Welcome to Simulation of communication systems (DT001A) and

A project course about MATLAB with SIMULINK and Communications Blockset MATLAB = Matrix Laboratory. Tool for numerical calculation and visualization. Commonly used for simulation of the communication system physical layer, signal and image processing research, etc. SIMULINK: Toolbox in Matlab that allows graphical data-flow oriented programming.

Aim of the course To prepare the student for thesis project and work in the area of telecommunciations development and research. To give experience of performance analysis of communication systems and algorithms, at the physical layer and datalink layer. To give experience of simulation tools such as MATLAB and SIMULINK. This may include modelling and simulation of traffic sources, channel models, modulation schemes, error coding schemes, equalizers, algorithms and protocols. A real-world project is studied within an application area such as cellular communications, modems for broadband access, wireless networks, short-range communication, digital TV transmission, IP-TV or IP-telephony.

Prerequisites Computer Networks A 7.5 ECTS credits or similar Computer Engineering B, Wireless Internet access (most important!) Computer Engineering AB-level, 30 ECTS credits TCP/IP networking Mathematical statistics Programming Other helpful courses: Transform theory, 7.5 ECTS credits. Electrical engineering A, Analog electronics or Circuit theory Electrical Engineering B, Telecommunications, 7.5 ECTS credits. Electrical engineering B, Signals and systems, 7.5 ECTS credits. Markov processes/Queueing theory

Litterature Matlab and Simulink documentation will be provided electronically. Please repeat physical layer issues and datalink layer issues in basic books in Computer Networks and Wireless Internet Access.

Requirements All lectures and supervision lessons are mandatory. You are expected to devote 20 hours/week to this course, for example in L209. Quzzes (multiple choice tests): At least 70% correct answers. Lab: About 20 hours of work. Homework problem. Oral presentations. Project

Requirements on the project Review at least one research paper, and describe some standard and some existing simulation model. Simulate a communications standard, or check the simulations made in a research paper. At least modify an existing simulation model, for exampel a Simulink or Matlab demo, or build a model of your own (more difficult) Produce some plots for several parameter cases, showing for example BER, bit rate or delay as function of at least two different parameters, for example SNR, facing model, modulation scheme, etc. The simulation results should be stable (the plots smooth and not jerky), i.e simulate sufficiently long simulation time, or take the average of sufficiently large number of simulations. Draw some interesting conclusions from this.

Grading is based on Keeping deadlines. Quzzes. Showing good understanding when andwering questions from teachers and other students about your presentations. Extent of own code. Research relevance. Own new results or conclusions.

Time plan and deadlines (prel) Week Introduction lectures - Start lab: Intro to Simulink. (About 20 hours of work) - Electronic quizzes in webct - Choose a standard and en existing model to simulate Week 46 - Assignment 1 (homework problem). - Conclude lab (demonstrate to teachers) Week Present chapter 2 for class: Theory study – present a standard and review a research paper - Present chapter 3 for class: Model – present an existing simulation model Week Demonstrate chapter 1 to teachers: Introduction (goal of your project) - Demonstrate chapter 4: Modifications to an existing simulation model, or a new model that you have built. Week Demonstrate some simulation results to teachers. Week 03 - Final report and project presentations, incl chapter 5: Results, and chapter 6: Conclusions.

”IMRaD” report disposition Use MIUN template for technical reports. Abstract Table of contents. 1. Introduction 2. Theory study (describe a standard and review a research paper) 3. Existing simulation model 4. Modifications to the simulation model/own simulation model 5. Simulation results 6. Conclusions List of sources Appendix: Simulation code

Assignment 1: Theory repetition The first assignment consists of old exam problems in Computer Networks A, Wireless Internet access B and Telecommunications B. Deadline: At the supervision lesson week 45. Be prepared to present your answers on the whiteboard.

12 MATLAB MATLAB = Matrix Laboratory. Tool for numerical calculation and visualization. Commonly used for simulation of the communication system physical layer, signal and image processing research, etc.

13 Command window Workspace Command history This is how MATLAB looks like

14 More MATLAB windows Figure window M-file editor Array editor

15 How to get help in MATLAB? help functionsname Shows unformatted text doc funktionsnamn Shows HTML documentation in a browser

SIMULINK SIMULINK: Toolbox in Matlab that allows graphical data-flow oriented programming.

