Audio ADC-DACsPrimer.ppt

《Audio ADC-DACsPrimer.ppt》由会员分享，可在线阅读，更多相关《Audio ADC-DACsPrimer.ppt（35页珍藏版）》请在麦多课文档分享上搜索。

1、Audio ADC/DACs Primer,David Hossack,2,Goals,Learn about a real world signal processing application There are hundreds of these in this room Also on DSP Board Learn about commercial considerations AskAgenda Start at actual A/D conversion Motivate sigma-delta modulator Motivate interpolation and decim

2、ation filters Example filtersNo equations simple overviewAsk questions,3,Audio Codec on DSK,physically large package by todays standards,4,Analog/Digital Signal Conversion,Converting two things: Continuous Time Discrete Time Sampling Sample rate samples/s or “Hz” eg 44.1kHz or 48kHz Need clock for d

3、iscrete time Concern on clock jitter at interface between discrete-to-continuous Continuous Value Discrete Value Quantization Number of levels or number of bits eg 16bit or 24bitThese conversions can happen separately Eg Switched capacitor DAC Digital (discrete time, discrete value) - analog, discre

4、te time Continuous time, but still sampled - analog, continuous timeNot necessarily a one-to-one transformation between input samples and output samples,5,Typical Specs for Audio Converters,SNR measure of additive noise 90-120dB “A-weighted” Bandwidth 20-20kHz THD measure of errors at harmonics of i

5、nput nonlinearity 80-110dBThese are “AC” Specs“Traditional” converter specs not appropriate Absolute accuracy Integral non-linearity Differential non-linearity Conversion Time,6,What does 100dB mean?,“CD quality” N= 16 bits = approx 6N + 2 = 98dB With assumptions regarding the signal and error pdfs

6、Flat weighting, full bandwidth 1 part in 100000 0.001%Component matching on silicon 1% easy, with care : 0.1% 12 bits usually requires calibration or signal processing Need to be careful to determine how errors manifest For audio: Absolute accuracy is not important Linearity fairly important Noise v

7、ery importantHard to design audio converter using only component matching Sigma-Delta Modulation is a signal processing method to solve this Introduces its own problems Oversampling Out of Band Noise Non-linear system that is hard to fully analyze,Errors Specs: Offset Gain Linearity Noise,7,Sigma De

8、lta Modulation,Method for obtaining high resolution signal conversion without requiring high component matching Quantizes input to small number of levels Signal detail is preserved and obtaining by filteringRequires signal processing Requires oversampling, requires sample rate conversion filters ADC

9、 decimation (downsampling with filtering) DAC interpolation (upsampling with filtering)Economics limited adoption until approx 1990 Moores law allowed the DSP implementation to be cost effectiveIn engineering, the “rules” and constraints are always changing Implementations have changed significantly

10、 over the years,8,Almost all audio converters use Sigma Delta Modulation,Delta Sigma Sigma-Delta Other applications of Sigma-Delta Modulator Based Converters: Communications Cell Phones Quantizer Memoryless Non-Linear Function Loop Filter Quantization decisions affect future quantization decisions H

11、as effect of making the quantizer behave more linearly Oversampling 128x typical 48kHz x 128 = 6.144MHzSigmaDelta Modulator Loop Loop Filter Coarse quantizer Quantization error are made to appear at high frequencies Desired signal is at low frequencies,9,One bit vs Multi-bit,In the one-bit D/A conve

12、rter, clock jitter in the over sampling clock translates directly into D/A errors - causing gross errors, increasing noise and reducing the sound quality.,In a multibit sigma-delta made up of multiple two-level D/A converters, the D/A output looks more like an analog signal, making it less sensitive

13、 to jitter and easier to filter.,10,Linear Signal Processing Model of SDM,Replace quantiser by a linear gain What gain value for two level quantizerNoise Transfer Function (NTF) The shape of the quantization noise Most of the energy is at high frequenciesSignal Transfer Function (STF) The transfer f

