C Program For Convolutional Code Matlab Pattern
Description
- Convolutional Code Matlab
- C Program For Convolutional Code Matlab Pattern Pdf
- C Program For Convolutional Code Matlab Patterns
decoded = vitdec(code,trellis,tblen, decodesthe vector opmode,dectype)code using the Viterbi algorithm. The MATLAB® structure trellis specifiesthe convolutional encoder that produced code; theformat of trellis is described in Trellis Description of a Convolutional Code andthe reference page for the istrellis function. code containsone or more symbols, each of which consists of log2(trellis.numOutputSymbols) bits.Each symbol in the vector decoded consists of log2(trellis.numInputSymbols) bits. tblen isa positive integer scalar that specifies the traceback depth. If thecode rate is 1/2, a typical value for tblen isabout five times the constraint length of the code.
Invariance are called convolutional codes. Convolutional coding with Viterbi decoding has been the predominant FEC technique used in space communication, particularly in geostationary satellite communication networks, such as VSAT (very small aperture terminal) networks. The first large-scale application includes a rate-1/2 convolutional code. To define the convolutional encoder, use the Trellis structure parameter. This parameter is a MATLAB ® structure whose format is described in Trellis Description of a Convolutional Code. You can use this parameter field in two ways.
opmode indicates the decoder's operation mode and its assumptions about the corresponding encoder's operation. Choices are in the table below.
Values of opmode Input
| Value | Meaning |
|---|---|
'cont' | The encoder is assumed to have started at the all-zeros state. The decoder traces back from the state with the best metric. A delay equal to tblen symbols elapses before the first decoded symbol appears in the output. This mode is appropriate when you invoke this function repeatedly and want to preserve continuity between successive invocations. See the continuous operation mode syntaxes below. |
'term' | The encoder is assumed to have both started and ended at the all-zeros state, which is true for the default syntax of the convenc function. The decoder traces back from the all-zeros state. This mode incurs no delay. This mode is appropriate when the uncoded message (that is, the input to convenc) has enough zeros at the end to fill all memory registers of the encoder. If the encoder has k input streams and constraint length vector constr (using the polynomial description of the encoder), “enough” means k*max(constr-1). |
'trunc' | The encoder is assumed to have started at the all-zeros state. The decoder traces back from the state with the best metric. This mode incurs no delay. This mode is appropriate when you cannot assume the encoder ended at the all-zeros state and when you do not want to preserve continuity between successive invocations of this function. |
For the 'term' and 'trunc' mode, the traceback depth (tblen) must be a positive integer scalar value, not greater than the number of input symbols in code.
dectype indicates the type of decisionthat the decoder makes, and influences the type of data the decoderexpects in code. Choices are in the table below.
Values of dectype Input
| Value | Meaning |
|---|---|
'unquant' | code containsreal input values, where 1 represents a logical zero and -1 representsa logical one. |
'hard' | code containsbinary input values. |
'soft' | For soft-decision decoding,use the syntax below. nsdec is required for soft-decisiondecoding. |
Syntax for Soft Decision Decoding
Convolutional Code Matlab
decoded = vitdec(code,trellis,tblen, decodes the vector opmode,'soft',nsdec)code using soft-decision decoding. code consists of integers between 0 and 2^nsdec-1, where 0 represents the most confident 0 and 2^nsdec-1 represents the most confident 1. The existing implementation of the functionality supports up to 13 bits of quantization, meaning nsdec can be set up to 13. For reference, 3 bits of quantization is about 2 db better than hard decision decoding.
Syntax for Punctures and Erasures
decoded = .. vitdec(code,trellis,tblen, denotesthe input punctured opmode,dectype,puncpat)code, where puncpat isthe puncture pattern vector, and where 0s indicatepunctured bits in the input code.
decoded = .. vitdec(code,trellis,tblen, allowsan erasure pattern vector, opmode,dectype,puncpat,eraspat)eraspat, to be specifiedfor the input code, where the 1sindicate the corresponding erasures. eraspat and code mustbe of the same length. If puncturing is not used, specify puncpat tobe []. In the eraspat vector, 1sindicate erasures in the input code.
