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Basic Knowledge of Data Converters Agenda • • Data Converter Overview ADC/DAC Basics – – – Sampling Theory ADC Architectures • SAR • Delta-Sigma • Pipeline • Flash DAC Architectures • • • R-2R String Data Converter Specifications / Test (how to get them from DATASHEET) – DC Spec. – AC Spec. – ADC/DAC Nomenclature What is ADC Analog to Digital AMPLITUDE 7FFFFF TIME 0000000 800000 What is DAC Digital to Analog AMPLITUDE 7FFFFF 0000000 800000 TIME ADC/DAC Basic – Sampling Theory – ADC Architectures • • • • Delta-Sigma SAR Pipeline Flash – DAC Architectures • R-2R • String Basic ADC Theory • Analog signal is sampled • The sampled analog signal is compared to one or more reference voltages • The result of the comparison is converted by digital logic to a binary number. SHANNON’S information theorem NYQUIST’S Criteria Shannon: An analog signal with a Bandwidth of fa must be sampled at a rate fs>2fa in order to avoid the loss of information. The Signal Bandwidth may extend from DC to fa (Baseband Sampling) or from f1 to f2, where fa = f2-f1 (Undersampling, or Super-Nyquist). Nyquist: If fs<2fa, then a phenomenon called aliasing will occur. Aliasing is used to advantage in undersampling applications Sampling Theory Input Waveform Sampled Output Sampling Function f(t) h(t) X t1 t2 t3 t4 g(t) Unit Pulses f(t4) = t f(t1) t T f(t2) f(t3) t1 t2 t3 t4 t Fourier Transform Input Spectrum Sampling Spectrum Sampled Spectrum H(f) Nyquist region F(f) G(f) = * f1 * f fs = 1/T 2fs NYQUIST'S THEOREM: fs-f1 > f1 f f1 fs fs+f1 2fs-f1 f fs > 2 ´ f1 14-8 Oversampling Why Oversample? • • TO MOVE ALIASING FREQUENCY FURTHER FROM THE DESIRED SIGNAL. TO RELIEVE ANTIALIASING AND RECONSTRUCTION FILTER REQUIREMENTS – COST – COMPLEXITY – RESPONSE • • TO ALLOW FOR LOWER APPARANT INPUT NOISE BY FILTERING IN THE DIGITAL DOMAIN. TO ALLOW FOR LOWER APPARANT INPUT NOISE BY SPREADING THE QUANTIZING NOISE OVER A WIDER BANDWIDTH. Sampling ADC Quantization Noise SIGNAL OUTPUT RMS QUANTIZATION NOISE = q/ fs 2 12 fs Effects of oversampling on Quantization Noise Analog signal fa sampled @ fs has images (aliases) at |±Kfs ±fa|, K = 1, 2, 3, ... fa I I fs 0.5fs 1.5fs ZONE 2 ZONE 1 ZONE 3 fa I 0.5fs 2fs ZONE 4 I fs I I I I 1.5fs 2fs Effect of oversampling on filter requirement Analog filter requirement for fo = 10MHz: fS = 30MSPS AND fS = 60MSPS ANALOG LPF fCLOCK = 30MSPS dB fo IMAGE IMAGE 10 20 30 40 IMAGE 50 IMAGE 60 70 80 FREQUENCY (MHz) fCLOCK = 60MSPS dB fo ANALOG LPF IMAGE IMAGE 10 20 30 40 50 60 70 80 Undersamplinig Why Undersample? • The AC bandwidth of the “analog portion” of an ADC is usually wider than the maximum sample rate. • Nyquist says that the BANDWIDTH not the FREQUENCY of the signal must be ½ sampling rate. • You can process the spectrum at harmonics of the sample rate as well Undersampling A ZONE 1 0.5fs fs 1.5fs 2fs 2.5fs 3fs 3.5fs fs 1.5fs 2fs 2.5fs 3fs 3.5fs 2fs 2.5fs 3fs 3.5fs ZONE 2 B I 0.5fs ZONE 3 C I 0.5fs fs 1.5fs Intermediate Frequency (IF) signal at 72.5MHz (±2MHz) is aliased between DC and 5MHz fs = 10.000 MHz 7fs= 70.000 MHz dc fs 2fs 3fs 4fs 5fs 6fs 7fs 0 10 20 30 40 50 60 70 BASEBAND ALIAS: dc TO 5 MHz SIGNAL: 72.5 ± 2 MHz f s = 10.000 MSPS Anti-aliasing