# LTE ,VITERBI, LDPC IN MATLAB

Exercise

-implement an lte conjunctilar encoder at a rate of 1/3 and

constraint length K=7. For the given encoder, the tables

generator is: g1 = 171oct = [1 1 1 1 0 0 1], g2 = 133oct = [1 0 1 1 0 1

1], g3 = 165oct = [1 1 1 0 1 0 1]. Assume QPSK configuration and 243

QAM symbols per frame.

-For a given range of the ratio of average energy per bit to

the power spectral density of noise (Εb/No) [1,..,10] dB

assume the n=10000000 bits transmission from an awgn channel

communication with noiseVar = 10.^(-snrdB/10).

-On the receiver use Viterbi decoding with the following

Parameters:

• Decision type: Unquantized decision uses the Euclidean distance to

calculate the branch metrics.

• Traceback depth: 37

• Operation mode: Continuous

Questions

Compare bit error rate (ber) (with a related chart) for

the absence of codification by encoding;

described above for the entire range of values (Εb/No)

[1,..,10] dB .

Hint: You can use the functions: erfc, convenc,

qammod, awgn, qamdemod, vitdec of the communication toolbox of

Matlab

2

Exercise

Modify Exercise 1 so that the BER of the decoding

case and concalicative encoder to be compared also with

an ldpc codec with a 3/4 rate that you use in ieee

802.11 standard. Assume, most QPSK configuration and 243 QAM

symbols per frame.

Use the functions:

-For QPSK configuration/deformation:

• qpskmod = comm. PSKModulator(M,'BitInput',true);

• qpskdemod = comm. PSKDemodulator(M,'BitOutput',true, ...

'DecisionMethod','Approximate log-likelihood ratio', ...

'Variance',noiseVar);

-For LDPC encoding/decoding:

• ldpcEncode(), ldpcDecode();

Questions

-Write the comments on the results you observe:

1. for the comparison of conjunctural codes with codes

LDPC.

2. for the comparison of conjunctimal codes and

LDPC codes in relation to the results for their

bar codes block of the 1st task

INSTRUCTIONS

- Use the Matlab Trial and not the Octave, so as to

you can use all of the above functions.

- Create a file (.m) in Matlab for each of the two

Exercises.

- For each of the two exercises also create a document

documentation that you will describe the code, the output of the

your programs, as well as you will answer the questions that

are put in the above exercises.

- Your exercise will be delivered like a zip file (set to

includes type files (.m) and documentation) in

electronic form in eclass on the delivery date.

- The zip file will be named in the following way:

erg2_onoma_epwnymo_number registry.zip.

-For Exercise 2 create a sparse H(162×648) table

via base matrix P =

[16 17 22 24 9 3 14 -1 4 2 7 -1 26 -1 2 -1 21 -1 1 0 -1 -1 -1 -1

25 12 12 3 3 26 6 21 -1 15 22 -1 15 -1 4 -1 -1 16 -1 0 0 -1 -1 -1

25 18 26 16 22 23 9 -1 0 -1 4 -1 4 -1 8 23 11 -1 -1 -1 0 0 -1 -1

9 7 0 1 17 -1 -1 7 3 -1 3 23 -1 16 -1 -1 21 -1 0 -1 -1 0 0 -1

24 5 26 7 1 -1 -1 15 24 15 -1 8 -1 13 -1 13 -1 11 -1 -1 -1 -1 0 0

2 2 19 14 24 1 15 19 -1 21 -1 2 -1 24 -1 3 -1 2 1 -1 -1 -1 0 ];

( 0 bedømmelser ) volos, Greece

Projekt ID: #32685225

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