DSP-CIS Chapter-3: Acoustic Modem Project Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven

Slides:



Advertisements
Similar presentations
| Page Angelo Farina UNIPR | All Rights Reserved | Confidential Digital sound processing Convolution Digital Filters FFT.
Advertisements

On the Relation Between Time-Domain Equalizers and Per-Tone Equalizers for DMT-Based Systems Koen Vanbleu, Geert Ysebaert, Gert Cuypers, Marc Moonen Katholieke.
© UNIVERSITY of NEW HAMPSHIRE INTEROPERABILITY LABORATORY VDSL MCM Simulation Tim Clark VDSL Consortium Tim Clark VDSL Consortium.
a By Yasir Ateeq. Table of Contents INTRODUCTION TASKS OF TRANSMITTER PACKET FORMAT PREAMBLE SCRAMBLER CONVOLUTIONAL ENCODER PUNCTURER INTERLEAVER.
Module-3 : Transmission Lecture-7 (11/5/00)
DSP-CIS Chapter-3: Acoustic Modem Project Marc Moonen Dept. E.E./ESAT, KU Leuven
Comparison of different MIMO-OFDM signal detectors for LTE
Chapter 8: The Discrete Fourier Transform
Digital Signal Processing for Communications and Information Systems (DSP-CIS) Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven
IERG 4100 Wireless Communications
P. 1 DSP Case Study ADSL Modems Geert Leus Fac. EEMCS, TUDelft
Wireless communication channel
1 Chapter 8 The Discrete Fourier Transform 2 Introduction  In Chapters 2 and 3 we discussed the representation of sequences and LTI systems in terms.
ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING(OFDM)
DSP-CIS Chapter 10: Cosine-Modulated Filter Banks & Special Topics
CHAPTER 8 DSP Algorithm Implementation Wang Weilian School of Information Science and Technology Yunnan University.
Digital Signal Processing for Communications and Information Systems (DSP-CIS) Marc Moonen Dept. E.E./ESAT, KU Leuven
4/5/00 p. 1 Postacademic Course on Telecommunications Module-3 Transmission Marc Moonen Lecture-6 Adaptive Equalization K.U.Leuven/ESAT-SISTA Module-3.
Transforms. 5*sin (2  4t) Amplitude = 5 Frequency = 4 Hz seconds A sine wave.
Digital Signal Processing II Lecture 9: Filter Banks - Special Topics Marc Moonen Dept. E.E./ESAT, K.U.Leuven
Digital Signal Processing – Chapter 10
Orthogonal Frequency Division Multiplexing - OFDM
QPSK Acoustic Software Radio Orr Srour & Naftali Zon Under the supervision of Ami Wiesel.
OFDM Presented by Md. Imdadul Islam.
Signals and Systems Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin EE 382C-9 Embedded Software Systems.
IV. Orthogonal Frequency Division Multiplexing (OFDM)
DSP2 Project ADSL Equalization Students: Dung Nguyen Quoc- Master Student Tudor Tesu- Erasmus Student Supervisor Jan Vangorp.
OFDM Each sub-carrier is modulated at a very low symbol rate, making the symbols much longer than the channel impulse response. Discrete Fourier transform.
Zhongguo Liu_Biomedical Engineering_Shandong Univ. Chapter 8 The Discrete Fourier Transform Zhongguo Liu Biomedical Engineering School of Control.
Digital Signal Processing Chapter 3 Discrete transforms.
Chapter 2 Signals & Systems Review
Chapter 5 Finite-Length Discrete Transform
Submission doc.: IEEE /1088r0 September 2015 Daewon Lee, NewracomSlide 1 LTF Design for Uplink MU-MIMO Date: Authors:
11/5/00 p. 1 Postacademic Course on Telecommunications Module-3 Transmission Marc Moonen Lecture-8 Multi-tone Modulation K.U.Leuven/ESAT-SISTA Module-3.
Dan Ellis 1 ELEN E4810: Digital Signal Processing Topic 3: Fourier domain 1.The Fourier domain 2.Discrete-Time Fourier Transform (DTFT) 3.Discrete.
