The method of quantization for an iterative decoder in a communication system

 

The invention relates to communication systems and can be used in methods of quantization. The technical result consists in the use of quantization in an iterative decoder. In the method of quantization of the received signal levels are divided equally at predefined intervals in the range, which is 2 times larger than the range of levels of the transmission signal of the transmitter, and quantuum the level of the input signal received in each period. 2 S. and 11 C.p. f-crystals, 5 Il., table 4.

Technical FIELD the Invention relates to a receiver in the communication system, and more specifically to a device and method for quantization of the received signal.

The PRIOR art system Resources, such as the number of bits, power and delay for the signal processing are limited, when the channel decoder is designed keeping in mind the real situation. Specific signal must be represented by a limited number of bits, in particular for processing in the decoder. In other words, the analog signal applied to the input of the decoder, it is necessary to quantize. The signal's resolution or fidelity of a signal should be considered for quantization, since it has a great pleanala bits quantization (QB), is of great interest to the system designer, when he represents the signals to the input terminal of the decoder and inside the decoder.

The transmitter in the communication system (for example, satellite system, wideband multiple access, code-division multiplexing (system SMDR), the system mdcr-2000) can use codes to direct error correction for reliable data transmission, and the receiver can apply the iterative decoding for the received data. Iterative decoding is characterized by applying the decoded output signal back to the input of the decoder. Therefore, the output signal of an iterative decoder is not a signal "hard" solutions, like the signal high or low level (for example, +1, -1), and is a signal of "soft" decisions (for example, 0,7684, -0,6432,.. .). An iterative decoder consists of at least two component decoders and the interleaver connected between the component decoders and produces a permutation of the sequence of bits received at its input side of the component decoder. When the components of the decoded signal is fed back to the output the output of the iterative decoder, converts interleaver iterative Deco

In Fig.1 shows a graph illustrating a method of quantization in the well-known Viterbi decoder for transmission of the speech signal.

In Fig. 1, the horizontal axis of the graph shows the amplitude levels of the received signal, and the vertical axis shows the probability density function (PPV) of the two signals. In this case, it is assumed that the transmission channel for the received signal is a channel with additive white Gaussian noise (abgs). The received and demodulated signal is quantized at predefined intervals relative to FPV. This quantization is typically used because of their advantages associated with simplicity and good performance of the decoding. As shown in Fig.1, QB is equal to 4 bits, and the resulting quantization levels (QL) are used to represent the range within the values +a and-A, which are the levels of the signal received from the transmitter. For example, although the received signal may have a value above or below-But because of the noise in the transmission channel, it is transformed accordingly to the maximum quantizing level (QMAX), or at a minimum level of quantization (QMIN).

In the Viterbi decoder mainly used the non-iterative decoding scheme, and its output is novania the Viterbi decoder allows you to decode an input signal with sufficient reliability. If the value of QB is set at 4 (QL=16), and the difference in characteristics between the Viterbi decoding and the decoding endless level is not more than 0.2 dB.

On the other hand, the input/output signal of an iterative decoder based on a soft input signal the output signal of the soft decisions (MVPS). Therefore, the confidence level and the polarity must be taken into account when determining the input signal of the decoder. That is, the output signal of an iterative decoder MVPS, which will be fed back should not be a signal of tough decisions (high or low), and should be a signal of soft decisions. But the known method of quantization (Fig.1) signals that are outside the range of levels of transmission from +a to-And is discarded when the analog-to-digital conversion, which leads to a serious degradation of the performance of an iterative decoder. Therefore, different levels must be assigned to the signals above and below, an input of an iterative decoder. In other words, the range of quantization must be greater than the range of levels of transmission between +a and-A, so that the reliability indices for the input signal of an iterative decoder were differentiated.

is enough resolution quantization, the resulting expansion of the range of quantization, will likely lead to performance deterioration of an iterative decoder. Therefore, it is necessary to determine the optimal value QB.

Although the signal demodulation FMD (two-phase shift keying) or CPM (quadrature phase shift keying), which is served in turbodecoding, which is part of the receiver is typically an analog signal, it is necessary to provide criteria, based on which you can get the parameters for the quantization of the analog signal in case of fulfillment of turbodecoding real of very large scale integrated circuits (VLSI).

Summary of the INVENTION the present invention is to create a way to expand the range of quantization above the highest and below the lowest value of the range of levels of transmission for an iterative decoder in a communication system.