filter for undersampling fs - f 1 f1 f2 2fs - f2 fc DR SIGNALS OF INTEREST IMAGE 0 0.5fS Bandpass filter specifications IMAGE IMAGE fS 1.5fS 2fS STOPBAND ATTENUATION = DR TRANSITION BAND: f2 TO 2fs - f2 f1 TO fs - f1 CORNER FREQUENCIES: f1, f2 Quantization Error • Analog signals are continuous • Digital signals have discrete values • A digital word that is converted to an analog signal will always contain errors • Quantization Error or Noise is dependent on the number of bits used in the conversion Quantization Data Converters’ Architectures • ADCs – – – – Delta Sigma SAR Pipeline Flash • DAC – R-2R – String Customers Talk Architecture??? Should you be scared - NO Can you handle it - TRY Just know the key characteristics and you have just focused in on your device selection A/D Converter - SAR - Pipeline - Flash - Delta Sigma ADC Architectures: Speed, Resolution, and Latency Analogy Delta Sigma – – – – 16 to 24 bits of resolution Typically Slow 10SPS to 105kSPS Long Latency If I was a camera I would have my aperture open longer SAR – – – – 8 to 18 bits of resolution ~50kSPS to 4MSPS No latency If I was a camera I would be have fast shutter speed Pipeline – – – – 8 to 14 bits of resolution Up to over 300 MSPS Some clock cycle latency I want to be a video camera when I grow up Flash – – – – 8 to 10 bits of resolution Up to over 1 GSPS no latency I just want to be FLASH TI Analog to Digital Families 300 M Speed: Sample Rate in SPS 100 M Pipeline Advantages •Higher Speeds •Higher Bandwidth Disadvantages •Lower Resolution •Pipeline Delay/Data Latency •More power 10 M 1M Delta Sigma SAR Advantages •High Resolution •Low cost •Low Power typically •High Stability (averages and filters out noise) Disadvantages •High Latency •Low Speed typically Advantages •No Latency (happens immediately) •High Resolution and Accuracy (<=18-bits) •Typically Low Power •Easy to Use and Multiplex Disadvantages •Typically sample Rates Limited to Approximately 4 MHz 500 k 100 k 10 k Delta Sigma 1k 0 6 8 10 12 14 16 Accuracy (Resolution in bit) 18 20 24 + - S/H fS Clock An “n” bit SAR converter takes n cycles to complete a conversion. SAR and Control Logic MSB LSB D/A Converter Ref FS: Full Scale Data Out VIN ADC – Successive Approximation Register (SAR) Architecture From most to least significant bit (MSB to LSB) simple compare functions are done and, when a bit is a 1, that amount of voltage is subtracted from the input signal. SAR’s are workhorse converters… easy to use… simple to understand… but are limited in both resolution and speed. FS FS 2 TI has MANY SAR ADCs. 0 MSB LSB Successive Approximation ADC ADC – Pipeline Architecture Pipeline converters are another high speed architecture. Several lower resolution converters are put together to result in a fast conversion time. Generally lower power and lower cost than Flash converters, the main disadvantage of a Pipeline converter is that it takes as many clock cycles as there are stages to output the data resulting in latency. STAGE 1 STAGE N Sample Hold Amplifier ANALOG INPUT Sample Hold Amplifier + S SAMPLE HOLD AMPLIFIER ADC DAC REGISTER TI has many Pipeline converters! + - ADC S ADC DAC REGISTER PARALLEL DIGITAL OUTPUT Latency SARs have none….OK, just a little