7- 1 Chapter 7: Fourier Analysis Fourier analysis = Series + Transform ◎ Fourier Series -- A periodic (T) function f(x) can be written as the sum of sines.
EE445S Real-Time Digital Signal Processing Lab Spring 2014 Lecture 16 Quadrature Amplitude Modulation (QAM) Receiver Prof. Brian L. Evans Dept. of Electrical.
Dept. E.E./ESAT-STADIUS, KU Leuven
OFDM Based WLAN System Song Ziqi Zhang Zhuo.
DSP-CIS Part-IV : Filter Banks & Subband Systems Chapter-12 : Frequency Domain Filtering Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven
Fire Tom Wada Professor, Information Engineering, Univ. of the Ryukyus Chief Scientist at Magna Design Net, Inc
DSP-CIS Chapter-3: Acoustic Modem Project Marc Moonen Dept. E.E./ESAT, KU Leuven
Automatic Equalization for Live Venue Sound Systems Damien Dooley, Final Year ECE Progress To Date, Monday 21 st January 2008.
Linear filtering based on the DFT
Digital Signal Processing for Communications and Information Systems (DSP-CIS) Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven
PAPR Reduction Method for OFDM Systems without Side Information
DTFT continue (c.f. Shenoi, 2006)  We have introduced DTFT and showed some of its properties. We will investigate them in more detail by showing the associated.
Professor A G Constantinides 1 Discrete Fourier Transforms Consider finite duration signal Its z-tranform is Evaluate at points on z-plane as We can evaluate.
Lecture 6-7: Discrete Channel partitioning Aliazam Abbasfar.
Digital Signal Processing for Communications and Information Systems (DSP-CIS) Marc Moonen Dept. E.E./ESAT, K.U.Leuven
Topics 1 Specific topics to be covered are: Discrete-time signals Z-transforms Sampling and reconstruction Aliasing and anti-aliasing filters Sampled-data.
Single carrier  Multicarrier  OFDM Single Carrier - ISI, Receiver complexity  ISI, Bit rate limitation Multi-carrier - Negligible ISI, Approximately.
Bitrate Maximizing Time-Domain Equalizer Design for DMT-based Systems Koen Vanbleu Promotor: Marc Moonen Coauthors: Geert Ysebaert, Gert Cuypers, Katleen.
DSP-CIS Part-III : Optimal & Adaptive Filters Chapter-9 : Kalman Filters Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven
Learning from the Past, Looking to the Future James R. (Jim) Beaty, PhD - NASA Langley Research Center Vehicle Analysis Branch, Systems Analysis & Concepts.
Introduction to OFDM and Cyclic prefix
EE345S Real-Time Digital Signal Processing Lab Fall 2006 Lecture 17 Fast Fourier Transform Prof. Brian L. Evans Dept. of Electrical and Computer Engineering.
بسم الله الرحمن الرحيم Digital Signal Processing Lecture 14 FFT-Radix-2 Decimation in Frequency And Radix -4 Algorithm University of Khartoum Department.
DSP-CIS Part-I / Chapter-3: Acoustic Modem Project Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven
Digital Image Processing Lecture 8: Fourier Transform Prof. Charlene Tsai.
DIGITAL SIGNAL PROCESSING ELECTRONICS
Advanced Wireless Networks
Orthogonal Frequency Division Multiplexing ...
Klaus Witrisal Signal Processing and Speech Communication Lab
EXPLOITING SYMMETRY IN TIME-DOMAIN EQUALIZERS
Channel Estimation in OFDM Systems
Lecture 17 DFT: Discrete Fourier Transform
DSP-CIS Part-I / Chapter-2 : Signals & Systems Review
Channel Estimation in OFDM Systems
EXPLOITING SYMMETRY IN TIME-DOMAIN EQUALIZERS
Presentation transcript:

DSP-CIS Chapter-3: Acoustic Modem Project Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 2 Chapter-3: Acoustic Modem Project Introduction Overview & Target Work Plan Week-1 Week-2: Channel modeling & evaluation Week 3-4: OFDM modulation Week 5-6 Week 7-8

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 3 –Digital communication over an acoustic channel (from loudspeaker to microphone) –FFT/IFFT-based modulation format : OFDM (as in ADSL/VDSL, WiFi, DAB, DVB…) –Channel estimation, equalization, etc… Digital Picture (OUT) Introduction/Overview D-to-A A-to-D +filtering +amplif. +filtering +… Tx Rx Digital Picture (IN) Transmitter Receiver

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 4 Digital communications over an acoustic channel: D-to-A A-to-D +filtering +amplif. +filtering +… Discrete-time transmit signal (sampling rate Fs, e.g. 10kHz) Discrete-time receiver signal (sampling rate Fs, e.g. 10kHz) Tx Rx Introduction

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 5 Digital communications over an acoustic channel: D-to-A A-to-D +filtering +amplif. +filtering +… Discrete-time transmit signal (sampling rate Fs, e.g. 10kHz) Discrete-time receiver signal (sampling rate Fs, e.g. 10kHz) Tx Rx This will be the easy part… Introduction

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 6 Digital communications over an acoustic channel: D-to-A A-to-D +filtering +amplif. +filtering +… Discrete-time transmit signal (sampling rate Fs, e.g. 10kHz) Discrete-time receiver signal (sampling rate Fs, e.g. 10kHz) Tx Rx …straightforwardly realized (in Matlab/Simulink with `Real-Time Workshop’, see below) means we do not have to deal with hardware issues, components, etc. Introduction

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 7 Digital communications over an acoustic channel: D-to-A A-to-D +filtering +amplif. +filtering +… Discrete-time transmit signal (sampling rate Fs, e.g. 10kHz) Discrete-time receiver signal (sampling rate Fs, e.g. 10kHz) Tx Rx …and will be modeled by a linear discrete-time transfer function (see below) H(z) Introduction

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 8 Digital communications over an acoustic channel: D-to-A A-to-D +filtering +amplif. +filtering +… Discrete-time transmit signal (sampling rate Fs, e.g. 10kHz) Discrete-time receiver signal (sampling rate Fs, e.g. 10kHz) Tx Rx This is the interesting part… (where we will spend most of the time) Introduction

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 9 Will use OFDM as a modulation format -OFDM/DMT is used in ADSL/VDSL, WiFi, DAB, DVB … -OFDM heavily relies on DSP functionalities (FFT/IFFT, …) Introduction

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 10 D-to-A A-to-D Tx Rx Target: Design efficient OFDM based modem (Tx/Rx) for transmission over acoustic channel Specifications: Data rate (e.g. 1kbits/sec), bit error rate (e.g. 0.5%), channel tracking speed, synchronisation, … Introduction

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 11 Work Plan 8 Weeks: –Week 0: Introduction Matlab/Simulink –Week 1: Audio playback, recording and analysis –Week 2: Acoustic channel measurement & modeling *deliverable* –Week 3-4: OFDM transmitter/receiver design *deliverable* –Week 5-6: OFDM over acoustic channel *deliverable* –Week 7-8: OFDM with adaptive equalization *deliverable*

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 12 Week 0 / Introduction to Matlab & Simulink Matlab tutorial provided.. Self-test = exercise 6 (IF ‘failure’,THEN ‘brush up your Matlab skills!’) CRUCIAL PREREQUISITE

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 13 Week 1 / Audio playback, recording and analysis Will provide basic Simulink scheme… (`Real-Time Workshop’) ✪ Time-frequency analysis of recorded signals