Another objective of the present invention is to provide a method of quantization for turbodecoding for optimal range of quantization of any number of bits of quantization.

The third objective of the present invention is to provide a method of quantization for turbodecoding for optimal range is udaetsya in the creation of a method of setting the number of bits to represent the internal signal of each particular decoder, the method is based on the number of bits of quantization of the input signal of an iterative decoder and metric calculation, each component decoder, when the transmission speed code iterative decoder is equal to 1/4 or higher.

The fifth objective of the present invention is to provide a method for obtaining the optimal quantization parameter for turbodecoding in the communication system.

The sixth objective of the present invention is to create a representation of the criteria by which you can get the parameters for the quantization of the analog signal on the input side of turbodecoding when turbodecoding done in real VLSI.

These and other problems are solved in the proposed method of quantization iterative decoder. According to this method of quantization levels of a received signal is divided equally at predefined intervals within the range that the 2ntimes (where n is a positive integer) is greater than the range of levels of the transmission signal of the transmitter, and quantuum the level of the signal received in each period.

A BRIEF description of the DRAWINGS the Above and other objectives, features and advantages of the present invention are explained in the following detailed description of the persons quantization for the Viterbi decoder, intended for transmission of the speech signal; Fig. 2 is a graph illustrating a method of quantization iterative decoder according to a preferred variant implementation of the present invention; Fig. 3 is a block diagram of the quantizer and an iterative decoder to illustrate relationships between them according to a preferred variant implementation of the present invention; Fig. 4 is a block diagram of an iterative decoder rate 1/3 code according to a preferred variant implementation of the present invention and Fig. 5 is an algorithm illustrating a method of quantization, according to a preferred variant implementation of the present invention.

A DETAILED DESCRIPTION of the PREFERRED OPTION IMPLEMENTATION
Description of the preferred alternative implementation of the present invention below with reference to the drawings. In the following description, well-known functions or structures are not described in detail in order not to complicate the description of the invention with unnecessary detail.

In Fig.2 shows a graph illustrating a method of quantization iterative decoder according to a preferred variant implementation of the present invention.

In Fig.2, the horizontal axis of the graph of the transmission for the received signal is a channel abgs. As shown in Fig.2, QB is equal to 4 bits, resulting in 16 QL. In a preferred embodiment, the range of quantization is extended above the high and below the low level range of the quantization from +a to-A (Fig.1). That is, different levels assign the signals above and below-A. Thus, expansion of the range of quantization of above and below-And allows us to differentiate the reliability indices for the input signal of an iterative decoder.

However, if the received signal has 16 levels (QB=4), as in the prior art (Fig.1), the lack of resolution quantization (QS=1/A), which arises due to the extended range of quantization may result in reduced performance of an iterative decoder. Therefore, it is necessary to find the optimal value QB and take into account the increase in dynamic range due to the calculation of internal metrics in each component decoder. Therefore, the number of bits required to signal processing in each component decoder, must be greater than the number of bits of quantization of the input signal in an iterative decoder for a predetermined number of bits.

From this point of view Ave is In Fig.3 depicts a block diagram of a quantizer for quantizing an input signal and an iterative decoder for receiving the quantized signal according to a preferred variant implementation of the present invention.

As shown in Fig. 3, first, second and third input signals may be analog signals coming out of the demodulator (not shown) of the receiver (not shown). The first input signal may contain systematic part of Xtowith the order of the original data values. The second and third input signals may represent, respectively, the part of the parity Y1Kand Y2K. That is, the second and third input signals are redundant values that are added to the original data to correct errors in the transmitter. In addition, the second and third input signals may be signals that are turbocoding and interleaving in the transmitter.

For input signals Xto, Y1Kand Y2Kthe quantizer 310 outputs a quantized signal X'to, Y'toand Y'2Kin the iterative decoder 320 with a range of quantization, advanced beyond the range of the levels of transfer from-a to +A, according to a preferred variant implementation of the present invention.

An iterative decoder 320 may be turbodecoding. Each component decoder is an iterative decoder 320 decodes the input signal in many ways. Among them g Viterbi (SOVA). In the case of the SOVA algorithm should consider the dynamic range is increased by calculating the metrics of branching in the decoder, and it is necessary to provide predefined additional bits. Use the MAP also requires a pre-defined additional bits, as the calculation of the internal metrics of branching is determined by the baud rate code. The quantizer 310 preferred alternative implementation of the present invention can work with both types of decoders. The same coding parameters are used in both the above schemes. If QB quantizer 310 is n, then the decoder must process the input signal with a precision of n+m (m0). The number m of bits varies with the speed of transmission of the code composite decoder.

