S Transmission Methods in Telecommunication Systems (5 cr) Tutorial 4/2007 (Lectures 6 and 7)

Similar documents
Digital Modulation Schemes

QUESTION BANK SUBJECT: DIGITAL COMMUNICATION (15EC61)

Lecture 8 Fiber Optical Communication Lecture 8, Slide 1

Objectives. Presentation Outline. Digital Modulation Revision

Solution of ECE 342 Test 3 S12

Channel. Muhammad Ali Jinnah University, Islamabad Campus, Pakistan. Multi-Path Fading. Dr. Noor M Khan EE, MAJU

Lecture 3 Concepts for the Data Communications and Computer Interconnection

Computer Networks - Xarxes de Computadors

BSc (Hons) Computer Science with Network Security. Examinations for Semester 1

Multi-Path Fading Channel

Objectives. Presentation Outline. Digital Modulation Lecture 03

Signal Encoding Techniques

Level 6 Graduate Diploma in Engineering Communication systems

Problem Sheets: Communication Systems

Contents. 7.1 Line Coding. Dr. Ali Muqaibel [Principles of Digital Transmission ]

EXAMINATION FOR THE DEGREE OF B.E. and M.E. Semester

Year : TYEJ Sub: Digital Communication (17535) Assignment No. 1. Introduction of Digital Communication. Question Exam Marks

Chapter 5: Modulation Techniques. Abdullah Al-Meshal

QUESTION BANK (VI SEM ECE) (DIGITAL COMMUNICATION)

Muhammad Ali Jinnah University, Islamabad Campus, Pakistan. Fading Channel. Base Station

Wireless Communication Systems Laboratory Lab#1: An introduction to basic digital baseband communication through MATLAB simulation Objective

ECE 476/ECE 501C/CS Wireless Communication Systems Winter Lecture 6: Fading

UNIT I Source Coding Systems

QUESTION BANK EC 1351 DIGITAL COMMUNICATION YEAR / SEM : III / VI UNIT I- PULSE MODULATION PART-A (2 Marks) 1. What is the purpose of sample and hold

ECE 476/ECE 501C/CS Wireless Communication Systems Winter Lecture 6: Fading

Introduction: Presence or absence of inherent error detection properties.

WIRELESS COMMUNICATIONS PRELIMINARIES

Narrow- and wideband channels

Mobile Radio Propagation: Small-Scale Fading and Multi-path

ECE 476/ECE 501C/CS Wireless Communication Systems Winter Lecture 6: Fading

Digital Communications over Fading Channel s

Lecture 3: Wireless Physical Layer: Modulation Techniques. Mythili Vutukuru CS 653 Spring 2014 Jan 13, Monday

BSc (Hons) Computer Science with Network Security, BEng (Hons) Electronic Engineering. Cohorts: BCNS/17A/FT & BEE/16B/FT

Basic Concepts in Data Transmission

Chapter 3 Digital Transmission Fundamentals

Lab 3.0. Pulse Shaping and Rayleigh Channel. Faculty of Information Engineering & Technology. The Communications Department

Noise and Interference Limited Systems

Lecture 17 Components Principles of Error Control Borivoje Nikolic March 16, 2004.

Physical Layer: Modulation, FEC. Wireless Networks: Guevara Noubir. S2001, COM3525 Wireless Networks Lecture 3, 1

ELT Receiver Architectures and Signal Processing Fall Mandatory homework exercises

TSTE17 System Design, CDIO. General project hints. Behavioral Model. General project hints, cont. Lecture 5. Required documents Modulation, cont.

Lecture 10 Performance of Communication System: Bit Error Rate (BER) EE4900/EE6720 Digital Communications

CDMA Mobile Radio Networks

Selected answers * Problem set 6

EXAMINATION FOR THE DEGREE OF B.E. Semester 1 June COMMUNICATIONS IV (ELEC ENG 4035)

CT-516 Advanced Digital Communications

Downloaded from 1

Data Communication. Chapter 3 Data Transmission

Exploring QAM using LabView Simulation *

Columbia University. Principles of Communication Systems ELEN E3701. Spring Semester May Final Examination

END-OF-YEAR EXAMINATIONS ELEC321 Communication Systems (D2) Tuesday, 22 November 2005, 9:20 a.m. Three hours plus 10 minutes reading time.

