Bit Error Rate in Digital Photoreceivers

Σχετικά έγγραφα
Pairs of Random Variables

Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1.

Περιεχόμενα διάλεξης

2 Composition. Invertible Mappings

Finite Field Problems: Solutions

Homework #6. A circular cylinder of radius R rotates about the long axis with angular velocity

19. ATOMS, MOLECULES AND NUCLEI HOMEWORK SOLUTIONS

Section 8.3 Trigonometric Equations

16 Electromagnetic induction

α A G C T 國立交通大學生物資訊及系統生物研究所林勇欣老師

Chapter 4 : Linear Wire Antenna

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

Homework 3 Solutions

Problem Set 3: Solutions

Potential Dividers. 46 minutes. 46 marks. Page 1 of 11

HOMEWORK#1. t E(x) = 1 λ = (b) Find the median lifetime of a randomly selected light bulb. Answer:

2/2/2018. PHY 712 Electrodynamics 9-9:50 AM MWF Olin 105

Example Sheet 3 Solutions

SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions

3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β

Analytical Expression for Hessian

b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds!

Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

Practice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1

Fractional Colorings and Zykov Products of graphs

Solution Series 9. i=1 x i and i=1 x i.

ST5224: Advanced Statistical Theory II

Areas and Lengths in Polar Coordinates

Areas and Lengths in Polar Coordinates

derivation of the Laplacian from rectangular to spherical coordinates

JMAK の式の一般化と粒子サイズ分布の計算 by T.Koyama

ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007

Math 6 SL Probability Distributions Practice Test Mark Scheme

Section 7.6 Double and Half Angle Formulas

TMA4115 Matematikk 3

HOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:

Bayesian statistics. DS GA 1002 Probability and Statistics for Data Science.

(a,b) Let s review the general definitions of trig functions first. (See back cover of your book) sin θ = b/r cos θ = a/r tan θ = b/a, a 0

1. A fully continuous 20-payment years, 30-year term life insurance of 2000 is issued to (35). You are given n A 1

Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics

Matrices and Determinants

Exercises to Statistics of Material Fatigue No. 5

How to register an account with the Hellenic Community of Sheffield.

2. Μηχανικό Μαύρο Κουτί: κύλινδρος με μια μπάλα μέσα σε αυτόν.

MathCity.org Merging man and maths

ANSWERSHEET (TOPIC = DIFFERENTIAL CALCULUS) COLLECTION #2. h 0 h h 0 h h 0 ( ) g k = g 0 + g 1 + g g 2009 =?

CE 530 Molecular Simulation

F19MC2 Solutions 9 Complex Analysis

Inverse trigonometric functions & General Solution of Trigonometric Equations

Notes on the Open Economy

Laplace s Equation in Spherical Polar Coördinates

ECON 381 SC ASSIGNMENT 2

4.6 Autoregressive Moving Average Model ARMA(1,1)

ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2

Numerical Analysis FMN011

Calculus and Differential Equations page 1 of 17 CALCULUS and DIFFERENTIAL EQUATIONS

Strain gauge and rosettes

Approximation of distance between locations on earth given by latitude and longitude

Concrete Mathematics Exercises from 30 September 2016

EE512: Error Control Coding

Space-Time Symmetries

C.S. 430 Assignment 6, Sample Solutions

Modbus basic setup notes for IO-Link AL1xxx Master Block

Calculating the propagation delay of coaxial cable

Homework 8 Model Solution Section

Statistical Inference I Locally most powerful tests

Instruction Execution Times

webpage :

DESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0.

Example of the Baum-Welch Algorithm

Solutions to Exercise Sheet 5

Appendix A. Stability of the logistic semi-discrete model.

Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013

An Inventory of Continuous Distributions

A Note on Intuitionistic Fuzzy. Equivalence Relation

Example 1: THE ELECTRIC DIPOLE

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.

Homework for 1/27 Due 2/5

CRASH COURSE IN PRECALCULUS

Other Test Constructions: Likelihood Ratio & Bayes Tests

the total number of electrons passing through the lamp.

Dynamic types, Lambda calculus machines Section and Practice Problems Apr 21 22, 2016

: Monte Carlo EM 313, Louis (1982) EM, EM Newton-Raphson, /. EM, 2 Monte Carlo EM Newton-Raphson, Monte Carlo EM, Monte Carlo EM, /. 3, Monte Carlo EM

1 String with massive end-points

[ ] [ ] ( ) 1 1 ( 1. ( x) Q2bi

ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 6/5/2006

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit

Q1a. HeavisideTheta x. Plot f, x, Pi, Pi. Simplify, n Integers

ECE 222b Applied Electromagnetics Notes Set 3a

Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in

k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +

ΕΠΙΧΕΙΡΗΣΙΑΚΗ ΑΛΛΗΛΟΓΡΑΦΙΑ ΚΑΙ ΕΠΙΚΟΙΝΩΝΙΑ ΣΤΗΝ ΑΓΓΛΙΚΗ ΓΛΩΣΣΑ

Second Order RLC Filters

2. THEORY OF EQUATIONS. PREVIOUS EAMCET Bits.

Overview. Transition Semantics. Configurations and the transition relation. Executions and computation

