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p. 1 DSP-II DSP Everywhere… Applications of DSP in Audio and Digital Communications Simon Doclo Dept. Elec. Engineering, K.U.Leuven

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Presentation on theme: "p. 1 DSP-II DSP Everywhere… Applications of DSP in Audio and Digital Communications Simon Doclo Dept. Elec. Engineering, K.U.Leuven"— Presentation transcript:

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2 p. 1 DSP-II DSP Everywhere… Applications of DSP in Audio and Digital Communications Simon Doclo Dept. Elec. Engineering, K.U.Leuven

3 14/12/01 p. 2 Simon Doclo DSP Everywhere… DSP in Digital Communications 3G-systems: UMTS, CDMA Wireless systems: GSM, WLAN Modems: Cable, ADSL, VDSL Line echo cancellation Introduction Satellite communications Optical communication

4 14/12/01 p. 3 Simon Doclo DSP Everywhere… DSP in Audio Applications Introduction Hearing aids / cochlear implants Hands-free telephony Tele-conferencing Voice-controlled systems Audio effects Audio and speech coding

5 14/12/01 p. 4 Simon Doclo DSP Everywhere… Other applications Medical applications Cryptography Process control in chemical, pharmaceutical, energy plants Image and video processing … Introduction Anywhere (digital) signals are present, DSP-techniques are required!

6 14/12/01 p. 5 Simon Doclo DSP Everywhere… Overview Introduction DSP in digital communications systems: –xDSL-modems: modulation, equalisation DSP in audio applications: –Hands-free communication: echo, noise and reverberation –Basic techniques: Acoustic echo cancellation (AEC) Multi-microphone beamforming –Application: hearing aids Conclusion

7 14/12/01 p. 6 Simon Doclo DSP Everywhere… Telephone Line modems High-speed data communication: –optical, cable, wireless, telephone line Telephone Line Modems –voice-band modems : up to 56kbits/sec in 0…4kHz band –ADSL modems : up to 6Mbits/sec in 30kHz…1MHz band –VDSL modems : up to 52Mbits/sec in …10MHz band Time to download 10 Mbyte-file: ModemTime 56 Kbps voice-band modem24 minutes 128 Kbps ISDN10 minutes 6 Mbps ADSL13 seconds 52 Mbps VDSL1.5 seconds

8 14/12/01 p. 7 Simon Doclo DSP Everywhere… xDSL Modems ADSL : Asymmetric Digital Subscriber Line HDSL : High Speed Digital Subscriber Line VDSL : Very High Speed Digital Subscriber Line …-1993: ADSL spurred by interest in video-on-demand (VOD) 1995 : ADSL/VOD interest decline 1996 : ADSL technology trials prove viability : ADSL deployment, reoriented to data applications, as telcos reaction to cable operators offering high- speed internet access with cable modems 2000-… : VDSL

9 14/12/01 p. 8 Simon Doclo DSP Everywhere… xDSL Modems Analog/digital telephone network: BW 3 kHz, SNR 35 dB Shannon capacity ADSL/VDSL: higher bandwidth, lower SNR + impairments Bitrate depends on length of copper line Upstream Downstream SubscriberCentral office Copper wire vb. 300 m6.4 Mbps52 MbpsVDSL 3 km640 Kbps6 MbpsADSL LengthUpDown 12 MHz 1.1 MHz Bandwidth

10 14/12/01 p. 9 Simon Doclo DSP Everywhere… Modulation-technique : DMT (Discrete Multitone) Basic idea: –Decompose frequency into tones (FFT/IFFT) –Assign bits according to SNR per tone –ADSL spec (=ANSI standard): 256 tones, 512-point (I)FFTs carrier spacing f o = kHz, basic sampling rate 2.21 MHz (=512* kHz) –VDSL (=proposal): up to 4096 tones, same carrier spacing DMT Principles: IFFT/FFT-based modulation frequentie SNR frequentie bits/toon

11 14/12/01 p. 10 Simon Doclo DSP Everywhere… ADSL Spectrum ADSL spectrum :

12 14/12/01 p. 11 Simon Doclo DSP Everywhere… Frequency-dependent channel attenuation introduces inter- symbol interference (ISI) equalization Coupling between wires in same or adjacent binders introduces crosstalk (XT) –Near-end Xtalk (NEXT) –Far-end Xtalk (FEXT) –Other systems (e.g. HPNA) Radio Frequency Interference (RFI): e.g. AM broadcast, amateur radio Noise: e.g. impulsive noise (=high bursts of short duration) Echo: due to hybrid impedance mismatch echo cancellation Conclusion: Need advanced modulation, DSP,etc. ! Communication impairments (1) useful signal FEXTNEXT