Course 2: Channels 1 1

Line Coding for Digital Communication

Digital Transmission (Line Coding) EE4367 Telecom. Switching & Transmission. Pulse Transmission

Digital Communication System

Multipath can be described in two domains: time and frequency

BSc (Hons) Computer Science with Network Security BEng (Hons) Electronic Engineering

Performance Evaluation of BPSK modulation Based Spectrum Sensing over Wireless Fading Channels in Cognitive Radio

Channel Characteristics and Impairments

Mobile & Wireless Networking. Lecture 2: Wireless Transmission (2/2)

Communication Theory

UNIT TEST I Digital Communication

COMPUTER COMMUNICATION AND NETWORKS ENCODING TECHNIQUES

EE390 Final Exam Fall Term 2002 Friday, December 13, 2002

MODULATION AND MULTIPLE ACCESS TECHNIQUES

Written Exam Channel Modeling for Wireless Communications - ETIN10

CS441 Mobile & Wireless Computing Communication Basics

Exercises for chapter 2

Digital Signal Processing PW1 Signals, Correlation functions and Spectra

Communication Channels

Wireless Physical Layer Concepts: Part II

EENG473 Mobile Communications Module 3 : Week # (12) Mobile Radio Propagation: Small-Scale Path Loss

Bit Error Rate Performance Evaluation of Various Modulation Techniques with Forward Error Correction Coding of WiMAX

ECE 630: Statistical Communication Theory

EE5713 : Advanced Digital Communications

Systems for Audio and Video Broadcasting (part 2 of 2)

Lecture 2 Physical Layer - Data Transmission

Digital Communication Systems Third year communications Midterm exam (15 points)

Broadcast and distribution networks

EE3723 : Digital Communications

Chapter 2 Channel Equalization

EEE482F: Problem Set 1

Revision of Lecture 3

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING QUESTION BANK. Subject Name: Digital Communication Techniques

Narrow- and wideband channels

Digital data (a sequence of binary bits) can be transmitted by various pule waveforms.

UNIVERSITY OF SOUTHAMPTON

Multi-carrier Modulation and OFDM

Digital Communication System

Outline / Wireless Networks and Applications Lecture 3: Physical Layer Signals, Modulation, Multiplexing. Cartoon View 1 A Wave of Energy

Lecture 13. Introduction to OFDM

Chapter 8. Digital Links

TSEK02: Radio Electronics Lecture 8: RX Nonlinearity Issues, Demodulation. Ted Johansson, EKS, ISY

DSRC using OFDM for roadside-vehicle communication systems

Chapter 4 Digital Transmission 4.1

RF Basics 15/11/2013

Principles of Baseband Digital Data Transmission

KINGS DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING DIGITAL COMMUNICATION TECHNIQUES YEAR/SEM: III / VI BRANCH : ECE PULSE MODULATION

Study on the next generation ITS radio communication in Japan

Chapter 4 Radio Communication Basics

Transcription:

S-7.1140 Transmission Methods in Telecommunication Systems (5 cr) Tutorial 4/007 (Lectures 6 and 7) 1

1. Line Codes / Johtokoodit Sketch beneath each other line codes Manchester, Differential Manchester and AMI when the bit train 1101000101 is transmitted. A: See L6, S7-8 1 1 0 1 0 0 0 1 0 1 Remarks: At the start of the Differential Manchester or AMI pulse train can be inverse and so the pulse train is different as above sketched. In the AMI pulse train the '1' pulse can have no transition to zero during the '1' bit. It's also possible that the pulse and the rest time above are vice versa.

. Abbreviations and terms / Lyhenteitä ja käsitteitä Explain briefly what do the following abbreviations and terms mean: a) ISI b) Matched filter a) See lecture 6 notes, slide 9: ISI = Intersymbol interference [pulssien välinen keskinäisvaikutus], in the ideal case the previous and the following pulses doesn't affect to the amplitude value of the pulse issued at the sampling time. b) See lecture 6 notes, slide 1: Matched filter [sovitettu suodatin] is needed in the receiver when the SNR value is desired to have maximum value. In the ideal case the impulse response of matched filter is reverse in the time domain than received pulse has. Because of the convolution in the time domain maximum correlation is then achieved. 3

3. Assume that noise has spectrum density of N 0 = 10-10 W/Hz and receiver s bandwidth is W = 00 khz and impedance level is Z 0 = 50 Ω. Calculate a) the (average) noise power P N at the receiver and b) the probability that noise voltage exceeds +00 mv. See L6, S11-1 10 W 5 a) Noise power PN = N0 df = 00 khz 10 = 4 10 W = 40 μw Hz W b) Noise s RMS voltage = standard deviation σ is URMS = σ = PN Z0 = 40 μw 50 Ω 44,7 mv m = mean value = 0 V, k σ = 00 mv -> k 4,5 To get the desired probability, we have to use Q-function and it s curves (on the next page). So the probability p = Q(k) 3,6 10 6 m λ 1 Q( k) e d π k m+ kσ λ = X σ m λ 4

