video transmission overwireless channel

IEIIT-BOCNR

DEIS, Università di Bologna

Video Transmission

over Wireless Channel

Bologna, 17.01.2011

Raffaele Soloperto

PhD Student @ DEIS, University of Bologna

Tutor: O.Andrisano

Co-Tutors: G.Pasolini and G.Liva (DLR, DE)

Bologna, 17.01.11 RAFFAELE SOLOPERTO

PhD Outline

� Focus on DVB-T and T2 standards:

� Signal Processing� Linear and Non Linear Predistorsion

� MultiRate – MultiStage Filters

� Channel Coding� LDPC, G-LDPC and DG-LDPC Codes

� Measurements and Tele-Measurements� Instrumentation and programmable circuits


PhD Outline

� Focus on DVB-T and T2 standards:

� Signal Processing� Linear and Non Linear Predistorsion

� MultiRate – MultiStage Filters

� Channel Coding� LDPC, G-LDPC and DG-LDPC Codes

� Measurements and Tele-Measurements� Instrumentation and programmable circuits

SIG

NA

LP

RO

CE

SS

ING

CH

AN

NE

LC

OD

ING

MEAS. AND TELE MEAS.

VIDEO OVER WIRELESS

II II, III

I, II, III


PhD Outline

Design of MultiStage and MultiRate Filters withminimum group delay

Signal Processing: MultiStage-MultiRate Filters


Scientific literature:

I) Ronald E.Crochiere, Lawrence R.Rabiner �� multistage multiratefilters with minimum number of taps

fixedproj<

II) Raffaele Soloperto, Gianni Pasolini �� multistage multirate filters withminimum group delay


MultiStage MultiRate Filter

DEC LPF INTM L

Downsampl.LPF

M

Downsampl.

LPF1Down sampl.

LPFI

MultiRate Decimation(min. number of taps)

M1 MI

ADC

X

X

LPF

LPF

X

X

DAC

cos(2π f0t) cos(2π f0t)

-sen(2π f0t) -sen(2π f0t)

+


Measurements (1/2)

Fc = 36 MHz

B = 8 MHz


Measurements (2/2)

Fc = 36 MHz

B = 1 MHz

IEIIT-BOCNR


Iterative decoding of DG-LDPC codes

Visiting PhD Student at DLR, Munich – DE

(Nov 2009 – July 2010)


Outline

� Introduction� LDPC codes

� Generalized LDPC codes

� Doubly Generalized LDPC codes� Graph representation

� Decoding algorithm

� Efficient encoding: Quasi-Cyclic DG-LDPC codes

� Conclusions


� Long LDPC/Turbo codes approach Shannon limit

� In the moderate/short block length regime, however, they show a gap from theoretical bounds (~1dB):

� Generalized LDPC codes (Leintmeier ’98, Chiani ’06, Liva ’06)

� Non-binary LDPC codes (Mackay, ’98)

� Doubly Generalized LDPC codes (Chiani/Paolini/Fossorier ’06)

Why DG-LDPC codes?


Low-Density Parity-Check Codes

� LDPC codes: (sparse) bipartite graph describing the parity-check equations.

=1001110

0101101

0011011

H

=⊕⊕⊕=⊕⊕⊕=⊕⊕⊕

0

0

0

7432

6431

5421

cccc

cccc

cccc

Parity-check equations:

Parity-check matrix of a Hamming (7,4):

Bipartite graph:

Variable nodes

Check nodes


LDPC codes: decoding on the bipartite graph

� ML decoding is unfeasible even for rather short block lengths…� Belief propagation (BP): iterative, message-passing decoding algorithm.� Sparse graph: the correlation among messages is reduced. BP ≈ ML.� Complexity: graph, nodes, iteration number, etc…

. . .

. . .

Channel observations(noisy symbol samples)

„bit reliabilites“

y1 y2 y3 yn. . .


Generalized LDPC

…

…Single Parity-Check

Low-density parity-check codes(large number of simple nodes)


Generalized LDPC

…

… Block code(ex. Hamming)

Block turbo codes (BTC) andgeneralized low-density codes (GLDC)(trade-off between node count and complexity)

HHHH


Generalized LDPC

…


Block turbo codes (BTC) andgeneralized low-density codes (GLDC)(trade-off between node count and complexity)

Error floors are lowered

Unbalancing of the edcoding complexity: all the complexity at the SCN!

Super Check Node can be stronger than conventional CN


Getting closer to the limits in the short/moderate length

Balancing the decoder complexity at CNs and VNs

DG-LDPC codes

“Generalized Stability Condition for Generalized and Doubly-Generalized LDPC Codes”,E.Paolini, M.P.C. Fossorier, M.Chiani, ISIT2007, Nice, France, June24 – June29, 2007

“Generalized and Doubly Generalized LDPC codes with random component codes for the binary erasure channel”, E.Paolini, M.P.C. Fossorier, M.Chiani, IEEE Transaction on Information Theory, Vol. 56, No 4, April 2010

“On the Growth Rate of the Weight Distribution of Irregular Doubly-Generalized LDPC Codes”, M.F. Flanagan, E. Paolini, M. Chiani, and M.P.C. Fossorier, Forty-Sixth Annual Allerton Conference, Allerton House, UIUC, Illinois, USA, September 23-26, 2008

STATE OF THE ART

“Doubly-Generalized LDPC codes: stability bound over the BEC”, E.Paolini, M.P.C. Fossorier, M.Chiani, IEEE Transaction on Information Theory, Vol. 55, No. 3, March 2009


� Motivation of our work:

� Simplify decoding algorithm

(new stopping criterions)

� Efficient encoding

(design of QC-DGLDPC codes)

DG-LDPC codes


Outline






� Conclusions


DG-LDPC GraphN

ois

y c

od

ew

ord

The Tanner graph of DG-LDPC codes can be obteined from that of LDPC codes with original VNs and CNs replaced by Super Variable Nodes and Super Check Nodes respectively.