Repetition of some basic concepts Frequency spectrum Digitalisation, source coding Error coding Modulation Multiple-access methods Base-band model Distorsion, noise Signal-to-noise ratio Bit-error ratio Statistics

Repetition of some basic concepts

Digitalization

PCM = Pulse Code Modulation = Digital transmission of analogue signals Sampler AD-converter with seerial output DA- converter Anti aliasing- filter Interpolation filter Number exemples from PSTN = the public telephone network Hz band pass filter. Stops everything over 4000Hz sampels per sec 8 bit per sampel i.e bps per phone call 2 8 = 256 voltage levels 0 1 Microphone Loudspeaker

Aliasing

Quantization noice

Digital transmission

Distorsion

Effect of attenuation, distortion, and noise on transmitted signal.

Point-to-point communication MikrofonHögtalare Source codingSource decoding Digitalizating compression 0110 Error managementError control Bitfel Flow control ModulationDemodulation NACK ACK Layer 6 Layer 2 Layer 1 Layer 7

Digital modulation methods Binary signal ASK = Amplitude Shift Keying (AM) FSK = Frequency Shift Keying (FM) PSK = Phase Shift Keying (PSK)

8QAM example: Below you find eight symbols used for a so called 8QAM modem (QAM=Quadrature Amplitude Modulation). The symbols in the first row represent the messages 000, 001, 011 and 010 respectively (from left to right). The second row representents 100, 101, 111 and 110.

Example 2 cont.

Bit rate vs baud rate Bit rate in bit/s: Where M is the number of symbols and f s is the symbol rate in baud or symbols/s.

Bit and baud rate comparison ModulationUnits Bits /symbol Baud rate Bit Rate ASK, FSK, 2-PSK Bit1NN 4-PSK, 4-QAM Dibit2N2N 8-PSK, 8-QAM Tribit3N3N 16-QAMQuadbit4N4N 32-QAMPentabit5N5N 64-QAMHexabit6N6N 128-QAMSeptabit7N7N 256-QAMOctabit8N8N

Figure 5.14 The 4-QAM and 8-QAM constellations Q (Quadrature phase) I (Inphase) Q (Quadrature phase) I (Inphase)

Sine wave example I 5 Volt л/2 radians = 90º Complex representation

Inphase and quadrature phase signal Sine wave as reference (inphase) signal: Cosine wave as reference (inphase) signal:

Complex baseband representation C = I+jQ Amplitude: Phase: RF signal (physical bandpass signal, if a cosine is reference signal): I jQ C |C| Arg C

Last slide last lecture

Equivalent baseband signal

Figure 5.11 The 4-PSK characteristics

Figure 5.12 The 8-PSK characteristics

Figure QAM constellations

Spectrum of ASK, PSK and QAM signal

Figure 3.9 Three harmonics

Figure 3.10 Adding first three harmonics

Example: Square Wave Square wave with frequency f o Component 1: Component 5: Component 3:

Figure 3.11 Frequency spectrum comparison

Filtering the Signal Filtering is equivalent to cutting all the frequiencies outside the band of the filter High pass INPUT S 1 (f) H(f) OUTPUT S 2 (f)= H(f)*S 1 (f) Low pass INPUT S 1 (f) H(f) f OUTPUT S 2 (f)= H(f)*S 1 (f) Band pass INPUT S 1 (f) H(f) OUTPUT S 2 (f)= H(f)*S 1 (f) Types of filters –Low pass –Band pass –High pass f f

Figure 6.4 FDM (Frequency division multiplex)

Figure 6.5 FDM demultiplexing example

Figure 6.19 Time division multiplex (TDM) in the american telephone network

Multiple access = channel access Several transmitters sharing the same physical medium, for example wireless network, bus network or bus network. Based on A physical layer multiplexing scheme A data link layer MAC protocol (medium access control) that avoids collisions, etc. Examples: TDMA (time division multiple-access) based on TDM FDMA (time division multiple-access) based on FDM CDMA based on spread spectrum multiplexing CSMA (carrier sense multiple-access) based on packet switching = statistical multiplexing

Cellular telephony generations 1G: (E.g. NMT 1981) Analog, FDMA circuit switched. 2G: (E.g. GSM 1991) Digital, FDMA+TDMA, 8 timeslots, circuit switched. 2.5G: (GPRS) Packet switched = statistical multiplexing. The old circuit switched infrastructure is kept. 3G: (e.g. WCDMA) FDMA + CDMA (= spread spectrum). 4G: (E.g. 3gpp LTE) All-IP. OFDM or similar.