Q-function Q(k) 5

4. Signal-to-noise ratio (SNR, k, κ) A DVB-S receiver has BER = 10 - without channel coding. When interleaving, Reed Solomon and Convolution codes are used BER = 10-10. Modulation method is QPSK (4-PSK) which has the 1 following proberty: BER = Q( SNR ) Calculate by using Q-function diagram how much SNR seems to be improved when channel coding is used. See lecture 6 slide 38 a) Without coding: ( ) ( ) BER = Q SNR = 10 = Q k 1 1 1 ( ) SNR = k and SNR ( db) = 10 lg SNR db 1 1 1 1 b) With channel coding: 10 ( ) ( ) BER = Q SNR = 10 = Q k So the improvement is ( ) SNR = k and SNR ( db) = 10 lg SNR db ( ) ( ) SNR db SNR db db 1 6

Q-function Q(k) 7

4. Signal-to-noise ratio (SNR, k, κ) A DVB-S receiver has BER = 10 - without channel coding. When interleaving, Reed Solomon and Convolution codes are used BER = 10-10. Modulation method is QPSK (4-PSK) which has the 1 following proberty: BER = Q( SNR ) Calculate by using Q-function diagram how much SNR seems to be improved when channel coding is used. See lecture 6 slide 38 a) Without coding: ( ) ( ) BER = Q SNR = 10 = Q k 1 1 1 ( ) SNR = k,07 = 4, 8 and SNR ( db) = 10 lg SNR 6,3 db 1 1 1 1 b) With channel coding: 10 ( ) ( ) BER = Q SNR = 10 = Q k So the improvement is ( ) SNR = k 6,3 = 39,7 and SNR ( db) = 10 lg SNR 16 db ( ) ( ) SNR db SNR1 db 9,7 db 8

5. A NRZ-signal (Non Return to Zero) / NRZ-signaali Calculate by giving formulas the power spectrum (density) of a NRZ-signal {0 V,1 V} when the bits 0 and 1 have the same probability. 1/ See L6, S15 Because of the probabilities for the bits '0' and '1' are the same, we can conclude that the random signal has DC-value = <v(t)> = 0,5 V. Now we can divide the random signal into the two parts: vi( t) = va( t) + vb( t ) = 05, V + vb( t) and vb ( t ) = { 05,, + 05, } = the random signal. Average value and autocorrelation: <v(t)> = R( ± ) = 05, R( ± ) = 05, v v ( ) When the random signal is vb t, the autocorrelation function is b τ R ( τ) = σ tria where D is the duration of a bit. And v D b R 0 = σ = P = ± 0, 5 = 0, 5 v ( ) ( ) 9

5. A NRZ-signal (Non Return to Zero) / NRZ-signaali Calculate by giving formulas the power spectrum (density) of a NRZ-signal {0 V,1 V} when the bits 0 and 1 have the same probability. / So the autocorrelation function for the NRZ-signal is τ R v ( τ ) = 05, tria + 05, D Thus the power spectrum density is ( ) = ( τ) = 05 ( ) + 05 δ( ) Gv f F R v, D sinc fd, f 10

6. Transferring a file in an AWGN channel / Tiedoston siirto kohinaisessa kanavassa 1/3 A file which size is 1,4 MB (about 11,74 Mbits transferred in an AWGN channel which has the attenuation of 16 db. The power of the transmitter is 30 dbm. The noise has 1-sided power spectrum 0 density N0 = 410 W / Hz in the receiver. The modulation system sends two bits (= 1 symbol) at the same time and the symbol error probability is E rx, where E rx is the average energy of a Ps = Q N0 9 symbol. How long it takes to transfer the file when P s 10 is needed? See L6, S0 1 6 The channel attenuation is A 16 1 10, S = db AS =. The transmitted power is PRX = 30 dbm = 1W. PTX So the received average power is PRX =. AS Rb Because of two bits are sent at the same time, the symbol rate is R S =, where is the bit rate. R b 11

6. Transferring a file in an AWGN channel / Tiedoston siirto kohinaisessa kanavassa /3 A file which size is 1,4 MB (about 11,74 Mbits transferred in an AWGN channel which has the attenuation of 16 db. The power of the transmitter is 30 dbm. The noise has 1-sided power spectrum 0 density N0 = 410 W / Hz in the receiver. The modulation system sends two bits (= 1 symbol) at the same time and the symbol error probability is E rx, where E rx is the average energy of a Ps = Q N0 9 symbol. How long it takes to transfer the file when P s 10 is needed? Because of E N RX (see Q-function figure): The average energy for a received symbol is Thus 9 ( 60) 10 Q, ERX = 6, 0 = SNR= 36 ERX = 36N N 0 0 P P 36N0 = R = 348, 9 kbit/ s AR TX TX b S b 18NA 0 S 0 E P T P PTX A R RX RX = RX S = = RS S b 1