Uniform Convergence of Fourier Series Michael Taylor

VBA Microsoft Excel. J. Comput. Chem. Jpn., Vol. 5, No. 1, pp (2006)

Paper Reference. Paper Reference(s) 1776/04 Edexcel GCSE Modern Greek Paper 4 Writing. Thursday 21 May 2009 Afternoon Time: 1 hour 15 minutes

Transcript:

Bit Eo Rat in Digital hotocivs In th pvious slids, w saw that th photociv aks a dcision as to whth th covd wavfo is abov ( o blow ( th thshold lvl. Whn nois is psnt, a wong dcision can b ad, i.. w hav a bit o. W will now ain tchniqus fo calculating th bit o pobability and hnc th BER. Γ. Έλληνας, Διάλεξη 3-4, ελ. 9 Digital hotociv Rcovd puls tain (output voltag ntic-hall Γ. Έλληνας, Διάλεξη 3-4, ελ. 3 ag 5

Eapl of a bit o Wily Bit os a a consqunc of th nois psnt on th civd signal. Sinc th nois is ando and pobabilistic, it can b dscibd using a ando vaiabl. Γ. Έλληνας, Διάλεξη 3-4, ελ. 3 Eapl of a bit o S S Only two typs of bit can b snt in a binay syst: s and s. Ths vnts a utually clusiv, so w hav (S + (S. S is th vnt was snt S is th vnt was snt D D Only two typs of dcision can b ad: th dtctd signal is abov o blow th thshold lvl, i.. ith a o a is dtctd. Ths vnts a utually clusiv, so w hav (D + (D. D is th vnt was dtctd D is th vnt was dtctd Γ. Έλληνας, Διάλεξη 3-4, ελ. 3 ag 6

Conditional pobabilitis S S D.S D.S D.S D.S D D A total of fou utually clusiv outcos a possibl in a binay counications syst Γ. Έλληνας, Διάλεξη 3-4, ελ. 33 Conditional pobabilitis D.S D.S Th shadd gions psnt vnts that giv a bit o: D. S a is dtctd and a was snt D.S D.S D.S a is dtctd and a was snt Ths two vnts a utually clusiv, hnc: ( bit o ( D. S + ( D. S Γ. Έλληνας, Διάλεξη 3-4, ελ. 34 ag 7

obability of bit o ( D / S ( D. S ( S Bay s foula Raanging givs: ( D. S ( S ( D / S Siilaly, w hav: ( D S ( S ( D /. S Thus th bit o pobability can b wittn as: ( bit o ( S ( D / S + ( S ( D / S Γ. Έλληνας, Διάλεξη 3-4, ελ. 35 obability of bit o Th pvious foula can b usd to calculat th bit o pobability povidd: w know what th pobabilitis of snding s and s a (oftn w hav (S (S.5 and w can obtain th conditional pobabilitis (D /S and (D /S. W can obtain (D /S and (D /S if w know what th DFs associatd with cption of th bits and in th psnc of nois a. Ths pocsss can b vy accuatly appoiatd by gaussian ando vaiabls; th gaussian DF is plottd on th nt slid. Γ. Έλληνας, Διάλεξη 3-4, ελ. 36 ag 8

p Gaussian DF ( ( π p( Γ. Έλληνας, Διάλεξη 3-4, ελ. 37 Gaussian DF Th gaussian DF occus vy widly in any applications (and fo that ason is also calld th Noal distibution. On ason fo this is th cntal liit tho. This tho tlls us that if w tak th su of a lag nub of indpndnt vaiabls X, X,... X n, and if ach of ths aks a sall contibution to th su X X + X +... + X n, thn th DF of X will appoach a gaussian shap as n. Th poof is byond th scop of this cous, but th ida can b illustatd bst by an apl,.g. oll n dic and add thi valus. If this vnt is patd nough tis, you gt a gaussian distibution. www.uss.on.nt/zhcchz/java/quincun/quincun.8.htl Γ. Έλληνας, Διάλεξη 3-4, ελ. 38 ag 9

optis of th gaussian DF p( ( X ( X an: X.5 by syty is th standad dviation: whn p( is usd to dscib th pobability of dtcting a nois cunt (o voltag thn psnts th s valu of th nois cunt (o voltag. Γ. Έλληνας, Διάλεξη 3-4, ελ. 39 Obtaining pobabilitis fo th gaussian DF Whn calculating th bit o pobability lat on, w will hav to valuat pobabilitis such as: ( X p( d This pssion cannot b calculatd analytically, w ust us nuical tchniqus. W dfin: Q( k π This can b obtaind nuically and thn plottd: k y dy Γ. Έλληνας, Διάλεξη 3-4, ελ. 4 ag

ag Γ. Έλληνας, Διάλεξη 3-4, ελ. 4 Q(k Γ. Έλληνας, Διάλεξη 3-4, ελ. 4 To calculat: [ ] d X ( ( π Lt: y π Q X dy X y / ( ( Obtaining pobabilitis fo th gaussian DF

