The present invention relates to a parity check matrix construction method for constructing a non-binary parity check matrix defining a non-binary LDPC code, more particularly relates to a parity check matrix construction system and a transmitter and receiver utilizing that non-binary parity check matrix.
In recent years, in the same way as the conventional turbo codes, LDPC (low density parity check) codes have begun to come into attention as error correction codes having superior properties close to the Shannon limit.
In particular, it is known that the decoding performance of these LDPC codes is equivalent to that of said turbo codes or exhibits superior characteristics to turbo codes when the code lengths are longer. For example, when the code lengths are tens of thousands of bits or more, sometimes the decoding performance of the turbo codes currently employed in third generation mobile phone systems is exceeded.
As LDPC codes, at the present time, binary type LDPC codes and non-binary type LDPC codes are known. If using the latter non-binary LDPC codes, compared with when using the former binary LDPC codes, there is the defect that the amount of processing increases. However, while there is this defect, if using the non-binary LDPC codes, even if said code lengths become shorter, the decoding performance is expected to be improved compared with when using binary LDPC codes.
Therefore, if the above defect can be eliminated by future technical development, it can be expected that the range of application of non-binary LDPC codes will expand. Therefore, if considering the method of constructing non-binary parity check matrices defining such non-binary LDPC codes, there will be the following problems.
When constructing a binary parity check matrix defining a binary code, it is sufficient to just determine at what positions in the matrix (what row and what column) to arrange the elements 1, that is, the non-zero elements, in a matrix comprised of the elements 0 and elements 1.
However, when constructing a non-binary parity check matrix defining the non-binary code, it is not sufficient to just determine the positions of said non-zero elements. It is necessary to also determine the values of the non-binary elements constituted by the n-ary elements (1, 2, 3, 4 . . . )
If studying the method for determining the values of the n-ary elements, in the past, there has been no clear standard or rule for the method of determination. In actuality, the general practice has been to randomly select the values of the n-ary elements (random selection method). For this reason, there was the problem that the performance ended up fluctuating in accordance with the selected pattern and stable, good performance could not be obtained.
Therefore, an object of the present invention, in consideration of said problem, is to provide a method of construction of an algorithm for constructing non-binary parity check matrices which give much better and stable performance compared with the case by the conventional random selection.
Further, an object of the invention is to provide a system for construction of said non-binary parity check matrices and further to provide a transmitter and receiver utilizing said non-binary parity check matrices.
To achieve said objects, the present invention is characterized by
(1) setting a binary parity check matrix of a binary LDPC code,
(2) detecting the cycles included in the binary parity check matrix, and
(3) selecting the non-binary elements in partial matrices corresponding to the detected cycles so that the determinants of the partial matrices do not become 0,
that selected non-binary elements forming the non-zero elements in the non-binary parity check matrix.
In the figure,
At step S11, a binary parity check matrix of a binary LDPC code having the same configuration as a non-binary parity check matrix is set,
at step S12, the cycles included in the set binary parity check matrix are detected,
at step S13, the non-binary elements in partial matrices corresponding to the cycles detected in the non-binary parity check matrix are selected so that the determinants for the partial matrices do not become zero,
where, said selected non-binary elements form the non-zero elements in the non-binary parity check matrix.
The thus selected non-binary elements form the non-zero elements in the non-binary parity check matrix. This means that small cycles where the determinants of the corresponding partial matrices become zero are prevented from being included in the non-binary parity check matrix. That is, the non-zero elements in the non-binary parity check matrix are selected so that there are no small weight (few non-zero element) codewords. The reason why to do so is that, as is well known, a parity check matrix gives a better decoding performance the smaller the number of small weight codewords, that is, small non-zero element codewords, included.
Here, to facilitate understanding of the present invention, the background of the art relating to the present invention will be explained.
An LDPC code of a code rate R and a code length N is defined by an M row and N column parity check matrix H as a linear block code. This LDPC code is called a non-binary LDPC code when the parity check matrix H is comprised of elements of a non-binary Galois field.
Here, a Galois field with q number of elements is expressed as GF(q). In the non-binary case, q>2. In particular, q of a power of 2 is generally used. For differentiation, an LDPC code of q=2 is called a “binary LDPC code”. Using this parity check matrix H, the LDPC code is defined as Hc=0. Here, c is the N row 1 column codeword vector. That is, the any vector c satisfying the above equation Hc=0 is defined as a codeword of the LDPC code defined by a parity check matrix H. The parity check matrix of this LDPC code is characterized in that the density of the non-zero elements is small.