ADS7881 12 bits 4MSPS Snapshot Acquisition Time Conversion Time = 150ηs Aperture delay = 2ηs If it was a 12 bit pipeline with 2 bits/stage, you would need: 150 ηs Conv t Delay = 6.6MSPS X 6 clock cycle delay = 40MSPS Pipeline A/D Converter Timing and Data Latency Sample Points S4 S5 S8 S1 S9 Analog Input S2 S6 S3 S7 Track Clock Hold Internal S/H Data Latency, 6.5 clock cycles Track Hold Output Data n n-7 n+1 n-6 n+2 n-5 n+3 n-4 n+4 n-3 n+5 n-2 n+6 n-1 n+7 n Pipeline A/D Converter Signal Encoding: SAR vs. Pipeline • SAR: Serial Encoding Sample #1 MSB B2 B3 B4 B5 B6 B7 LSB B7 LSB Conversion Time • Pipeline: Parallel Encoding Sample #1 MSB B2 B3 B4 B5 B6 Conversion Time Sample #2 MSB B2 B3 B4 B5 B6 B7 LSB B3 B4 B5 B6 B7 Sample #3 MSB B2 LSB And Now for something completely different Delta Sigma’s Delta-Sigma Overview • What is a delta-sigma ADC? – A 1-bit converter that uses oversampling (can be multi-bit) – “Delta” = comparison with 1-bit DAC – “Sigma” = integration of the Delta measurement • What is the advantage of delta-sigma? – Essentially digital parts which result in low cost – High resolution • What are the disadvantages? – Limited frequency response – Most effective with continuous inputs – Latency 3 S D Converters – Functional Block Diagram Analog Input PGA Analog Modulator Advantages: • • • Minimum analog components Integrates easily with digital logic Oversampling reduces inband noise 1-bit wide Digital Filter n-bits wide Digital Output Disadvantages: • Speed limited to upper audio range Delta-Sigma A/D Converters Analog Input Delta-Sigma Modulator Digital Filter Decimator Digital Decimating Filter (usually implemented as a single unit) Digital Output Delta-Sigma A/D Signal Path You are here Analog Input Delta-Sigma Modulator Digital Filter Decimator Digital Decimating Filter (usually implemented as a single unit) Digital Output Delta-Sigma A/D Signal Path TIME DOMAIN FREQUENCY DOMAIN MAGNITUDE AMPLITUDE TIME FREQUENCY Delta-Sigma A/D Signal Path Analog Input Delta-Sigma Modulator Digital Filter Decimator Digital Decimating Filter (usually implemented as a single unit) Digital Output Delta-Sigma A/D Signal Path TIME DOMAIN Believe it or not, the sine wave is in there! FREQUENCY DOMAIN SIGNAL 1 0 Fs (drawing is approximate) QUANTIZATION NOISE Delta-Sigma A/D Signal Path TIME DOMAIN FREQUENCY DOMAIN SIGNAL 7FFFFF (+FS) 800000 (-FS) Fs QUANTIZATION NOISE Delta-Sigma A/D Signal Path Analog Input Delta-Sigma Modulator Digital Filter Decimator Digital Decimating Filter (usually implemented as a single unit) Digital Output Delta-Sigma A/D Signal Path TIME DOMAIN 7FFFFF FREQUENCY DOMAIN SIGNAL 0000000 800000 QUANTIZATION NOISE Fs Delta-Sigma A/D Signal Path Analog Input Delta-Sigma Modulator Digital Filter Decimator Digital Decimating Filter (usually implemented as a single unit) Digital Output Delta-Sigma A/D Signal Path TIME DOMAIN FREQUENCY DOMAIN QUANTIZATION ALIAS NOISE 7FFFFF SIGNAL 0000000 800000 Fd ORIGINAL Fs Delta-Sigma A/D Signal Path OUTPUT OF DECIMATING FILTER SIGNAL FROM MODULATOR 7FFFFF 0000000 7FFFFF (+FS) 800000 (-FS) 800000 DECIMATING FILTER Oversampling, digital filter, NOISE SHAPING, AND DECIMATION A fs QUANTIZATION NOISE = q / 12 q = 1 LSB Nyquist Operation ADC