13 14/12/01 p. 12 Simon Doclo DSP Everywhere… Communication impairments (2) ADSL channel attenuation, crosstalk, noise

14 14/12/01 p. 13 Simon Doclo DSP Everywhere… Modulation - Demodulation (1) DMT-transmission block scheme: S/PS/P FFT IFFT P/SP/S Discrete equivalent channel 4-QAM 8-QAM Bitstream (freq domain) Modulation (IFFT) Time domain signal Demodulation (FFT) Equalisation FEQ

15 14/12/01 p. 14 Simon Doclo DSP Everywhere… Modulation - Demodulation (2) Transmission: modulation is realized by means of 2N- point Inverse Discrete Fourier Transform (IFFT) ( example N=4 ) Receiver: demodulation with inverse operation, i.e. FFT real

16 14/12/01 p. 15 Simon Doclo DSP Everywhere… The Magic Prefix Trick (1) Additional feature : before transmission, a prefix is added to each time-domain symbol, i.e. the last samples are copied and put up front :

17 14/12/01 p. 16 Simon Doclo DSP Everywhere… The Magic Prefix Trick (2) Prefix insertion : in the receiver, the samples corresponding to the prefix are removed (=unused) : S/PS/P FFT FEQ IFFT P/SP/S Discrete equivalent channel

18 14/12/01 p. 17 Simon Doclo DSP Everywhere… The Magic Prefix Trick (3) if channel impulse response has length L (= L non-zero taps) and ( is prefix length), then all transient effects between symbols are confined to the prefix period : Tx-sideRx-side Tone 3 Tone 2 Tone 1 Tone 0 Tone 3 Tone 2 Tone 1 Tone 0 PrefixFrom IFFTGuardbandTo FFT * ch(t) r(t)s(t) Channel

19 14/12/01 p. 18 Simon Doclo DSP Everywhere… The Magic Prefix Trick (4) Magic trick fails if, resulting in –inter-symbol-interference (ISI) = interference from previous symbol(s) (same carrier) –inter-carrier interference (ICI) = interference from other carriers In the receiver, after removing the samples corresponding to the prefix, the i-th tone is observed, multiplied by a factor H(i.f o ), i.e. the channel response for frequency f=i.f o Prefix trick is based on a linear convolution (filtering by channel impulse response) being turned into a circular convolution, which corresponds to component-wise multiplication in frequency domain easy equalization !

20 14/12/01 p. 19 Simon Doclo DSP Everywhere… Overview Introduction DSP in digital communications systems: –xDSL-modems: modulation, equalisation DSP in audio applications: –Hands-free communication: echo, noise and reverberation –Basic techniques: Acoustic echo cancellation (AEC) Multi-microphone beamforming –Application: hearing aids Conclusion

21 14/12/01 p. 20 Simon Doclo DSP Everywhere… Hands-free communication Recorded microphone signals are corrupted by: Far-end echoes acoustic echo cancellation Acoustic background noise noise suppression Room reverberation dereverberation Application: hands-free telephony, hearing aids, voice control

22 14/12/01 p. 21 Simon Doclo DSP Everywhere… Signal model: some maths… Multi-microphone signal enhancement algorithms: –Extract clean speech/audio signal from microphone recordings –Exploit spatial and frequency diversity between speech and noise Microphone signals (m=1…M): Output signal: compute filters g[k] : –echo cancellation: –noise reduction/dereverberation: g m [k] cancels noise components g m [k] focuses on speech s[k] unknown known (=loud- speaker signal)

23 14/12/01 p. 22 Simon Doclo DSP Everywhere… Overview Introduction DSP in digital communications systems: –xDSL-modems: modulation, equalisation DSP in audio applications: –Hands-free communication: echo, noise and reverberation –Basic techniques: Acoustic echo cancellation (AEC) Multi-microphone beamforming –Application: hearing aids Conclusion

24 14/12/01 p. 23 Simon Doclo DSP Everywhere… Acoustic echo cancellation (AEC) Suppress acoustic and line echo: –to guarantee normal conversation conditions : users do not like to hear a delayed and filtered version of their own voice –to prevent the closed-loop system from becoming unstable if amplification is too high

25 14/12/01 p. 24 Simon Doclo DSP Everywhere… Propagation of sound waves in an acoustic environment results in –signal attenuation –spectral distortion The attenuation and distortion can be modeled quite well as a linear filtering operation Non-linear distortion mainly stems from the loudspeakers. Its effect is typically of second order, therefore (often) not taken into account The linear filter h[k] modeling the acoustic path between loudspeaker and microphone is represented by the acoustic impulse response Room Acoustics