Spread spectrum DS-CDMA = Direct Sequence Code Division Multiple Access Chip sequencies

Figure Encoding rules

Figure CDMA multiplexer

Figure CDMA demultiplexer

Figure 9.1 Discrete Multi Tone (DMT) Essentially the same thing as OFDM Used in ADSL modems

Figure 9.2 ADSL Bandwidth division

OFDM modulation A simple example: 4 sub-carriers 8 PSK

Technical data for DAB and DVB-T

Orthogonal Frequency Division Multiplex (OFDM) Summary of advantages Can easily adapt to severe channel conditions without complex equalization Robust against narrow-band co-channel interference Robust against Intersymbol interference (ISI) and fading caused by multipath propagation High spectral efficiency Efficient implementation using FFT Low sensitivity to time synchronization errors Tuned sub-channel receiver filters are not required (unlike conventional FDM) Facilitates Single Frequency Networks, i.e. transmitter macrodiversity. Summary of disadvantages Sensitive to Doppler shift. Sensitive to frequency synchronization problems. Inefficient transmitter power consumption, due to linear power amplifier requirement.

Bit error rate (BER) = Bit error probability = Pb Packet error rate (PER) = Packet error probability for packet length N bits: Pp = 1 – (1-Pb) N

Error-correcting codes (ECC), also known as Forward-error correcting codes (FCC) A block code converts a fixed length of K data bits to a fixed length N codeword, where N > K. A convolutions code inserts redundant bits into the bit-stream. Code rate ¾ means that for every 3 information bit, totally 4 are transferred, i.e. every forth of the transferred bits is redundant.

Bit rates Gross bit rate = Transmission rate. Symbol rate = Baud rate ≤ Gross bit rate In spread spectrum: Chip rate ≥ Bit rate ≥ Symbol rate. In FEC: Net bit rate = Information rate = Useful bit rate ≤ Code rate * Gross bit rate Maximum throughput ≤ Net bit rate Goodput ≤ Throughput

Nyquist formula Gives the gross bit rate,without taking noise into consideration:  Symbol rate < Bandwidth*2  Bit rate < Bandwidth * 2log M The above can be reached for line coding (base band transmission) and so called single- sideband modulation. Howeverm in practice most digital modulation methods give:  Symbol rate = Bandwidth

Signal to noise ratios S/N= SNR = Signal-to-noise ratio. Often same thing as C/N=CNR = Carrier-to-noise ratio  SNR in dB = 10 log10 (S/N) S/I = SIR = Signal-to-interference ratio. Often the same thing as C/I=CIR = Carrier-to-interference ratio. I is the cross-talk power. CINR = C/(I+N) = Carrier-to-noise and interference ratio Eb/N0 = Bit-energy (Power in watt divided by bitrate) divided by Noise density (in Watt per Hertz) Es/N0 = Symbol-energy (Power in Watt divided by bitrate) divided by Noise density (in Watt per Hertz)

Shannon-Heartly formula Gives the channel capacity, i.e. the maximum information rate (useful bit rate) excluding bit error rate. I=B * 2log (1+C/N)

Some statistical distributions

Gaussian noise Time Voltage

Gaussian = Normal distribution Probability density funciton

Additive White Gaussian Noise (AWGN) channel White noise = wideband (unfiltered) noise with constant noise density in Watt/Hertz Pink noise = lowpass-filtered noise. Additive = linear mixing. + Signal Noise source Noisy signal

Bernoulli distribution Random sequence of independent 0:s and 1:s.

Exponential distribution Commonly used for time between phone calls and length of phone calls. Simple model for calcuclation and simulation, but does not reflect data traffic bursty nature.

More commons distributions Poisson distribution Rectangular distribution Discrete distributions, for example the distribution of a dice