Oversampling + Digital Filter Kfs fs B + Decimation DIGITAL ADC DEC FILTER fs Oversampling + Noise Shaping + Digital Filter Kfs + Decimation fs fs Kfs 2 2 C SD MOD fs 2 DIGITAL FILTER REMOVED NOISE Kfs REMOVED NOISE DIGITAL DEC FILTER fs Kfs 2 2 Kfs The Delta-Sigma Modulator Sigma Delta Signal input, X1 + X3 X2 + X4 To Digital Filter - Difference Amp X5 Integrator VMax - Comparator (1-bit ADC) 1-bit DAC 4 Signal input, X 1 + X 3 X 2 - + X 4 Difference Amp X 5 1-bit DAC X1 X2 Vmax 0V +Vmax -Vmax X3 +Vmax X4 1 X5 -Vmax 0 Vmax 0V Integrator VMax Comparator (1-bit ADC) Latch Delta-Sigma Modulator To Digital Filter Averaging Filters Full-scale Delta-Sigma Modulator DC input levels 1-bit data 0V 1-bit data streams 1/2 full-scale input 1 0 1 0 1 0 1 0 Average = 0.5 1/4 full-scale input 3/4 full-scale input 1 0 0 0 1 0 0 0 1 1 1 0 1 1 1 0 Average = 0.25 Average = 0.75 The Frequency Domain Power Signal amplitude SNR = 6.02N + 1.76dB ; (for an N-bit ADC Sine wave input) Quantization Noise Average noise floor (flat) FS / 2 Frequency FS Power Oversampling by K Times Oversampling by K times SNR = 6.02N + 1.76dB ; (for an N-bit ADC Sine wave input) Same total noise, but spread over more frequencies Average noise floor k FS / 2 Frequency k FS The Digital Filter Ideal digital filter response Power Oversampling by K times SNR = 6.02N + 1.76dB + 10 log(Fs/2*BW) Noise removed by filter BW k FS / 2 Frequency k FS Noise-Shaped Spectrum Signal Amplitude Power SNR = 6.02N + 1.76dB The integrator serves as a highpass filter to the noise. The result is noise shaping k FS / 2 Frequency k FS 1st order DS Modulator CLK Vin(t) Integrator D/A Dout(t) Filtering the Shaped Noise Signal amplitude Power Digital filter response HF noise removed by the digital filter k FS / 2 Frequency k FS The 2nd Order Delta-Sigma Modulator INTEGRATOR + ∑ - INTEGRATOR 1-BIT ADC + ∑ - 1-BIT OUTPUT 1-bit DAC MODULATOR OUTPUT SPECTRAL QUANTIZATION NOISE DENSITY y x i i1 i e 2 e i1 e i2 2 f T N2( f) 4 erms 2 T sin 2 2 The Delta-Sigma Modulator Modulator noise densities 0 100 200 300 Hz 1st-order 2nd-order 3rd-order 4th-order 400 500 The Delta-Sigma Modulator Modulator noise densities 0 1 1st-order 2nd-order 3rd-order 4th-order 2 3 4 Hz 5 6 7 Sampling speed vs. ENOB SIGNAL Fd Fs QUANTIZATION NOISE ADC Topology Summary ADC Topology SAR F Conversion < 5Msps Resolution Comments Up to 18-bit Simple operation, low cost, low power. Delta-Sigma < 100ksps < 10MSPS Up to 24-bit Up to 16-18 bits Slow, moderate cost. Flash < 500Msps Up to 10-bit Fast, expensive, large power requirements. Pipeline < 200Msps Up to 16-bit Fast, expensive, large power requirements. 6 D/A Converter – R-2R – String – Current Steering TI DAC Technologies Instrumentation and Measurement Typically for Calibration Converter Resolution 20 DS Industrial Settling Time (µs) Number of Out put DACs Resistor String – Inexpensive R-2R – More accurate -Trimmed at final test Typically Voltage out MDAC’s (dig control gain/atten, Waveform gen.) High Speed Video and Communication Update rate (MSPS) Typically 1 Output but a few 2 Output Current out 16 12 Resistor String & R-2R Current Steering 8 1000 100 10 8 6 4 Settling Time- s 2 1 1/UpdateRate Setling time .05 .001 R-2R Architecture R R R R R R R