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 14 Transmission channel consist of –Tx `front end’: filtering/amplification/Digital-to-Analog conv. –Loudspeaker (ps: cheap loudspeakers mostly have a non-linear characteristic  ) –Acoustic channel –Microphone –Rx `front end’: filtering/Analog-to-Digital conv. D-to-A A-to-D +filtering +amplif. +filtering +… Discrete-time transmit signal (sampling rate Fs, e.g. 10kHz) Discrete-time receiver signal (sampling rate Fs, e.g. 10kHz) Tx Rx Week 2 / Channel Modeling & Evaluation

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 15 – first there is a dead time – then come the direct path impulse and some early reflections, which depend on the geometry of the room – finally there is an exponentially decaying tail called reverberation, corresponding to multiple reflections on walls, objects,... Acoustic channel (`room acoustics’): Acoustic path between loudspeaker and microphone is represented by the acoustic impulse response (which can be recorded/measured) Week 2 / Channel Modeling & Evaluation

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 16 Complete transmission channel will be modeled by a discrete-time (FIR `finite impulse response’ ) transfer function –Pragmatic & good-enough approximation –Model order L depends on sampling rate (e.g. L=100…1000…) Week 2 / Channel Modeling & Evaluation D-to-A A-to-D +filtering +amplif. +filtering +… Tx Rx H(z) PS: will use shorthand notation here, i.e. h k, x k, y k, instead of h[k], x[k], y[k]

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 17 When a discrete-time (Tx) signal x k is sent over a channel…..then channel output signal (=Rx input signal) y k is Week 2 / Channel Modeling & Evaluation =`convolution’

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 18 Can now run parameter estimation experiment: 1.Transmit `well-chosen’ signal x k 2.Record corresponding signal y k D-to-A A-to-D +filtering +amplif. +filtering +… Tx Rx Week 2 / Channel Modeling & Evaluation H(z) xkxk ykyk

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p Least squares estimation (i.e. one line of Matlab code ) Week 2 / Channel Modeling & Evaluation Carl Friedrich Gauss (1777 – 1855)

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 20 Week 2 / Channel Modeling & Evaluation Estimated transmission channel can then be analysed… Frequency response Information theoretic capacity ps: noise spectrum? Claude Shannon

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 21 Week 3-4 / OFDM modulation DMT – Discrete Multitone Modulation OFDM – Orthogonal Frequency Division Multiplexing Basic idea is to (QAM-)modulate (many) different carriers with low-rate bit streams. The modulated carriers are summed and then transmitted. A high-rate bit stream is thus carried by dividing it into hundreds of low-rate streams. Modulation/demodulation is performed by FFT/IFFT (see below) Now 14 pages of (simple) maths/theory…

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 22 OFDM Modulation Consider the modulation of a complex exponential carrier (with period N) by a `symbol sequence’ (see p.27) defined as (i.e. “1 symbol per N samples of the carrier”) PS: remember that modulation of sines and cosines is similar/related to modulation of complex exponentials (see also p.26, 2 nd ‘PS’) 1/14 x carrier symbol sequence

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 23 OFDM Modulation This corresponds to… 2/14 x carrier symbol sequence

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 24 OFDM Modulation Now consider the modulation of N such complex exponential carriers by `symbol sequences’ defined as 3/14 x x x … + x …

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 25 OFDM Modulation This corresponds to…..and so can be realized by means of an N-point `Inverse Discrete Fourier Transform’ (IDFT) !!! 4/14

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 26 OFDM Modulation PS: Note that modulates a DC signal (hence often set to zero) PS: To ensure time-domain signal is real-valued, have to choose PS: The IDFT matrix is a cool matrix: –For any chosen dimension N, an IDFT matrix can be constructed as given on the previous slide. –Its inverse is the DFT matrix (symbol `F’). DFT and IDFT matrices are unitary (up to a scalar), i.e. –The structure of the IDFT matrix allows for a cheap (complexity N.logN instead of N.N) algorithm to compute the matrix-vector product on the previous slide (=IFFT =inverse fast Fourier transform) 5/14

