Design and Performance of Rate Compatible-SCCC Alexandre Graell i Amat †‡, Guido Montorsi ‡, Francesca Vatta* † Universitat Pompeu Fabra. Barcelona, Spain.

Slides:



Advertisements
Similar presentations
TWO STEP EQUATIONS 1. SOLVE FOR X 2. DO THE ADDITION STEP FIRST
Advertisements

You have been given a mission and a code. Use the code to complete the mission and you will save the world from obliteration…
Using Matrices in Real Life
© Negnevitsky, Pearson Education, Lecture 12 Hybrid intelligent systems: Evolutionary neural networks and fuzzy evolutionary systems Introduction.
Advanced Piloting Cruise Plot.
1 Vorlesung Informatik 2 Algorithmen und Datenstrukturen (Parallel Algorithms) Robin Pomplun.
Chapter 1 The Study of Body Function Image PowerPoint
1 Copyright © 2013 Elsevier Inc. All rights reserved. Chapter 1 Embedded Computing.
Copyright © 2011, Elsevier Inc. All rights reserved. Chapter 5 Author: Julia Richards and R. Scott Hawley.
1 Copyright © 2013 Elsevier Inc. All rights reserved. Appendix 01.
1 Copyright © 2010, Elsevier Inc. All rights Reserved Fig 2.1 Chapter 2.
By D. Fisher Geometric Transformations. Reflection, Rotation, or Translation 1.
Business Transaction Management Software for Application Coordination 1 Business Processes and Coordination.
and 6.855J Cycle Canceling Algorithm. 2 A minimum cost flow problem , $4 20, $1 20, $2 25, $2 25, $5 20, $6 30, $
Jeopardy Q 1 Q 6 Q 11 Q 16 Q 21 Q 2 Q 7 Q 12 Q 17 Q 22 Q 3 Q 8 Q 13
Jeopardy Q 1 Q 6 Q 11 Q 16 Q 21 Q 2 Q 7 Q 12 Q 17 Q 22 Q 3 Q 8 Q 13
Title Subtitle.
My Alphabet Book abcdefghijklm nopqrstuvwxyz.
0 - 0.
DIVIDING INTEGERS 1. IF THE SIGNS ARE THE SAME THE ANSWER IS POSITIVE 2. IF THE SIGNS ARE DIFFERENT THE ANSWER IS NEGATIVE.
SUBTRACTING INTEGERS 1. CHANGE THE SUBTRACTION SIGN TO ADDITION
MULT. INTEGERS 1. IF THE SIGNS ARE THE SAME THE ANSWER IS POSITIVE 2. IF THE SIGNS ARE DIFFERENT THE ANSWER IS NEGATIVE.
FACTORING ax2 + bx + c Think “unfoil” Work down, Show all steps.
Addition Facts
Year 6 mental test 5 second questions
Year 6 mental test 10 second questions
2010 fotografiert von Jürgen Roßberg © Fr 1 Sa 2 So 3 Mo 4 Di 5 Mi 6 Do 7 Fr 8 Sa 9 So 10 Mo 11 Di 12 Mi 13 Do 14 Fr 15 Sa 16 So 17 Mo 18 Di 19.
ZMQS ZMQS
Richmond House, Liverpool (1) 26 th January 2004.
REVIEW: Arthropod ID. 1. Name the subphylum. 2. Name the subphylum. 3. Name the order.
BT Wholesale October Creating your own telephone network WHOLESALE CALLS LINE ASSOCIATED.
ABC Technology Project
Chapter 9 -- Simplification of Sequential Circuits.
Capacity-Approaching Codes for Reversible Data Hiding Weiming Zhang, Biao Chen, and Nenghai Yu Department of Electrical Engineering & Information Science.
1 Undirected Breadth First Search F A BCG DE H 2 F A BCG DE H Queue: A get Undiscovered Fringe Finished Active 0 distance from A visit(A)
© Charles van Marrewijk, An Introduction to Geographical Economics Brakman, Garretsen, and Van Marrewijk.
VOORBLAD.
15. Oktober Oktober Oktober 2012.
Name Convolutional codes Tomashevich Victor. Name- 2 - Introduction Convolutional codes map information to code bits sequentially by convolving a sequence.
1 Breadth First Search s s Undiscovered Discovered Finished Queue: s Top of queue 2 1 Shortest path from s.
Factor P 16 8(8-5ab) 4(d² + 4) 3rs(2r – s) 15cd(1 + 2cd) 8(4a² + 3b²)
Squares and Square Root WALK. Solve each problem REVIEW:
On Construction of Rate-Compatible Low-Density Parity-Check (RC-LDPC) Codes by Mohammadreza Yazdani and Amir H. Banihashemi Department of Systems and Computer.
© 2012 National Heart Foundation of Australia. Slide 2.
Sets Sets © 2005 Richard A. Medeiros next Patterns.
Understanding Generalist Practice, 5e, Kirst-Ashman/Hull
Chapter 5 Test Review Sections 5-1 through 5-4.
GG Consulting, LLC I-SUITE. Source: TEA SHARS Frequently asked questions 2.
Addition 1’s to 20.
25 seconds left…...
Test B, 100 Subtraction Facts
Januar MDMDFSSMDMDFSSS
Week 1.
We will resume in: 25 Minutes.
©Brooks/Cole, 2001 Chapter 12 Derived Types-- Enumerated, Structure and Union.
1 Unit 1 Kinematics Chapter 1 Day
PSSA Preparation.
Immunobiology: The Immune System in Health & Disease Sixth Edition
How Cells Obtain Energy from Food
Immunobiology: The Immune System in Health & Disease Sixth Edition
By Rasmussen College. 1. What majors or programs do you offer? 2. What is the average length of your programs? 3. What percentage of your students graduate?
Improving the Performance of Turbo Codes by Repetition and Puncturing Youhan Kim March 4, 2005.
1 –Mandatory exercise for Inf 244 –Deadline: October 29th –The assignment is to implement an encoder/decoder system.
Presentation transcript:

Design and Performance of Rate Compatible-SCCC Alexandre Graell i Amat †‡, Guido Montorsi ‡, Francesca Vatta* † Universitat Pompeu Fabra. Barcelona, Spain ‡ Politecnico di Torino. Torino, Italy * Università di Trieste. Trieste, Italy NEWCOM, Department 1-SPW1 meeting ENSEA, April 28th, 2005

2 Politecnico di Torino – Universitat Pompeu Fabra Motivations ■Standard SCCC for high-rates: Outer Encoder  Inner Encoder

3 Politecnico di Torino – Universitat Pompeu Fabra Motivations ■Standard SCCC for high-rates: High-rate Encoder  Inner Encoder ■ If the interleaver size is fixed different information block sizes for different rates ■ For very high rates, the increasing value of the outer code rate causes an interleaver gain penalty error floor

4 Politecnico di Torino – Universitat Pompeu Fabra Motivations ■Standard Rate-compatible SCCC: ■ Rate-compatibility restricts puncturing to the inner encoder ■ In general, the rate of the inner encoder is restricted to be R i  1 t he overall code rate is at most R o Outer Encoder  Inner Encoder PiPi

5 Politecnico di Torino – Universitat Pompeu Fabra A new class of SCCC RC-SCCC ■The inner code may be punctured beyond the unitary rate R SCCC may be greater than the outer code rate ■Puncturing is split between systematic and parity bits:  s : systematic permeability  p : parity permeability Outer Encoder  u Inner Encoder PoPo MUXMUX PsiPsi PpiPpi

6 Politecnico di Torino – Universitat Pompeu Fabra A new class of SCCC ■Performance depend on puncturing patterns P o,P s i,P p i  s and  p should be properly selected ■We propose design criteria of this new class of SCCC by deriving the upper bounds to the error probability Outer Encoder  PoPo Inner Encoder MUXMUX PpiPpi PsiPsi C’ o C’’ o C’ i

7 Politecnico di Torino – Universitat Pompeu Fabra Upper bounds to the error probability ■We obtain: ■The dominant contribution to the error probability for (asymptotic with N) is the largest exponent of N,  M.

8 Politecnico di Torino – Universitat Pompeu Fabra Upper bounds to the error probability ■For recursive inner encoder: and ■ h(  M ): weight associated to the highest exponent of N

9 Politecnico di Torino – Universitat Pompeu Fabra Upper bounds to the error probability ■We obtain: ■ d o’ f : free distance of C’ o ■ d o’’ (d o’ f ): minimum weight of C’’ o code sequences corresponding to a C’ o code sequence of weight d o’ f ■ d i’ f,eff : effective free distance of C’ i ■ h (3) m : minimum weight of C’ i sequences generated by weight 3 input sequences

10 Politecnico di Torino – Universitat Pompeu Fabra Upper bounds to the error probability Outer Encoder  PoPo Inner Encoder MUXMUX PpiPpi PsiPsi C’ o C’’ o C’ i ■ d o’ f : free distance of C’ o ■ d o’’ (d o’ f ): minimum weight of C’’ o code sequences corresponding to a C’ o code sequence of weight d o’ f ■ d i’ f,eff : effective free distance of C’ i ■ h (3) m : minimum weight of C’ i sequences generated by weight 3 input sequences