26 14/12/01 p. 25 Simon Doclo DSP Everywhere… –direct path impulse and early reflections, which depend on the geometry of the room Acoustic Impulse Response (1) –dead time Different parts: –an exponentially decaying tail called reverberation, coming from multiple reflections –For typical applications the impulse reponse is between 100 and 400 ms long several 100 to kHz memory requirement for circular buffers in DSP –Because people move around in the recording room, the acoustic impulse response is highly time-varying

27 14/12/01 p. 26 Simon Doclo DSP Everywhere… Acoustic Impulse Response (2) ESAT speech laboratory : T ms Paleis voor Schone Kunsten : T ms Original speech signal :

28 14/12/01 p. 27 Simon Doclo DSP Everywhere… Acoustic Impulse Response : FIR or IIR ? If the acoustic impulse response is modeled as –an FIR filter many hundreds to several thousands of filter taps are required –an IIR filter filter order can be reduced, but still several hundreds of filter coefficients are required (=bad model for acoustic impulse response) –Remark: IIR-filters good model for classical filters (LP,HP,BP,BS) hence FIR models are typically used in practice –as they are guaranteed to be stable –as adaptive filtering techniques are called for: FIR adaptive filters are easier than IIR adaptive filters

29 14/12/01 p. 28 Simon Doclo DSP Everywhere… AEC based on Adaptive Filtering Goal: Identify acoustic impulse response h[k] and subtract filtered loudspeaker signal from microphone signal Thanks to the adaptivity –time-varying acoustics can be tracked –AEC is self-learning –performance superior to performance of conventional techniques

30 14/12/01 p. 29 Simon Doclo DSP Everywhere… Adaptive Filtering Algorithms Algorithm: 2 steps –Filter loudspeaker signal error signal indicates how close this signal is to recorded microphone signal –Update filter: update depends on error signal error signaldesired signal filtered signal

31 14/12/01 p. 30 Simon Doclo DSP Everywhere… Normalized Least Mean Square (NLMS) with L is the adaptive filter length, is the adaptation stepsize, is a regularization parameter and k is the discrete-time index Data filtering Filter update Circular data buffer Filter coefficients

32 14/12/01 p. 31 Simon Doclo DSP Everywhere… Control Algorithm AEC is more than just an adaptive filter : –adaptive filter is supplemented with control software, which mainly controls the adaptation speed (e.g. no adaptation during double-talk) –In practice echo suppression is limited to 30 dB due to time-variance, non-linearities, finite filterlength postprocessing (e.g. center-clipping)

33 14/12/01 p. 32 Simon Doclo DSP Everywhere… Real-time DSP Implementation (1) AEC-implementation on DSP (lab equipment): 50 MHz : data acquisition (ADC/DAC) 50 MHz : acoustic echo cancellation (AEC) AECADC/DAC

34 14/12/01 p. 33 Simon Doclo DSP Everywhere… Real-time DSP Implementation (2) Adaptive filtering part : several algorithms can be selected –NLMS : time-domain algorithm –PB-FDAF : frequency-domain algorithm (better performance) Control software –double-talk detection –non-linear postprocessing algorithm Variable sampling rate –Common sampling rates for speech applications: 8 kHz, 16 kHz –for audio applications: kHz, 44.1 kHz, 48 kHz Echo paths up to 325 ms can be modeled and tracked with the FDAF based on LMS at 8 kHz sampling frequency and 16 ms delay

35 14/12/01 p. 34 Simon Doclo DSP Everywhere… Real-time DSP Implementation (3) Execution times for the most important blocks of the DSP code were measured : N=768 FFT-size=128 f s =8000 Hz block 64 samples = 8 ms

36 14/12/01 p. 35 Simon Doclo DSP Everywhere… Demo Output AEC Near-end signal Output AEC Double-talk without Detection Local speaker Far-end signal

37 14/12/01 p. 36 Simon Doclo DSP Everywhere… Overview Introduction DSP in digital communications systems: –xDSL-modems: modulation, equalisation DSP in audio applications: –Hands-free communication: echo, noise and reverberation –Basic techniques: Acoustic echo cancellation (AEC) Multi-microphone beamforming –Application: hearing aids Conclusion

38 14/12/01 p. 37 Simon Doclo DSP Everywhere… Beamforming basics Background/history: antenna array design for RADAR Array elements are combined electronically such that: –array can be steered towards specific direction higher directivity –beam shaping is possible Beamforming for hands-free communication : –focus beam on speech source(s) speech enhancement and dereverberation –put spatial nulls in direction of noise sources noise reduction Classification: –fixed beamforming: data-independent fixed filters g m [k] e.g. delay-and-sum, weighted-sum, filter-and-sum –adaptive beamforming: data-dependent adaptive filters g m [k] e.g. LCMV-beamformer, Generalized Sidelobe Canceller

