM Modulator Encoder Channel Estimator w3 Bit error rate tester Decoder Channel Equalizer Wireless Channel Model w2 w1 OFDM Demodulator w0 15 Design Possible LabVIEW Extensions Add fixed-point data type Build fixed-point arithmetic operations, filtering operations, etc. Estimate implementation complexity as function of input wordlengths in blocks Automatically estimate or log max and min values on arcs Implement wordlength search algorithms Max Min IWL w0 4.8 -4.5 3 W1 3.7 3.7 2 W2 0.8 -0.9 0 w2 wopt 5 dw2 wb dw1 5 w1 16