Obtaining pobabilitis fo th gaussian DF p( ( X ( X Q p ( d Γ. Έλληνας, Διάλεξη 3-4, ελ. 43 Towads BER... In th contt of ou digital photociv, w can say that output voltag v(t gnatd idiatly aft th aplifi stag in spons to th tansission of and will hav an valus of V and V fo ths two pulss. Th thshold lvl (V th will b st btwn ths two valus. Howv, nois (du.g. to thal and aplifi contibutions will b supiposd on ths an valus, and th distibutions will follow that of a gaussian DF. Hnc th civd voltags fo and hav DFs givn by p (v and p (v spctivly: Γ. Έλληνας, Διάλεξη 3-4, ελ. 44 ag

Towads BER... dtctd voltag, v p (v (D /S (D /S V V th V p (v Assu Γ. Έλληνας, Διάλεξη 3-4, ελ. 45 QUESTION W saw ali that th bit o pobability is: + ( S ( D / S ( S ( D / S If w assu that ons and zos a qually likly to b snt, thn (S (S.5 and: [ D / S ( D / ] ( S + By considing an NRZ wavfo with V, and picking a thshold idway btwn this and V, i.. V th V /, show that: Q V ( Γ. Έλληνας, Διάλεξη 3-4, ελ. 46 ag 3

Bit Eo Rat in Digital hotocivs In th pvious slids, w saw that th photociv aks an o whnv nois pushs th wavfo to th wong sid of th thshold lvl. W also saw that w could odl this pocss using th gaussian distibution. W will now finish ou tatnt by showing how BER is latd to SNR. Γ. Έλληνας, Διάλεξη 3-4, ελ. 47 Digital hotociv Bit os can b ad h; th nub dpnds on th SNR of th civd signal Rcovd puls tain (output voltag ntic-hall Γ. Έλληνας, Διάλεξη 3-4, ελ. 48 ag 4

W saw ali that th bit o pobability is: Towads BER... + ( S ( D / S ( S ( D / S If w assu that ons and zos a qually likly to b snt, thn (S (S.5 and: [ D / S ( D / ] ( S + W will consid a NRZ wavfo with V, and pick a thshold idway btwn this and V, i.. V th V /. W f to this as a unipola wavfo. Γ. Έλληνας, Διάλεξη 3-4, ελ. 49 Towads BER... ( D / S Vth V p (v p (v p v ( v π v ( D / S ( v V th p V th ( v dv Γ. Έλληνας, Διάλεξη 3-4, ελ. 5 ag 5

Using th lationship: w hav: Towads BER... ( X Q D / S ( v V ( th Vth Q Γ. Έλληνας, Διάλεξη 3-4, ελ. 5 Towads BER... ( v V ( D / S p ( v π V th V p (v p (v v V th ( D / S ( v V th p ( v dv Γ. Έλληνας, Διάλεξη 3-4, ελ. 5 ag 6

Towads BER... By syty, w hav: V th V 3V th p (v Gn aa black aa ( D / S p( v 3 V th v dv Γ. Έλληνας, Διάλεξη 3-4, ελ. 53 Towads BER... Using w hav: ( X Q ( D / S ( v 3V Q 3V th Vth Q th V Γ. Έλληνας, Διάλεξη 3-4, ελ. 54 ag 7

ag 8 Γ. Έλληνας, Διάλεξη 3-4, ελ. 55 [ ] + / ( / ( th V Q V Q S D S D Hnc: Now, b that is th s nois voltag, so: an squa nois pow Towads BER... Γ. Έλληνας, Διάλεξη 3-4, ελ. 56 Also, if ons and zos a qually likly, Hnc th SNR is: an squa signal pow [ ] V V V + V Copaing with th bit o pobability, SNR Q V Q Bit Eo obability

plot of Q function Fo plot of Q function, fo -9, nd to find Q(k -9, which givs k 6.. Γ. Έλληνας, Διάλεξη 3-4, ελ. 57 and SNR Hnc w hav fo -9 : Q SNR Fo th plot of Q(k vsus k, w hav k 6., 9 i..: SNR 6. SNR 7. In db, w hav SNR log (7. 8.6 db Γ. Έλληνας, Διάλεξη 3-4, ελ. 58 ag 9

BER vsus SNR fo unipola NRZ Bit o pobability -5-5 - - -5-5 -5 - - -5 - -5 5 5 5 SNR (db Γ. Έλληνας, Διάλεξη 3-4, ελ. 59 Coplntay o function Not that w hav usd Q(k in ths calculations; ost ttbooks ak us of th coplntay o function fc( dfind as: fc ( π It is staightfowad to show this is latd to Q(k as follows: Q( k fc u k du (MATLAB, fo apl, uss fc(, not Q( Γ. Έλληνας, Διάλεξη 3-4, ελ. 6 ag 3