14、unction from the input to the putput Can be flat (delay or no delay)See books, Matlab SDM Toolbox,11,Sigma-Delta DAC,Two Level DAC No matching problems Errors are gain, offsetHorrible out of band noise Non-linearities due to inter symbol interference and slew rate limitingMultilevel DACImplementatio

15、ns Switched Capacitor Continuous amplitude, discrete time filter Current Source,12,Multi Level DAC,13,SDM DAC Stages,Digital Interpolation 2x Interpolator Upsample by 2 Halfband (FIR) Allpass based structure (IIR) 2x Interpolator Upsample by 2 Halfband (FIR) Allpass based structure (IIR) CIC Interpo

16、lator Often Linear Interpolator Sinc2 Also need CIC compensation filterDigital Sigma Delta Modulator Digital Dynamic Element Matching Also designed using sigma-delta techniques Analog DAC,128x,1x 2x,2x 4x,4x 128x, 17 levels, 16 of 2 level,14,SDM ADC Stages,Analog Sigma Delta Modulator 2-17 Levels (1

17、-16 decision thresholds) Digital Decimation CIC Down Sample by 32 Sinc4 2x Decimator Down Sample by 2 Halfband (FIR) Allpass based structure (IIR) 2x Decimator Down Sample by 2 Halfband (FIR) Allpass based structure (IIR) Also need CIC compensation filter,128x,128x 4x,4x 2x,2x 1x,15,CIC Filter,Recur

18、sive Filter Structure yet FIR Pole / Zero Cancellation Need to use modulo arithmetic Efficient for Interpolation and Decimation Very good transfer function for large rate changes Interpolator images of signals near dc are suppressed Decimator frequencies that will alias to near DC suppressed Very si

19、mple implementation,Graphic from wikipedia,16,Many diagrams taken from this paper:,17,18,19,20,Component Responses Continuous Coefficients,FIR1,FIR2,Sinc2,21,Digital Filter Implementation,Use CIC filters at higher sample rates Cost efficient structure for implementing restricted set of FIR filters U

20、se FIR/IIR Filters at lower sample rates Exploit structural symmetries Eg Half band FIR interpolator uses input samples directly Eg Half-band or parallel all-pass filters Restricted responses Compensation required for CIC filters CIC often implemented flat FIR/IIR usually implemented by a simple DSP

21、 engine Fixed program hardwired in logic Single multiplier or multiplier equivalent Eg Canonic Signed Digit / Signed Power of Two “multiplierless” Multiple channels implemented by single DSP engine Cost/Power important not on digital process Eg 0.35u or 0.18u rather than say 65nm or 45nm for analog

22、reasons,22,23,24,25,Signal Processing Design and Optimization,Oversampling Rate for Analog Converter Number of levels for Analog Converter Filter architecture Number of Stages Type (CIC/FIR/IIR) of stage Limit Memory Requirement Limit Coefficient Wordlength or number of CSD/SPT terms Affects filter

23、response 16 bit typical Limit Data Wordlength requirement Affects SNR, quantization effects 20-24 bit typical No floating point!,26,Signed Power of Two Coefficients,Digitally “easy” coefficients 0 +1, -1 +1/2, -1/2 +1/4, -1/4 Sums of these Eg +1/2 1/16 + 1/128Compare with Booth encoding used in mult

24、ipliers Only need a fixed set of coefficients Less general opportunity to optimize,27,28,A very simple DSP,One FIR tap calculated per clock cycle - Already have higher clock rate available,Twos complement or SPT,24 bit Twos complement,24 bit Twos complement,24 bit Twos complement,29,Component Respon

25、ses Continuous Coefficients,FIR1,FIR2,Sinc2,30,Full Response with Continuous Coefficients,31,Full Response with SPT Coefficients,32,33,Gentler Frequency Response Requires higher sampling rate,34,Summary,Audio ADC and DAC is a rich example of real world signal processingSystem / Architectural Level Design Use digital technology to overcome weaknesses in analogFilter Architectural Design CIC vs FIR vs IIRFilter Optimization Structure Word lengths of coefficients and data,35,Presented By: David Hossack,Analog Devices, Inc. 804 Woburn Street Wilmington MA ,