Performed by :

Nidhi Gupta, 63/EC/07

Rupinder Singh, 83/EC/07

Siddi Jai Prakash, 101/EC/07

Electronics and Communication Division

Netaji Subhas Institute of Technology, Delhi

PERFORMANCE ANALYSIS OF FREE SPACE OPTICAL (FSO)

COMMUNICATION USING DIFFERENT CODING SCHEMES

Mentored by:

Prof. Subrat KarDept. of Electrical Engineering IIT Delhi Dr. S.P. SinghElectronics and Communication DivisionNetaji Subhas Institute of Technology, Delhi

OBJECTIVETo design a communicationsystem between earth and a

geoSatellite with free space as

thechannel.

Aperture averaging – Aperture effects at the transmitter

Adaptive Optics - Use of collimating lenses at transmitter and receiver

Spatial Diversity – Using a number of transmitters arranged horizontally or vertically

Error Control Coding – Using ECC, for data transmission.

METHODOLOGY

Source used was a simple coherent laser light.No source coding was usedDifferent channel coding schemes namely,

Convolutional, LDPC and RS were usedM-PPM and OOK modulation techniques were used.Channel was the free space with different

turbulence conditionsThe detection at the receiver side was direct.

Features –High Data Bandwidth of 1 Gbps and

above–Low BER, High SNR–Narrow Beam Size

–Power Efficient and Data Security–Cheap

–Quick to deploy and redeploy– Channel Impairments like

Dispersion, Scattering, Turbulence

Free Space Optical Communication (FSO)

Terrestrial FSO Block Diagram

Comparative Study of Fiber Optical Cable and FSO Communication

ERROR CONTROL CODING TECHNIQUES

Figure Convolutional Encoder

Convolutional codes are performed on bit to bit basis.

m-bit information symbol (each m-bit string) to be encoded is transformed into an n-bit symbol, where m/n is the code rate (n ≥ m) transformation is a function of the last k information symbols, where k is the constraint length of the code, using the generator matrix.

CONVOLUTIONAL CODES

Implementation in MATLAB Encoding using the function ‘convenc’ using a

trellis structure ‘trellis’[msg_enc_bi, stateEnc] = convenc(msg_orig,

trellis, stateEnc)

Decoding using the function ‘vitdec’ and ‘hard’ decoding[msg_dec, metric, stateDec, in] =

vitdec(msg_demod_bi(:), trellis, tblen, 'cont', 'hard', metric, stateDec, in)

Low Density Parity Check Codes (LDPC)

ENCODING IN MATLAB

MATLAB has a fixed size of sparse matrix 32400 x 64800

Hence, we generate our own custom sparse matrix.

We then generate Parity Check bits using LU decomposition of sparse matrix

Finally, we solve for c in L(Uc) = B.s, where H = [A|B], s = input vector

Decoding -The Optimized Algorithm There are three key variables in the algorithm: L(rji), L(qij),

and L(Qi). L(qij) is initialized as

L(qij) = L(ci). For each iteration, update L(rji), L(qij), and L(Qi) using the following equations:

At the end of each iteration, L(Qi) provides an updated estimate of the log-likelihood ratio for the transmitted bit ci.The soft-decision output for ci is L(Qi). The hard-decision output for ci is 1 if L(Qi) < 0 , and 0 else.

REED SOLOMON CODES

Figure A pictorial representation of the transmitted bits after Reed Solomon Encoding.

For Reed- Solomon codes, the code minimum distance is given by

dmin = n - k + 1The code is capable of correcting any combination of t or fewer errors, where t can be expressed as

In the simulation, we have used M = 5 is the no. of bit sequences in a symbol, K = 127 is the number of data symbols being encoded, andN = 255 is the total number of code symbols in encoded block.Therefore, Code Rate = 127/255 ~ 0.5

MODULATION SCHEMES

Adaptive OOK

PPM

M-PPM

COMMUNICATION CHANNEL

Communication ChannelsLognormal:For standard devaitions between 0.001 to 0.6

Gamma-Gamma:for higher standard deviations:

MONTE CARLO SIMULATIONSMonte Carlo simulation performs analysis

by building models of possible results by substituting a range of values—a probability distribution—for any factor that has inherent uncertainty

coding gain is the measure in the difference between the signal to noise

ratio (SNR) levels between the uncoded system and coded system required to

reach the same bit error rate (BER) levels when used with the error

correcting code (ECC).

CODING GAIN

RESULTS4-PPM under Lognormal (var=0.1)

4-PPM under Lognormal (var=0.01)

4-PPM under Lognormal (var=0.001)

OOK under Lognormal (var=0.1)

OOK under Lognormal (var=0.01)

OOK under Lognormal (var=0.001)

4-PPM under Gamma-Gamma (var=0.1)

4-PPM under Gamma-Gamma (var=0.01)

4-PPM under Gamma-Gamma (var=0.001)

OOK under Gamma-Gamma (var=0.1)

OOK under Gamma-Gamma (var=0.01)

OOK under Gamma-Gamma (var=0.001)

Effect of PPM index on curve (LDPC)

Effect of Coding Rate on Coding Gain

Effect of Coding Rate on Coding Gain

Recommendation for Future WorkOne can investigate the effects of

Medium turbulence channels, namely gamma-gamma using Accept Reject Method.

High turbulence channels, namely exponential on the BER in the communication link.

Implement more coding techniques like Turbo coding and Trellis coded modulation (TCM).

References: M. Karimi, M. Nesiri-Kenari, “BER Analysis of Cooperative Systems in Free-Space

Optical Networks” J. of Lightwave Technology, vol. 27, no. 24, pp. 5637-5649, Dec 15, 2009

E. W. B. R. Strickland, M. J. Lavan, V. Chan, “Effects of fog on the bit-error rate of a free space laser Communication system,” Appl.Opt., vol. 38, no. 3, pp. 424–431, 1999.

M. Uysal, J. Li, and M. Yu, “Error rate performance analysis of coded free-space optical links over gamma -gamma

atmospheric turbulence channels,” IEEE Trans . Wireless Communication, vol. 5, no. 6, pp.1229–1233, 2006.

L. Andrews, R. Phillips, C. Hopen, Laser Beam Scintillation With Applications. New York: SPIE Press, 2001.

Bernard Sklar, Reed – Solomon Codes. Stephen B. Wicker, Vijay K. Bhargava, “An introduction to Reed Solomon Codes. Ghassemlooy, Z. And Popoola, W.O Terrestrial Free Space optical Communication. Gallager, Robert G., “Low-Density Parity-Check Codes”, Cambridge, MA, MIT Press,

1963. Amin Shokrollahi, “LDPC Codes: An introduction”, Digital Fountain, Inc, April 2, 2003 Henk Wymeersch, Heidi Steendam and Marc Moeneclaey, DIGCOM research group,

TELIN Dept., Ghent University, “Log-domain decoding of LDPC codes over GF(q)”.