6. Transferring a file in an AWGN channel / Tiedoston siirto kohinaisessa kanavassa 3/3 A file which size is 1,4 MB (about 11,74 Mbits transferred in an AWGN channel which has the attenuation of 16 db. The power of the transmitter is 30 dbm. The noise has 1-sided power spectrum 0 density N0 = 410 W / Hz in the receiver. The modulation system sends two bits (= 1 symbol) at the same time and the symbol error probability is E rx, where E rx is the average energy of a Ps = Q N0 9 symbol. How long it takes to transfer the file when P s 10 is needed? The time needed for transmission is T 6, bit 11 744 10 = 33, 7 s 3 bit 348, 9 10 s 13

7. 8-PSK, 16-QAM and noise / 8-PSK, 16-QAM ja kohina 1/ a) See lecture 6 notes and slide 38. Let A = 1 and 8-PSK is used. Calculate the symbol error rate of 8-PSK when a white Gaussian noise having the voltage rms-value 97,7 dbμv is added to the signal. b) See lecture 6 notes and slide 39. Let a = 1 and BER (Bit Error Rate or Ratio) = 10-6. Calculate by giving formulas the maximum allowed rms-value for white Gaussian noise and give SNR (Signalto-Noise Ratio) in db's when 16-QAM is considered. See L6, S38 a) To find out probability Q(k) = p when SNR = κ = k is known and when k > 3, k e Qk ( ) A π 1 π pε = Q sin Q sin 97,7 k π σ M = 6 0 8 10 10 5 1 Q( 5) e 6,35 10 5 π 7 14

7. 8-PSK, 16-QAM and noise / 8-PSK, 16-QAM ja kohina / a) See lecture 6 notes and slide 38. Let A = 1 and 8-PSK is used. Calculate the symbol error rate of 8-PSK when a white Gaussian noise having the voltage rms-value 97,7 dbμv is added to the signal. b) See lecture 6 notes and slide 39. Let a = 1 and BER (Bit Error Rate or Ratio) = 10-6. Calculate by giving formulas the maximum allowed rms-value for white Gaussian noise and give SNR (Signalto-Noise Ratio) in db's when 16-QAM is considered. b) The bit error rate (ratio) is 3 E 3 a 6 pε b = Q = Q = 10 4 10N0 4 σ So 6 ( ) κ ( ) Q SNR = 1,33 10 SNR 4,7 = SNR,1 10lg,1 13,4 db a a 1 = κ σ = = 13 mv σ κ 4,7 Please use Q-function figure here to get SNR! 15

8. HDB-3 and NRZ coding / HDB3- ja NRZ-koodaus a) HDB-3 coding is used for the bit train 011000000011. Sketch the RZ-pulse train. 1/ b) A NRZ-coded base band signal is transferred in a cable, which attenuation is 0 db/km. In a receiver the level of the white Gaussian noise is 150 fw. The error probability in the receiver is 10-8. Calculate the maximum length of a cable when the transmitted power to the cable is 16 dbm. a) See L6, S7-8, HDB-3 is derived from AMI 0 1 1 0 0 0 0 0 0 0 1 1 When four (4) zeros are going to send consecutively [peräkkäin], last zero is coded using a violation pulse (same direction as an earlier one pulse has). Violation pulses are added to AMI code because of the synchronization in a receiver is easier. If you think for example that there are 500 sequential zeros the receiver can lost the synchronization when AMI is used. AMI is used in USA in PSTN systems, HDB-3 in Europe. 16

8. HDB-3 and NRZ coding / HDB3- ja NRZ-koodaus a) HDB-3 coding is used for the bit train 011000000011. Sketch the RZ-pulse train. / b) A NRZ-coded base band signal is transferred in a cable, which attenuation is 0 db/km. In a receiver the level of the white Gaussian noise is 150 fw. The error probability in the receiver is 10-8. Calculate the maximum length of a cable when the transmitted power to the cable is 16 dbm. See L6, S15 8 b) Let p = 10. Thus (from the Q function figure) k = SNR = κ 5,5. So the SNR = κ 30,5 and 4,54 pw PR = SR = κ NR 4,54 pw 10lg dbm 83, 4 dbm 1 mw db PS PR 16 + 83,4 PS = PR + l 0 l = km km 4,97 km 5 km km 0 db 0 17

9. Block Codes / Lohkokoodit A block code consists of the following codes: 10011, 11101, 01110, 00000. a) How many errors can be detected/corrected by this code? b) Is this a linear code? a) See L7, S11-1 dmin = 3 l = dmin 1= t = l/ = 1 d min = the minimum number of bits that are different in code words, Hamming distance l = the number of errors that can be detected at reception (but not corrected) t = the integer part of calculation l/, the number of errors that can be corrected. b) This is a linear code, because two conditions are satisfied: - It includes the all-zero vector - The sum of any two code vectors produces another vector in the code 18