Legend:


DG-LDPC Graph

SVNs and SCNs are subcodes with lengths equal to the degrees of their corresponding super nodes!

SVNs degree

(dvx, kvx): subcode for the SVN

dvx: block length of the subcode

kvx: dimension of the subcode

Kv1

no

isy

co

de

wo

rd b

its

SUPER VARIABLE NODE


DG-LDPC Graph

SVNs and SCNs are subcodes with lengths equal to the degrees of their corresponding super nodes!

SCNs degree

(dcy, kcy): subcode for the SCN

dcy: block length of the subcode kcy: dimension of the subcode

SUPER CHECK NODE


DG-LDPC. Decoding algorithm

Iterative decoding based on belief propagation (BP)

A Priori information at the i-th iteration

Extrinsic information at the i-th iteration


Decoding Algorithm

ITERATIONS

SVN

SCN

SUPER CHECK NODE ELABORATION

SUPER VARIABLE NODE ELABORATION

APP LLR TRANSMITTED BIT

HARD DECISION

SYNDROME CHECK


EXIT Chart


Stopping Criterions

Simulation on standard PC (Pentium IV, 3.00GHz, 3.00GB RAM)

Example: DG-LDPC code

500 SVNs (SPC(7,6))

500 SCNs (Hamm(7,4))

R = 0.5

Transmitted codewords = 1000

Eb/N0 = 1.8 dB (CER = 10-4)

State of the art

Proposed solutions

da

ta r

ate

[K

bp

s]

• STEP STOP: evaluation of parity-check equations every N iterations.

• THRESHOLD STOP: evaluation of parity-check equations after a fixed number of iterations (threshold)


Iterative decoding simulator

In principle, we can simulate all possible iteratively – decodable codes


Iterative decoding simulatorIn principle, we can simulate all possible iteratively – decodable codes

π

C C

…

…

Convolutional turbo codes(small number of complex nodes)

Convolutionalcode

…


Block turbo codes (BTC) andgeneralized low-density codes (GLDC)

(trade-off between node count and complexity)

HHHH

…

…

Low-density parity-check codes(large number of simple nodes)

Singleparity-check

IEIIT-BOCNR


RESULTS


Outline






� Conclusions


Protographs

� Protograph: small graph with N variable nodes and M check nodes

� Each check/variable node in a protograph identifies a check/variable node type

� Multiple, parallel edges are allowed.

Type A Type B

Type c Type d Type e


� Derived graph: obtained by q replicas on the protograph.

� Cyclic edge permutations: the DG-LDPC code is quasi-cyclic (QC).

� Shift-register-based encoder.

Protographs


Proof (sketch):

� Expand rows/columns of Γ according to the rule

� Permute rows/columns of according to a defined algorithm (not shown here)

� HDGLDPC is block circulant

Protographs

THE CODE IS QUASI-CYCLIC

Proposition. A sufficient condition for having a QC DG-LDPC is that the protograph is expanded by means of circulant permutation matrices

HDGLDPC


7 SCNs Hamm(15,11)

15 SVNs Hamm(7,4)

Q = 30

# SVNs = 450

# SCNs = 210

# bits = 1800

R = 0.533

Kv1 = 4

dv1 = 7

dc1 = 15

Protographs example (1/3)


Adjaceny Matrix

HQC-DGLDPC


Rows/columns expansion

Rows/columns permuation



Performance of a (1800, 960) QC-DGLDPC code and DG-LDPC code in terms of CER on the AWGN channel

There is NO degradation of performance between a QC code and unstructured code!

Q = 30

# SVNs = 450

# SCNs = 210

R = 0.533


Outline






� Conclusions


� Signal Processing:� design of MultiRate MultiStages Filters with minimum group

delay

� Channel Coding:� General Purpose decoder machine for iterative codes (LDPC,

G-LDPC, DG-LDPC..)� efficient encoding: Quasi Cyclic codes

� Mesearements and TeleMeasurements:� remotization of instrumentation and programmable circuits� remotization of the connections by means of a programmable

matrix

Conclusions


Publication


”Sistema di filtraggio, Cancellatore d’eco, Studio delle prestazioni delsistema e Pianificazione di rete.”

”Sistema di filtraggio multistadio, Precorrezione non lieare, Cancellatored’eco.”

”Sistema di filtraggio multistadio, Precorrezione non lieare, Precorrezionelineare, Cancellatore d’eco.”

”Sistema di filtraggio multistadio, Precorrezione non lieare, Precorrezionelineare, Cancellatore d’eco, Modulatore.”

”Attività di misura per la caratterizzazione del Cancellatore d’eco afinestra fissa, con tecnologia ad impulsi e LMS.”

”Deliverable Finale DVB2006 (Polo tecnologico TV digitale)”:- DVB-T Echo Canceller (design & implementation);- DVB-T Echo Canceller (measurements).

DELIVERABLES – DVB2006


THANK YOU!

video transmission overwireless channel

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