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itpp::LLR_calc_unit Class Reference

Log-likelihood algebra calculation unit. More...

#include <itpp/comm/llr.h>

Public Member Functions

 LLR_calc_unit ()
 Constructor, using the default table resolution.
 LLR_calc_unit (short int Dint1, short int Dint2, short int Dint3)
 Constructor, using a specific table resolution.
void init_llr_tables (short int Dint1=12, short int Dint2=300, short int Dint3=7)
 Set the quantization and table parameters.
QLLR to_qllr (double l) const
 Convert a "real" LLR value to an LLR type.
QLLRvec to_qllr (const vec &l) const
 Convert a vector of "real" LLR values to an LLR type.
QLLRmat to_qllr (const mat &l) const
 Convert a matrix of "real" LLR values to an LLR type.
double to_double (QLLR l) const
 Convert an LLR type to a "real" LLR.
vec to_double (const QLLRvec &l) const
 Convert a vector of LLR types to a "real" LLR.
mat to_double (const QLLRmat &l) const
 Convert a matrix of LLR types to a "real" LLR.
QLLR jaclog (QLLR a, QLLR b) const
 Jacobian logarithm.
QLLR Boxplus (QLLR a, QLLR b) const
 Hagenauer's "Boxplus" operator.
QLLR logexp (QLLR x) const
 Logexp operator.
ivec get_Dint ()
 Retrieve the table resolution values.


ITPP_EXPORT std::ostream & operator<< (std::ostream &os, const LLR_calc_unit &l)
 Print some properties of the LLR calculation unit in plain text.

Related Functions

(Note that these are not member functions.)

typedef signed int QLLR
typedef Vec< QLLRQLLRvec
typedef Mat< QLLRQLLRmat
const QLLR QLLR_MAX = (std::numeric_limits<QLLR>::max() >> 4)
ITPP_EXPORT std::ostream & operator<< (std::ostream &os, const LLR_calc_unit &lcu)
 Print some properties of the LLR calculation unit in plain text.

Detailed Description

Log-likelihood algebra calculation unit.

This class contains functions for algebra with log-likelihood ratios (LLRs). The class is mainly useful for modules that rely on certain nonlinear operations on LLRs (e.g. boxplus for LDPC and turbo decoding and Jacobian logarithm for soft demodulation). The routines provided are numerically efficient and use only integer arithmetics. Additionally, they allow for arbitrary quantization of LLRs in order to study effects of limited precision (fixed point number representations). As a consequence, computations are approximate. With the standard settings, the numerical precision should be sufficient (and practically equivalent to floating point precision) for all practical applications. However, one can construct cases where small numerical artifacts due to quantization effects (e.g., soft demodulation with very high or very low SNR) can be observed.

An LLR for an information bit b is defined according to

\[ L = \log \frac{P(b=0)}{P(b=1)} \]

and it is in general a real number. LLR values are represented via the special type, "quantized LLR" (QLLR). The relation between the quantized representation and the real (floating-point) LLR value is

\[ \mbox{QLLR} = \mbox{round} \left(2^{\mbox{Dint1}}\cdot \mbox{LLR}\right) \]

The user parameter Dint1 determines the granularity of the quantization, and it can be set arbitrarily. The functions to_double() and to_qllr() can be used to perform conversions between the two representations (QLLR to floating-point, and vice versa).

The class provides functions for the computation of the Jacobian logarithm and Hagenauer's "boxplus" operator. These functions are based on a table-lookup. The resolution of the table is determined by the parameters Dint2 and Dint3. See the class constructor for more detail. When an object of LLR_calc_unit is created, corresponding lookup-tables are also generated. The resolution of these tables can be adjusted by providing parameters to the constructor.

The variable table resolution allows one to study complexity versus accuracy (i.e., how different table resolutions would degrade performance) to some extent. Yet the main purpose of the QLLR representation is to provide a tool for writing efficient simulation code, rather than to provide for bit-level (fixed-point) simulations. For bit-level simulations, a true fixed point representation of LLRs would be preferred/required. With the default setting of the table parameters, using the QLLR type is practically as accurate (but much faster) as using "double" to represent LLRs. Decoder implementations may then provide functions using QLLR, fixed-point, or double (for compatibility reasons) representations of LLR values.

Note: the QLLR type does not check that the correct quantization level is used. I.e., in theory it would be possible to add two QLLR types with different quantization (Dint) parameters. This is intentionally implemented this way to achieve maximum runtime efficiency.

Definition at line 124 of file llr.h.

Constructor & Destructor Documentation

itpp::LLR_calc_unit::LLR_calc_unit ( short int  Dint1,
short int  Dint2,
short int  Dint3 

Constructor, using a specific table resolution.

See init_llr_tables() for more details on the parameters.

Definition at line 41 of file llr.cpp.

References init_llr_tables().

Member Function Documentation

void itpp::LLR_calc_unit::init_llr_tables ( short int  Dint1 = 12,
short int  Dint2 = 300,
short int  Dint3 = 7 

Set the quantization and table parameters.

Dint1Determines the relation between LLR represented as real number and as integer. The relation is

\[ \mbox{QLLR} = \mbox{round} \left(2^{\mbox{Dint1}}\cdot \mbox{LLR}\right) \]

Dint2Number of entries in the table. If this is zero, then logmap becomes logmax.
Dint3Determines the table resolution. The spacing between each entry is

\[ 2^{-(Dint1-Dint3)} \]

The default parameter values are chosen to give a performance practically indistinguishable from that of using floating point calculations.

Example: (recommended settings with "exact" computation via high resolution lookup table)

LLR_calc_unit lcalc(12, 300, 7);

Example: (recommended settings with logmax, i.e. no table lookup)

LLR_calc_unit lcalc(12, 0, 7);

Definition at line 55 of file llr.cpp.

Referenced by LLR_calc_unit().

QLLR itpp::LLR_calc_unit::jaclog ( QLLR  a,
QLLR  b 
) const
QLLR itpp::LLR_calc_unit::Boxplus ( QLLR  a,
QLLR  b 
) const

Hagenauer's "Boxplus" operator.

This function computes:

\[ \mbox{sign}(a) * \mbox{sign}(b) * \mbox{min}(|a|,|b|) + f(|a+b|) - f(|a-b|) \]


\[ f(x) = \log(1+\exp(-x)) \]

Definition at line 123 of file llr.cpp.

References it_info_debug, logexp(), and QLLR_MAX.

Referenced by itpp::LDPC_Code::bp_decode(), and itpp::LDPC_Code::soft_syndrome_check().

QLLR itpp::LLR_calc_unit::logexp ( QLLR  x) const

Logexp operator.

This function computes

\[ f(x) = \log(1+\exp(-x)) \]

Definition at line 261 of file llr.h.

References it_assert_debug.

Referenced by Boxplus(), and jaclog().

Friends And Related Function Documentation

typedef signed int QLLR

The quantized log-likelihood ratio (QLLR) representation, scalar form. See LLR_calc_unit.

Definition at line 46 of file llr.h.

typedef Vec<QLLR> QLLRvec

The quantized log-likelihood ratio (QLLR) representation, vector form. See LLR_calc_unit.

Definition at line 51 of file llr.h.

typedef Mat<QLLR> QLLRmat

The quantized log-likelihood ratio (QLLR) representation, matrix form. See LLR_calc_unit.

Definition at line 56 of file llr.h.

const QLLR QLLR_MAX = (std::numeric_limits<QLLR>::max() >> 4)

The largest possible QLLR value

Definition at line 61 of file llr.h.

Referenced by Boxplus(), jaclog(), and to_qllr().

The documentation for this class was generated from the following files:
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