Additional Syntaxes for Continuous Operation Mode
Continuous operation mode enables you to save the decoder'sinternal state information for use in a subsequent invocation of thisfunction. Repeated calls to this function are useful if your datais partitioned into a series of smaller vectors that you process withina loop, for example.
decoded = .. vitdec(..,' is the same as the earlier syntaxes, except that the decoder starts with its state metrics, traceback states, and traceback inputs specified by cont',..,initmetric,initstates,initinputs) initmetric, initstates, and initinputs, respectively. Each real number in initmetric represents the starting state metric of the corresponding state. initstates and initinputs jointly specify the initial traceback memory of the decoder; both are trellis.numStates-by-tblen matrices. initstates consists of integers between 0 and trellis.numStates-1. If the encoder schematic has more than one input stream, the shift register that receives the first input stream provides the least significant bits in initstates, while the shift register that receives the last input stream provides the most significant bits in initstates. The vector initinputs consists of integers between 0 and trellis.numInputSymbols-1. To use default values for all of the last three arguments, specify them as [],[],[].
[decoded,finalmetric,finalstates,finalinputs] = .. vitdec(..,' is the same as the earlier syntaxes, except that the final three output arguments return the state metrics, traceback states, and traceback inputs, respectively, at the end of the decoding process. cont',..)finalmetric is a vector with trellis.numStates elements that correspond to the final state metrics. finalstates and finalinputs are both matrices of size trellis.numStates-by-tblen. The elements of finalstates have the same format as those of initstates.
Traceback Matrices
The tth columnof P1 shows the t-1th timestep states given the inputs listed in the input matrix. For example,the value in the ith rowshows the state at time t-1 that transitions tothe i-1 state at time t. Theinput required for this state transition is given in the ith rowof the tth column ofthe input matrix.
The P1 output is thestates of the traceback matrix. It is a [number of states x tracebacklength] matrix. The following example uses a (7,5), rate 1/2 code.This code is easy to follow:
t = poly2trellis(3,[7 5]);
k = log2(t.numInputSymbols);
msg = [1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 11 0 0 1 1 0 0 1 1 0 0];
code = convenc(msg,t); tblen= 15; [d1 m1 p1 in1]=vitdec(code(1:end/2),t,tblen,'cont','hard')
In this example, the message makes the encoder states followthe following sequence:
0 2 3 1 / 0 2 3 1 / ..
C Program For Convolutional Code Matlab Pattern Pdf
Since the best state is 0 (column index of smallest metric in m1 –1), the traceback matrix starts from state 0, looking at the first row (0th state) of the last column of P1, ([1; 3; 1; 3]), which is 1. This indicates 1 for the previous state.
Next, the traceback matrix checks in1 ([0; 0; 1; 1]), whichindicates 0 for the input. The second row (1ststate) of the 14th column of P1 ([1;3; 1; 3]) is 3. This indicates 3 forthe previous state.
The traceback matrix checks in1 ([0; 0; 1; 1]), which indicatesthat the input was 0. The fourth row (3rd state) of the 13th columnof P1 ([0; 2; 0; 2]), is 2. This indicates 2 for the previous state.
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The traceback matrix checks in1 ([0; 0; 1; 1]), which indicatesthe input was 1. The third row (2nd state) ofthe 12th column of P1 ([0;2; 0; 2]), is 0. This indicates 0 forthe previous state.
C Program For Convolutional Code Matlab Patterns
The traceback matrix checks in1 ([0; 0; 1; 1]), which indicatesthe input was 1. The first row (0th state) ofthe 11th column of P1 ([1;3; 1; 3]), is 1. This indicates 1 forthe previous state. Then, the matrix checks in1 ([0; 0; 1; 1]), whichindicates 0 for the input.
To determine the best state for a given time, use m1. The smallest number in m1 represents the best state.