11 Politecnico di Torino – Universitat Pompeu Fabra Upper bounds to the error probability ■We obtain: ■ d o’ f : free distance of C’ o ■ d o’’ (d o’ f ): minimum weight of C’’ o code sequences corresponding to a C’ o code sequence of weight d o’ f ■ d i’ f,eff : effective free distance of C’ i ■ h (3) m : minimum weight of C’ i sequences generated by weight 3 input sequences

12 Politecnico di Torino – Universitat Pompeu Fabra Upper Bound to the error probability ■Then, P b (e) (asymptotic with respect to N): ■For large E b /N 0 BER performance is given by: d o’ f odd d o’ f even

13 Politecnico di Torino – Universitat Pompeu Fabra Upper Bound to the error probability ■Design considerations: ■ P o should be chosen to optimize C’ o distance spectrum ■ P s i and P p i should be chosen so that h(  m ) and h m are maximized ■ P p i must be optimized to yield the best C’ i IOWEF ■ P s i must be selected to optimize d o’’ (d o’ f ) P s i turns out to be interleaver dependent

14 Politecnico di Torino – Universitat Pompeu Fabra Rate-compatible SCCC ■We designed well-performing rate-compatible SCCC following the aforementioned considerations ■ P s i to optimize d o’’ (d o’ f ) ■ P p i to optimize C i’ IOWEF ■ We used a searching algorithm that works incrementally, fulfilling the rate-compatible restriction, so that the punctured positions for a given outer rate are also punctured for all higher rates.

15 Politecnico di Torino – Universitat Pompeu Fabra The SCCC Scheme Rate-1/2 4 state  u Rate-1/2 4 state Fix punct. MUXMUX PsiPsi PpiPpi d o’ f =3 d o’ f =4 outer code puncturingconstituent codes

16 Politecnico di Torino – Universitat Pompeu Fabra Performance Bounds Bounds of Rate-2/3 SCCC for several  p N=200. P o,1  p =2/30  p =4/30  p =6/30  p =8/30  p =10/30

17 Politecnico di Torino – Universitat Pompeu Fabra Performance Bounds Bounds of Rate-2/3 SCCC for several  p N=200. P o,2  p =2/30  p =4/30  p =6/30  p =8/30  p =10/30

18 Politecnico di Torino – Universitat Pompeu Fabra Simulation Results Performance of Rate-2/3 SCCC for several  p N=200. P o,1  p =2/30. Simulation  p =2/30. Bound  p =4/30. Simulation  p =4/30. Bound  p =8/30. Simulation  p =8/30. Bound  p =10/30. Simulation  p =10/30. Bound

19 Politecnico di Torino – Universitat Pompeu Fabra Simulation Results  p =2/30. Simulation  p =2/30. Bound  p =4/30. Simulation  p =4/30. Bound  p =8/30. Simulation  p =8/30. Bound UMTS PCCC SCCC (VTC’01) Performance of Rate-2/3 SCCC for several  p N=2000. P o,1

20 Politecnico di Torino – Universitat Pompeu Fabra Simulation Results  p =4/222. Simulation  p =4/222. Bound  p =10/222. Simulation  p =10/222. Bound  p =16/222. Simulation  p =16/222. Bound UMTS PCCC Performance of Rate-9/10 SCCC for several  p N=2000. P o,1

21 Politecnico di Torino – Universitat Pompeu Fabra Simulation Results Performance versus  p for several E b /N 0. R=9/10. N=2000. P o,1 22/222 20/222 18/222 16/222 14/222 12/222 10/222 8/222 6/222 4/222 2/222 pp

22 Politecnico di Torino – Universitat Pompeu Fabra Simulation Results FER Performance comparison. N=428 SCCC (10 it.) PCCC (8 it.) LDPC (50 it.)

23 Politecnico di Torino – Universitat Pompeu Fabra Conclusions ■Derived lower bound to the error probability of a new class of SCCC ■Derived suitable design guidelines ■Derived optimal Rate-compatible SCCC families ■The proposed scheme offers good performance for low to moderate block lengths in a large range of rates ■ The interleaver gain for low rates is kept also in the case of heavy puncturing ■This code structure has been proposed as a candidate coding scheme for ESA MHOMS

24 Politecnico di Torino – Universitat Pompeu Fabra Open Problems ■Convergence analysis EXIT charts and Density Evolution Techniques are difficult to apply ■We are open to cooperations with other groups!!!