In Fig.4 depicts a block diagram of turbodecoding rate 1/3 code according to a preferred variant implementation of the present invention.

As shown in Fig.3 and 4, the first and second decoders 420 and 450 accept the signal values of the soft decision, each of which has many bits. The first and second decoders 420 and 450 can operate based on algorithms MAP or SOVA. The iterative decoder can be turbodecoding.

who in their respective levels, chosen from the set {10, 11, 12... 1n2-1} using the quantizer 310 (Fig.3). Then
X'K, Y'1K, Y'2K{10, 11, l2... 1n2-1} ..... (1)
The first adder 410 adds the received signal X'toand external information signal EXT2, which does not exist in the initial decoding is the result of decoding in the second decoder 450 and fed back from the second block 470 subtraction. The first decoder is activated by the output signal of the first adder 410 X'to+EXT2 and Y'1Kand outputs the signal X'to+EHT+EXT2. The first block 430 subtraction subtracts EXT2 from the output signal of the first decoder. Therefore, the signal at the node NA has the form X'to+EJT.

Interleaver 440 performs a permutation of the sequence of the signal output from the first block 430 subtraction through alternation and outputs a signal X'to+EJT. The second decoder 450 is activated by the output signal X'to+EHT the interleaver 440 and Y'2Kand then outputs a signal X'to+EHT+EXT2. Facing interleaver 460 reorder the bits of the signal X'toprior to their initial positions by turned interleave node NA, from the signal of the soft decision, which comes from facing the interleaver 460. The output signal of the second unit 470 of the subtraction is used as the external information signal EXT2 for the first decoder 430.

Characteristics of error correction can be improved, as the iteration continues, and then at a certain iteration, the output signal of the decoder becomes free from errors. In the device 480 hard decision output decoder, free from errors, decoding hard decision, and the signal tough decisions is supplied to the output buffer 490.

In addition, the dynamic range of the signals increased with the metric calculation in the first and second decoders 420 and 450. Therefore, each component decoder levels of representation of a signal will be equal to 2n+m-1. The value of n bits is equal to QB for the input signal (Fig.3), and m is the number of bits added depending on the dynamic range, which is the result of the calculation metric for decoding each component decoder. Usually m is determined by the baud rate code of the component decoders in an iterative decoder.

In accordance with a preferred embodiment of the present izopet is zestawienie input signal at pre-defined levels. So how to account for increased dynamic range obtained by computing the metric, QB required for metric values, is equal to n+m bits.

When using the SOVA decoder the increase of m bits occurs when calculating the path metric. The path metric at the current time is equal to the sum of the path metric accumulated to decode to a previous point in time (normalized metric, metric branching obtained by using the new input signal at the current time, and external information. Therefore, the dynamic range of the new path metric is greater than the input signal. The path metric at the current time k is calculated as
PM(k)=PM(k-1)+BM(k)

where ci(k) and uj(k) take values {+1, -1}.

In equation (2) PM(k) is the path metric calculated when the value of k, PM(k-l) is the path metric accumulated up to (k-1), BM(k) - metric transition when the value of k, X(k) - systematic input signal when the value of k, Yi(k) is the input of the i-th signal parity, ci(k) - i-e codeword parity, ui(k) - i-e systematic code word and EXT(k) - external information signal.

If in equation (2) baud rate code iterativelyui(k)+Yi(k)ci(k)+Y2(k)c2(k)+EXT(K).....(3)
From equation (3) it follows that BM(k) is the sum of four terms. Since ci(k) takes values -1 or +1, then
|BM(k)|<42n-1= 2n+2-1.....(4)
where n is the number of bits assigned to represent the input signal of the iterative decoder, |BM(k)| denotesand 2n-1the highest value of each summand. Assuming that the rate of transmission of the code of the component decoders is equal to 1/3 and bits (QB=n) representation of a signal assigned to an input side of an iterative decoder, two (=m) bits are added to n bits by increasing the dynamic range in the component decoder in accordance with equation (4). Representing the amount of BM(k) and PM(k-1), PM(k) has a dynamic range that can be greater than that of BM(k), but which can be maintained at a constant level due to normalization at each calculation. Therefore, when QB=n transfer rate 1/3 code, using (n+2) bits to compute the metric in the iterative decoder enables the decoder to perform decoding without compromising performance. Uracil way it can be modified in accordance with the transmission rate of the code.