39 14/12/01 p. 38 Simon Doclo DSP Everywhere… Microphone signals are delayed and summed together array can be virtually steered to angle Angular selectivity is obtained, based on constructive ( = ) and destructive ( ) interference Uniform delay-and-sum beamforming implies –Uniform array equal inter-microphone distance –Uniformly distributed delays Delay-and-sum beamforming (1)

40 14/12/01 p. 39 Simon Doclo DSP Everywhere… Spatial directivity pattern H(, ) for uniform DS-beamformer H(, ) has sinc-like shape and is frequency-dependent Delay-and-sum beamforming (2) M=5 microphones d=3 cm inter-microphone distance =60 steering angle f s =16 kHz sampling frequency

41 14/12/01 p. 40 Simon Doclo DSP Everywhere… For an ambiguity, called spatial aliasing, occurs. This is analogous to time-domain aliasing where now the spatial sampling (=d) is too large. Delay-and-sum beamforming (3) M=5, =60, f s =16 kHz, d=8 cm Spatial aliasing

42 14/12/01 p. 41 Simon Doclo DSP Everywhere… Better directivity patterns than DS-beamformer are obtained with weighted-sum and filter-and-sum beamformers –e.g. Frequency-independent directivity pattern Filter-and-sum beamformer M=8 Logarithmic array L=50 =90 f s =8 kHz

43 14/12/01 p. 42 Simon Doclo DSP Everywhere… Adaptive filter-and-sum structure: –Minimize noise output power, while maintaining a chosen frequency response in look direction (and/or other linear constraints) –LCMV = Linearly Constrained Minimum Variance minimize variance of output z[k] in order to avoid desired signal to be distorted or cancelled out, J linear constraints are added Adaptive beamforming

44 14/12/01 p. 43 Simon Doclo DSP Everywhere… Generalized Sidelobe Canceller (1) GSC consists of three parts: –Fixed (delay-and-sum) beamformer, in order to achieve spatial alignment of speech source speech reference –Blocking matrix, placing spatial nulls in the direction of the speech source noise references –Multi-channel adaptive filter with delay Postproc

45 14/12/01 p. 44 Simon Doclo DSP Everywhere… Blocking matrix C a : –creating maximum M-1 independent noise references by placing spatial nulls in look-direction –different possibilities: e.g. Griffiths-Jim, Walsh broadside Generalized Sidelobe Canceller (2) Problems of GSC: –impossible to reduce noise from look-direction –reverberation effects cause signal leakage in noise reference adaptive filter is only updated when no speech is present !

46 14/12/01 p. 45 Simon Doclo DSP Everywhere… Overview Introduction DSP in digital communications systems: –xDSL-modems: modulation, equalisation DSP in audio applications: –Hands-free communication: echo, noise and reverberation –Basic techniques: Acoustic echo cancellation (AEC) Multi-microphone beamforming –Application: hearing aids Conclusion

47 14/12/01 p. 46 Simon Doclo DSP Everywhere… Application: Hearing Aids (1) Hearing problems are very common nowadays Most of the users are dissatisfied with the performance of their hearing aid in noisy environments (cocktail party effect) increase speech intelligibility by reducing background noise Traditional hearing aids: –one microphone, analog, limited signal processing –amplification of all incoming sound without distinction between different sound sources Enabling technologies: –microphone miniaturisation integrate multiple microphones into one hearing aid –micro-electronics: size ASIC < 10 mm 2, low power consumption –advanced DSP techniques (noise reduction, feedback suppression)

48 14/12/01 p. 47 Simon Doclo DSP Everywhere… Improvement of speech intelligibility by reduction of background noise BTE hearing aid with 2 (or more) closely-spaced microphones GSC in switched mode: Beamfomer : weights can be adapted during speech Noise suppression (ANC) : only adaptation during noise Speech detection : determine when speech is present Application: Hearing Aids (2)

49 14/12/01 p. 48 Simon Doclo DSP Everywhere… Conclusion DSP-techniques can be found in many every- day products: –audio applications: CD, MiniDisc, hands-free telephony –communications: GSM, modems, WLAN –medical applications: hearing aids, cochlear implants Implementation differences: –sampling rate, memory requirements, complexity Basic techniques: –filters, filterbanks, FFT/IFFT frequency filtering –adaptive filters track changing systems –multi-sensor systems spatial filtering


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