R + 2R 2R 2R 2R 2R 2R 2R 2R 2R LSB MSB VR E F + small. Only 2*N resistors required - tight resistor matching required - not inherently monotonic ANALOG OUTPUT ( VOUT ) Resistor String DAC Architecture VREF R 7/8 V RE F 1 R 6/8 V RE F 0 1 R 0 5/8 V RE F 1 R 4/8 V RE F 0 1 + R 0 3/8 V RE F 1 - R 2/8 V RE F 0 1 VFB R 0 1/8 V RE F 1 R 0V VOUT 0 LSB 1 0 MSB 1 = VREF S(bi/2i) Typical Block Diagrams of a Resistor String DAC VREF VFB REF(+) DAC REGISTER RESISTOR STRING + VOUT REF(-) GND (a) VREF x2 DAC Latch Data Clock / W E Control and Interface Buffer C S (b) VOUT Current Steering DACs 2N-1 Current Sources I I I IOUT IOUT Switches determined by digital input Precision DAC Product Strategy Low Cost • Limited Accuracy • Low Cost • High Accuracy • Great AC Specifications • Small Packages • High Channel Counts • Single and Dual Supply Output Ranges • Expensive • High Accuracy • More BACK DAC Architecture Positioning 15 Current Steering typically settles to 0.1% Precision DACs (R-2R and String) to .003% Settling Time (µs) HPA07 10 5 Higher Power Consumption 0 0 1 * INL is at the 16-bit level 10 16 INL (LSB) 32 64 More BACK Data Converter Specifications Evaluating the ADC (Datasheet) Key Performance Characteristics • DC – – – – Offset error Gain error Differential linearity Integral linearity • AC – SNR – THD – SFDR • Others How Large is an LSB ? 1 LSB = N= VFULLSCALE(nom.) 2N N = Resolution of ADC 8 10 12 14 16 20 1 LSB ± 5 V input range 39.06 9.77 mV 2.44 mV 610 mV 153 V 9.53 V 1 LSB + 5 V input range 19.53 mV 4.88 mV 1.22 mV 305 V 76.3 V 4.77 V 1 LSB + 3 V input range 11.72 mV 2.93 mV 732 V 183 V 45.8 V 2.86 V V Resolution vs. Accuracy: Poor Accuracy Poor Resolution Good Accuracy Poor Resolution Poor Accuracy Good Resolution Good Accuracy Good Resolution 4 AC Specs • • • • SNR (Signal-to-Noise Ratio) – RMS value representing the ratio of the amplitude of the desired signal to noise power below one half the sampling frequency. Measure of the strength of a signal to background noise. Contributes to the overall dynamic performance of the device at higher frequencies and affects the linearity at those frequencies. In the audio world, a low signal-to-noise ratio means the device has lots of hiss and static, while a high rating means clear-sounding audio. THD (Total Harmonic Distortion) – • The ratio of the sum of the powers of all harmonic frequencies above the fundamental frequency to the power of the fundamental frequency. • THD is usually expressed in dB. ENOB (Effective Number Of Bits) • The number of bits achieved in a real system. • Is another way of specifying the SNR. • ENOB = (SNR-1.76) / 6.02 and says that the converter is equivalent to a perfect ADC of this ENOB number of bits. SFDR (Spurious Free Dynamic Range) • The headroom available in an FFT plot. • It is the distance in dB between the fundamental input and the worse spur. Fundamental Signal SFDR First Harmonic Second Harmonic Average Noise Floor DC errors 111 Actual Transfer Function 110 Ideal Transfer Function Digital Output code 101 100 011 010 001 000 Offset Error – Actual Full Scale Range Analog Input Voltage Ideal Full Scale Range Offset Error • The offset error is the difference between the nominal and actual offset points. • It is