Equation (4) obtained on the assumption that the number of bits that must be added to the BM(k), responds to the detection value of the upper limit BM(k). When speed transmission code 5 1/42n-1>|BM(k)|. The simulation proved that the iterative decoder allows you to decode without deterioration of its performance in the case when 2 bits are added to calculate the internal metrics in component decoder when the transfer rate 1/3 code. The number of terms summed in the calculation of the metric branching increases with decreasing speed transmission code component decoder. The resulting increase in BM(k) leads, in turn, increase m.

The coding parameters used in the preferred embodiment of the present invention are listed in table 1, where QB, L and QS parameters that define the characteristics of the quantizer. In the case of the quantizer with the same average pitch ratio between QL and QB is
QL=2OB-1..... (5)
and the relationship between QB, QMIN and QMAX
QMAX=2QB-1-1=-QMIN..... (6)
Qs is defined as 1/. If L is specified, then
QS = 1/(QMAX+1)/(A

Table 2 presents parameter combinations for optimal encoding options for turbodecoding SOVA according to a preferred variant implementation of the present invention.

If L=4, the range of quantization is greater than the transmission rate of four times. The latter describes the test was performed in the range of quantization extended in one, two and four times at a given QB. All combinations of each component decoder is QL=2QB+2. Under these conditions revealed a set of optimal quantization parameters.

Table 3 lists the simulation results of combinations of Eb/No-QB-QSA-L in relation to the probability of error per bit (PSA) and the probability of error per frame (wok) related to the parameter sets shown in table 2. Used by eternal a posteriori probability (log-MAP). The algorithm log-MAP is described in the work (Implementation and Performance of a Serial MAP Decoder for Use in an Iterative Turbo Decoder", Steven S. Pietrobon, Proc. , IEEE Int. Symp. On Information Theory, p.471, 1995). The simulations were performed in the direct auxiliary channel (F-SCH) in the system MDRC-2000, when the set speed 2 (RS2) in the mode N=1 and the data transfer rate 28 kbps (see RTT TIA-TR45.5" from 02 June 1998). Used by the test channel was channel abgs, and Eb/No0.5 dB and 1.0 dB.

From table 3 it can be seen that for a given QB, for turbodecoding need a broader range of quantization than the known method of quantization. For example, PSA and wok for L=1 at 1.0 dB 7-10 times greater than that for L=2 or 4 at 1.0 dB. That is, if L=1, then=1/QS has the smallest value. Therefore, the resolution is high, but the range of the quantizer (QR) is not sufficient, which results in performance deterioration. For turbodecoding need a broader range of values of QR for a given QB compared to the Viterbi decoder. When set to QB, turbodecoding has a lower resolution quantization, but the workspace (QR) of the quantizer is wider than that of the Viterbi decoder. Despite the lower resolution of TurboCache with regard to optimum L.

When L is from 2 to 4 at a given QB, performance turbodecoding are not bad, assuming that you want the QR, which is at least two times larger than the commonly used value QR. It is preferable to choose the optimal quantization parameters, when the signal-to-noise ratio (SNR) is 1.0 dB or more. Optimal values of QB and QS are respectively 6 and 8. It is assumed that the optimal settings to get QR four times greater than A, that is, L is equal to 4. Although good performance can be obtained when QB=7 & QS= 16, performance is slightly improved compared with the case where QB= 6 & QS=8, thus causing the dissipation of bits that represent the input signal. In conclusion, it should be noted that the performance deterioration caused by QR limited, it becomes more significant at higher SNR value.

When encoding of the signal is necessary to determine the quantization threshold. The quantization threshold is a limit value, which converts the input analog signal. Set threshold quantization is given by
T= TQMIN-1, TQMIN, TQMIN+1, . .., T-1, T0, T1allocated using the formula

where k=-QMIN, -QMIN+1, -QMIN+2,...-1, 0, 1, QMAX-1, QMAX, TQMIN-1= -and TQMAX= +.

The set of quantization thresholds for QB=6 and L=4, according to a preferred variant implementation of the present invention, it is translated in table 4. QL=63, and the representation is given in binary format with the addition of up to 2.=1/QS=A/8, QMAX=31, and QMIN=-31.