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 27 OFDM Modulation So this will be the basic modulation operation at the Tx : –The X’s are (QAM-symbols) defined by the input bit stream –The time-domain signal segments are obtained by IDFT/IFFT and then transmitted over the channel, one after the other. At the Rx, demodulation is done with an inverse operation (i.e. DFT/FFT=fast Fourier transform, see also p.33). 6/14 Real(X) Imag(X) Example: ‘16-QAM’

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 28 OFDM Modulation Sounds simple, but forgot one thing: channel H(z) !! OFDM has an ingenious way of dealing with the channel effect, namely through the insertion of a so-called `cyclic prefix’ at the Tx : If the channel is FIR with order L (see p.16), then per segment, instead of transmitting N samples, N+L sampes are transmitted (assuming L<<N), where the last L samples are copied and put up front… NL 7/14

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 29 OFDM Modulation At the Rx, throw away L samples corresponding to cyclic prefix, keep the other N samples, which correspond to This is equivalent to … 8/14 prefix N N+L

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 30 OFDM Modulation The resulting matrix (call it `H’) is an NxN `circulant matrix’ =every row is the previous row up to a ‘cyclic shift’ 9/14 N N (*)

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 31 OFDM Modulation PS: Cyclic prefix converts a (linear) convolution (see p.29) into a so-called ‘circular convolution’ (see p.30) Circulant matrices are cool matrices… A weird property (proof by Matlab!) is that when a circulant matrix H is pre-/post-multiplied by the DFT/IDFT matrix, a diagonal matrix is always obtained: Hence, a circulant matrix can always be written as (=eigenvalue decomposition! ) 10/14

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 32 OFDM Modulation Combine previous formulas, to obtain… 11/14

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 33 In other words… This means that after removing the prefix part and performing a DFT in the Rx, the obtained samples Y are equal to the transmitted symbols X, up to (scalar) channel attenuations H n (!!) OFDM Modulation 12/14

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 34 PS: It can be shown (check first column of ) that H n is the channel frequency response evaluated at the n-th carrier ! (p.32 then represents ‘frequency domain version’ of circular convolution, i.e. ‘component-wise multiplication in the frequency domain’) `Channel equalization’ may then be performed after the DFT (=in the frequency domain), by component-wise division (divide by H n for carrier-n). This is referred to as `1-tap FEQ’ (Freq.-domain EQualization) OFDM Modulation 13/14

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 35 OFDM Modulation Conclusion: DMT-modulation with cyclic prefix leads to a simple (trivial) channel equalization problem (!!) 14/14 S/PS/P FFT FEQ IFFT P/SP/S 0 Discrete equivalent channel CP insertionCP removal

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 36 Week 3-4 Target Week 3-4: –Study/understand OFDM scheme Surf around, use IEEE Xplore, Wikipedia, etc. –Simulate basic OFDM Transceiver in Matlab First without channel dispersion & without noise, then with noise, then with channel (model from Week-2) –Extend OFDM Tx/Rx with mechanism for channel estimation and/or equalizer (FEQ) initialization/updating based on transmitted training symbols. –Optional : Extend OFDM Tx/Rx with `bit-loading‘ =Carriers with a high SNR transmit more bits/sec

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 37 D-to-A A-to-D Tx Rx Week 5-6 / 7-8 Target Week 5-6: –OFDM over acoustic channel, with basic Simulink (Real- time Workshop) scheme (Week-1). –OFDM over acoustic channel, with decision-directed adaptive equalization (see Part IV) Target Week 7-8: etc…

DSP-CIS / Chapter-3: Acoustic Modem Project / Version p. 38 BE THERE !! Runs over 8 weeks (time budget = 60hrs) Each week –1 PC/Matlab session (supervised, 2.5hrs) –2 ‘Homework’ sesions (unsupervised, 2*2.5hrs) Deliverables after week 2, 4, 6, 8 Grading: based on deliverables, evaluated during sessions –3/5pts for ‘basic’ exercises (=mostly code needed in future sessions) –2/5pts for 'optional' exercises TAs: (English+Italian) (English+Dutch+WestFlemish) (English+Persian) (English+Persian) PS: groups of 2 Important !