the difference in voltage between the first ideal code transition and the actual code transition of the ADC. • This error affects all codes by the same amount and can usually be compensated for by a trimming process. If trimming is not possible, this error is referred to as the zero-scale error. Gain Error – • The gain error is the difference between the ideal gain between zero and full scale on the transfer function and the actual gain after the offset error has been corrected to zero. • This error represents a difference in the slope of the actual and ideal transfer functions and as such corresponds to the same percentage error in each step. • This error can also usually be adjusted to zero by trimming. DC Specs 111 Actual Transfer Function Ideal Transfer Function 110 < 1LSB DNL Digital Output code 101 100 011 010 > 1LSB DNL 001 000 Analog Input Voltage INL < 0 INL (Integral Nonlinearity Error) - (or simply linearity error) • The deviation of the values on the actual transfer function from the ideal transfer function once the gain and offset errors have been nullified. • The summation of the differential nonlinearities from the bottom up to a particular step, determines the value of the INL at that step. • The unit for INL is LSB. DNL (Differential Nonlinearity Error) – (or simply differential linearity) • The differential nonlinearity error is the difference between an actual step width (for an ADC) or step height (for a DAC) and the ideal value of 1 LSB (Least Significant Bit). • If the DNL exceeds 1 LSB, the magnitude of the output gets smaller for an increase in the magnitude of the input. • In an ADC there is also a possibility that there can be missing codes (if DNL < -1LSB) i.e. one or more of the possible 2n binary codes are never output. Major DNL Errors ADC Missing Code 111 110 101 100 011 010 001 000 0 1 2 3 4 5 6 Input Voltage 7 LOST??? Different Datasheets list specs in different terminologies – INL in LSB, mV, %, PPM – Power in mW, V, I – Gain error/drift in %FSR, μV The Relevancy… Power (W) = Vin (V) X Ioper (A) Cheat Book LSB LSB * mV % PPM LSBX(2)[1].VrefX100 2N LSB X 100 2N LSB X 106 2N mV mV X 2N . (2)[1].Vref 100 * mV . (2)[1] Vref mV X 104 (2)[1] .Vref % % X 2N 100 % X (2)[1] .Vref * % X 104 PPM PPM X 2N 104 PPM X (2)[1] .Vref 100 PPM 104 * [1] The factor 2 in brackets is to be used for a bipolar device. ADC Offset Errors Ideal transfer characteristic Output Code 111 110 101 100 011 Actual transfer characteristic 010 001 000 0 1 2 3 4 5 6 7 Input Voltage 10 ADC Gain Errors Output Code 111 110 101 100 011 010 001 000 0 1 2 3 4 5 6 7 Input Voltage 11 ADC INL Errors 111 Output Code 110 101 100 011 010 001 000 0 1 2 3 4 5 6 7 Input Voltage 13 ADC DNL Errors Output Code 111 110 101 100 011 010 001 000 0 1 2 3 4 5 6 7 Input Voltage 12 DNL Major Errors ADC Missing Code DAC Non-monotonic 7 Output Voltage Output Code 111 110 101 100 011 010 001 000 0 1 2 3 4 5 6 Input Voltage 7 6 5 4 3 2 1 0 000 001 010 011 100 101 110 111 Input Code 12 Amplitude (dB) Dynamic Specifications Fundamental F 0 -10 -20 -30 -40 -50 -60 -70 -80 -90 -100 -110 -120 -130 Harmonics 0 1k H2 H3 H4 H5 H6 H7 H8 2k 3k 4k 5k 6k 7k 8k H9 9k 10k Frequency - Hz 14-30 Amplitude (dB) Spurious Free Dynamic Range (SFDR) Fundamental F 0 -10 -20 -30 -40 -50 -60 -70 -80 -90 -100 -110 -120 -130 SFDR 0 1k 2k 3k 4k 5k 6k 7k 8k 9k 10k Frequency / Hz 14-32 Amplitude (dB) Intermodulation Distortion, IMD 0 -10 -20 -30 -40 -50 -60 -70 -80 -90 -100 -110 -120 -130 f1 f2 - f1 0 1k f2 2f1 - f2 2k 3k 2f2 - f1 4k 5k 6k f1 + f2 7k 8k 9k 10k Frequency / Hz 14-33 Measuring Noise • RMS noise – Usually calculated from standard deviation of a series of samples – Used to calculate ENOB – Does not depend on noise type • Peak-to-peak noise – Gives “display resolution” – Estimates typically assume that the noise is Gaussian Measuring Noise Calculating RMS noise N Variance of a set of N samples: Standard deviation: Effective number of bits (if samples are ADC codes): 2 (x x ) 2 i i 0 N ENOB M log 2 2 Measuring Noise Peak-to-peak noise For Gaussian noise, > 99.9% of samples occur in the interval: ( X 3 . 3 ,X 3 . 3 ) X X Then our rule of thumb is: Peak-to-peak noise = 6.6 * RMS noise Digital Output Code Signal to Noise Ratio (SNR) 111 110 101 100 011 010 001 000 SNR = Q VSIN VN SNR(dB) = 6.02 ´ N + 1.76 N is number of bits of resolution 0.5 FS Each extra bit provides approximately 6 dB improvement in the SNR ! FS Analog Input Voltage Effective Number Of Bits (ENOB): +Q/2 Q -Q/2 ENOB = (SNR + D)(dB) - 1.76 6.02 Quantization Noise 14-29 Definition of "NOISE-FREE" code resolution Effective resolution = log2 Noise-free Code resolution = log2 Full scale range RMS noise Full scale range P-P noise P-Pnoise = 6.6 × RMS noise (most commonly used ratio) = effective resolution – 2.72 bits bits Typical output RMS NOISE in uV and effective resolution in bits First Notch of Filter and O/P Data Rate -3 dB Frequency G=1 G=4 G = 16 G = 128 10 Hz 2.62 Hz 1.7 0.5 0.36 0.36 60 Hz 15.72 Hz 8.5 2.0 0.6 0.45 250 Hz 65.5 Hz 130 25 7.5 1.7 1 kHz 262 Hz 180 40 Output Noise: 3.1 x 103 0.7 x 103 Effective Resolution: 10 Hz 2.62 Hz 21.5 21.5 19.5 16.5 60 Hz 15.72 Hz 19.5 19 19 16.5 250 Hz 65.5 Hz 15.5 15 15 14.5 1 kHz 262 Hz 10.5 11 11 10 Device (Semiconductor, Resistor) Noise Dominates at the Lower Frequencies (< 60 Hz notch) Quantization Noise Dominates at the Higher Frequencies Aperture-Jitter (Sampling Uncertainty) A VP V+ Dv V Dv DtA t The Aperture Error is less than 1 LSB, if: TA -VP Dt A 1 2n fmax In a 12-bit system with a maximum signal frequency of 20 MHz, the ApertureJitter has to be less than 3.8 ps ! Jitter Limits 130 120 0.1 ps 110 0.3 ps 100 *16 Bit 1 ps SNR(dB) 90 *14 Bit 3 ps 80 *12 Bit 70 10 ps 60 50 40 30 1 10 100 Maximum Signal Frequency (MHz) * Equivalent converter SNR 1000 Number of Input Channels – What is meant by 4 SE or 4 Diff? Multiplexer ADC – What is meant by 3x2 Diff? Multiplexer ADC Multiplexer ADC Number of Input Channels Single Ended (SE) vs Differential (Diff) • SE: – Referenced to ground – Grounds may not be the same across causing a noisier environment Ain • Diff: – Full-scale Range – Wider code steps – More accurate Ain+ Ain- ADC Interface Solutions Principle Configuration Choices Single-Ended Input + fs + fs/2 Vcm -fs/2 Input Vcm IN ADC - fs Differential Input IN + fs/2 Vcm -fs/2 IN ADC IN Vcm Requires full input swing from +fs to –fs 2x the swing compared to differential Input signal at IN typically requires a common-mode