In Fig. 5 shows an algorithm illustrating a method of quantization iterative decoder according to a preferred variant implementation of the present invention.

As shown in Fig.5, the quantizer 310 (Fig.3) sets the encoding parameters at step 510. In this case, L must be installed in such a way that the range of quantization can be extended above and below And to assign different levels of the signals above or below And to the input analog signal Xto, Y1Kand Y2K. For turbodecoding acceptable range of quantization is greater than the range of levels of the transmission signals from-a to +A 21-22once at a given QB. QB establish given the lack of resolution of quantization due to the expansion of the range of quantization. QB with the first decoder must be installed with the increased dynamic range resulting from the calculation of the internal metric. If the baud rate code iterative decoder is equal to 1/4 or more, the number of bits representing the signal, each component decoder is the sum of the QB on the input side and the additional bits. QMAX is equal to 2QB-1-1, and QMIN equal to QMAX.

The quantizer 310 sets the clock count by 1 at step 520 and receives analog signals Xto, Y1Kand Y2Kat step 530. At step 540, the quantizer 310 multiplies each signal Xto, Y1Kand Y2Kon QS and outputs X'to, Y'1Kand Y'2Kusing the rounding operation. If the value of X'tomore than QMAX, then it is converted to QMAX, and if it is less than QMIN, then it is converted to QMIN. This also applies for values of Y'1Kand Y'2K.

The quantizer 310 determines whether the current clock count is greater than DLINE FRAME equal to the frame size of the input signal, which is decoded at step 550. If the clock count is less than GLINER, which means that the input signal is not at the end of the frame, a quantizer 310 returns to step 530. If the clock count is greater than GLINER, which means that the input signal is at the end of the frame is I for an iterative decoder, according to a preferred variant implementation of the present invention expands the range of quantization above the high boundary and below the low end of the range of levels of transmission from-a to +A, sets QB given the resulting lack of resolution quantization, sets the number of bits representing the signal, each component decoder takes into account the dynamic range defined by calculating their internal metrics, and presents criteria for the optimal quantization parameters, when the iterative decoder is made with regard to the actual situation.

Although the invention is shown and described with reference to specific preferred implementation, specialists in the art it should be clear that various changes in form and detail may be made without deviating from the scope and essence of the invention defined in the following claims.


Claims

1. The method of quantization for an iterative decoder, comprising the stages at which divide equally the received signal levels at predefined intervals, and by mentioning the words, the range of signal transmission from the transmitter, if the signal transmission from the transmitter is equal to m, and quantuum the level of the signal received in each period, using pre-defined intervals.

2. The method of quantization on p. 1, wherein the positive integer 1 = 2.

3. The method of quantization on p. 1, characterized in that a positive integer of 1 is 1.

4. The method of quantization on p. 1, wherein the iterative decoder comprises at least one component decoder, and at least one component decoder calculates the metric by using a predetermined number of bits, which is greater than the number of bits required to represent the received signal levels.

5. The method of quantization on p. 4, characterized in that a predetermined number of bits is two bits in the case where the iterative decoder has a speed code 1/4 or higher.

6. The method of quantization on p. 4, characterized in that each component decoder processes the input signal using the algorithm of maximum a posteriori probability (MAP) or algorithm soft output Viterbi (SOVA).

7. The method of quantization for iterative by using a scale factor quantization using from 5 to 7 bits of quantization in the range m21once more, where 1 is a positive integer, the range of signal transmission from the transmitter, if the signal transmission from the transmitter is equal to m, and quantuum the level of the signal received in each period, using pre-defined intervals.

8. The method of quantization on p. 7, wherein the positive integer 1 = 2.

9. The method of quantization on p. 7, characterized in that the number of quantization bits is 6.

10. The method of quantization on p. 9, characterized in that the scale factor quantization is equal to 8.

11. The method of quantization on p. 7, wherein the iterative decoder comprises at least one component decoder, and at least one component decoder calculates the metric by using a predetermined number of bits, which is greater than the number of bits required to represent the received signal levels.

12. The method of quantization on p. 11, characterized in that a predetermined number of bits is two bits in the case where the iterative decoder has a speed code 1/4 or higher.

13. The method of quantization on p. 11, characterized in that each component decoder decodes the input signals and (SOVA).

 

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