voltage for bias Input IN\ also requires a Vcm for correct dc-bias Combined Differential inputs result in full-scale input of +fs to –fs Each input only requires 0.5x the swing compared to single-ended Both inputs require a Vcm for correct dc-bias Typical SPI Interface SPI ADS8344 CH0 CS SS DCLK SCLK DOUT MISO DIN MOSI BUSY GPI CH7 43 I2C Interface — DSPs VDD ADS7828 2k CH0 CH1 2k C55XX I2C SDA CH7 SCL ADS7828 CH0 CH1 C55XX I2C SDA SCL CH7 48 Parallel—Digital Signal Processor Digital Signal Processor ADS8322 CS GPO CLK CLK R/W RD decoder CONVST A[19:0] Digital Signal Processor ADS8322 CS GPO CLK CLK R/W RD logic A[19:0] CONVST GPO GPO BUSY GPI D[15..0] D[15..0] Figure 1 D[15..0] BUSY D[15..0] logic INT Figure 2 46 Pseudo-Differential Mode ADC’s AIN(+) ADC AIN(-) +/- 200mV Maximum DAC Pseudo-Differential Mode ADC’s DAC OUTPUT AIN(+) AIN(-) Analog Output (V) Settling time of a DAC Settling Time, ts Error Band Final Value Glitch Digital Change Delay Time t Monotonicity A DAC is monotonic if its output either increases or remains constant as the digital input increases, with the result that the output will always be a single-valued function of the input. Glitch Improvement • Main Cause of Glitch – Charge in the switch causes node voltage to change temporarily – More number of switches toggling when code changes – more glitch!! V IN + a • TSMC products uses RowColumn decoding (see next slide) – 30~40 switches toggling at any code change • HPA07 products uses single decoder – maximum of two switches toggling at any time Charge Q gets split V R FB fb Rt VOUT ADC Nomenclature • • TI ADCs - TLC/TLVxxxx 0 or Blank 8-Bit 1 10-Bit 2 12-Bit 3 14-Bit 4 16-Bit 7 4½ Digit TLC: 5V TLV: 3V • HS ADCs Not Included ADS51xx ADS52xx ADS54xx ADS55xx ADS8xx THS14xx THS12xx THS10xx BB ADCs & Future - ADS1xxx Delta-Sigma ADCs (except ADS1286 SAR) ADS1xxx: 12-Bit ADS11xx: 16-Bit ADS121x: 24-Bit, Integrated ADS122x: 24-Bit, Low Power ADS123x: 24-Bit Weight ADS125x: 24-Bit Programmable ADS127x: 24-Bit Fast AC/DC ADS16xx: 16-/18-Bit Wide Bandwidth - ADS78xx/ADS8xxx SAR/Nyquist ADCs ADS78xx: 8-/10-/12-/14-/16-Bit <1MSPS ADS83xx: 16-/18-Bit <1MSPS ADS84xx: 16-/18-Bit >1MSPS ADS85xx: 12-/16-Bit +/-10V - THS10xxx/12xx, TLV12xx/15xx High-speed (<10 MSPS) All Future DAP ADCs Will Have ADS Prefix! DAC Nomenclature • TI 8-/10-/12-Bit DACs • - TLC/TLV56xx TLC: 5 V TLV: 3 V • High Speed CMOS DACs (Update Rate > 40MSPS) DAC56xx DAC9xx DAC29xx THS56xx • Delta Sigma DACs DAC1xxx: 14/16-Bit Burr-Brown and Newer TI DACs - DACx5xx String DACs (0 to +5 V) DAC55xx: 8-Bit, I2C, Unipolar DAC65xx: 10-Bit, I2C, Unipolar DAC751x: 12-Bit, SPI, Unipolar DAC754x: 12-Bit, Parallel, Bipolar DAC755x: Enhanced 12-Bit, SPI, Unipolar DAC757x: 12-bit, I2C, Unipolar DAC85xx 16-bit, Serial or Parallel, Unipolar or Bipolar - DAC76xx R-2R DACs (0 to +2.5 V & +/-2.5 V) DAC76xx: 12-/16-Bit, SPI or Parallel, Bipolar - DAC77xx R-2R High-voltage DACs (0 to +10 V & +/-10 V) DAC77xx: 12-/16-Bit, SPI or Parallel, Bipolar - DACx8xx R-2R Multiplying DACs. 2nd Source to ADI/LTC DAC78xx: 12-bit, SPI or Parallel DAC880x: 14-Bit, SPI or Parallel DAC881x: 16-Bit, SPI DAC882x: 16-Bit, Parallel - DAC883x: R2R DAC 16-Bit, SPI, Low Power, Best INL/DNL Thanks! Questions?