Note that the LDPC code is decoded on a Tanner graph corresponding to the parity check matrix H (see later mentioned
For the decoding, a BP (belief propagation) algorithm on said Tanner graph is used. This is a type of repeated decoding. By exchanging information (messages) between the variable nodes and check nodes, the likelihood of the bits is converged to the optimal value. The reception performance of the LDPC code depends to a large degree on this Tanner graph, that is, the parity check matrix H, so many systems have been devised to construct good parity check matrices. Specifically, it is known that elimination of small cycles in the parity check matrix greatly improves the performance. Almost all parity check matrix construction systems focus on elimination of short length cycles. Note that in the Tanner graph of the later explained
The present invention, as explained above, does not aim at elimination of small cycles in a parity check. Its object is to select values of the non-zero elements in accordance with a certain set algorithm (the above
Below, embodiments of the present invention will be explained. The present invention takes note of a non-binary LDPC code using a parity check matrix of the column weight 2. In general, in a regular binary LDPC code, it is reported that the decoding performance by a parity check matrix of the column weight 3 is good. However, in a regular non-binary LDPC code, as the Galois field increases in dimensions, usually with q=8 or so, the decoding performance of a parity check matrix with a column weight 2 exceeds that of the column weight 3. For this reason, even if limiting the embodiment of the present invention to a parity check matrix of the column weight 2, there is not that much of a problem. Note that even if considering the optimal distribution of the irregular column weight, as q becomes larger, it is shown that the optimal column weight distribution approaches a regular weight 2 (see following document).
[Document]
X. Y. Hu, E. Eleftheriou, and D. M. Arnold, “Regular and Irregular Progressive Edge-Growth Tanner Graphs,” IEEE Trans. Inform. Theory, vol. 51, pp. 386-398, January 2005.
Next, refer to
The “c” of said Hc means codeword. That is, this is a codeword linked one-to-one with each of the many “information bits” to be encoded and transmitted from the transmitting side. As shown in
Aa+Cb=0
Bb+Ec=0
Db+Fc=0,
so the a, b, and c forming the non-zero elements of the codeword c are determined (note: the codeword c differs from the non-zero element c).
Therefore, when Hc=0 stands, there is the codeword c. In this case, so long as the determinant of the partial matrix corresponding to the cycle CL, that is, det| |, is 0, Hc=0 could stand with non-zero vector c. The relationship of the two is shown by the double-headed arrow of
However, in
What is to be noted here is that in a binary matrix comprised of elements 0 and elements 1, the determinant, that is, the det| | at the right side of
However, in a non-binary matrix, as shown in
In short, the parity check matrix configuration algorithm in the present invention takes note of the fact that in a parity check matrix H of the column weight 2, the matrix H comprised of the cycle CL corresponds to the codeword c and there is a corresponding codeword only when the determinant of the matrix is zero, finds cycles in the parity check matrix, and selects the non-binary non-zero elements so that the determinant does not become 0. Due to this, it becomes possible to increase the smallest code weight of the codeword c and improve the existing decoding performance (reception performance).
In the graph of
Here, compared with the existing conventional example (random selection method), according to the present invention, at the block error rate (BLER) being ten to the minus fifth, it is learned that an improvement of the reception performance of about 0.1 to 1.0 dB is achieved. In addition to this, when employing a non-binary parity check matrix constructed using the prior art, the reception performance fluctuates. However, when employing a non-binary parity check matrix constructed according to the present invention, it is learned that the reception performance, that is, the decoding performance, becomes extremely stable without fluctuation.
Note that K (=N−M) shown in
Next, the method of construction of a parity check matrix based on an embodiment of the present invention will be explained specifically.
Referring to
At step S21 (
At step S22, the i-th column in the N columns in the matrix of
At step S23, the value of the non-zero element “1” of the 1st column and 1st row (i=1) in
At step S24, all cycles of the length L0 (explained later) or less included in the partial matrices created from the 1st column to the i-th column, that is, the partial matrices created at the left from the i-th column in question are detected (the cycles at the right from the i-th column are not noted at all).
Regarding detection of the cycles, for example, referring to the above-mentioned
Not just one loop forming such a cycle is detected in one matrix. Usually, a plurality of cycles is detected. The length of a cycle means, for example, if referring to
The values of the non-zero elements are selected so that the determinant does not become zero for each such detected cycle, but there are cases where the determinants will not become zero for all detected cycles. In this case, said lengths end up being limited to not more than a predetermined upper limit length. This is because it is sufficient that a certain size of codeword be obtained. Note that it is also possible to detect only cycles of less than the upper limit length from the start to realize greater efficiency of the routine.
Further, if expressing this quantitatively, the length L0 of the cycle is made that upper limit value. Further, this upper limit length is determined by
Lmin+2[(Lmin−2)/4]
Here, Lmin indicates the length of the shortest cycle included in the binary parity check matrix, while [ ] indicates that, when expressing X as [X], that this [X] is a highest integer not exceeding X. Note that the grounds for deriving the formula of the upper limit value are explained in detail with reference to
Above, the detection of cycles was explained in detail, but at step S25 (
Step S26: When it is judged that no cycles were detected at step 25 (No), the value of the second non-zero element (taking as an example the i=1 of
It is possible to completely randomly select all elements in the middle of one cycle in this way because so long as suitably selecting the single last unselected element in the later explained step S28, it is possible to make the determinant of the partial matrix corresponding to said cycle non-zero.
In short, at said step S26, the selection at the selection step S13 (
Returning to said step S25, here, if cycles are detected (YES), the routine proceeds to step S28.
At step S28, the value of the second non-zero element of the i-th column is selected from the GF(q) elements (1 to 7) so that the determinants of the matrices corresponding to all cycles do not become zero.
In short, the above selection (S13) is executed by successively assigning one of said n-ary elements (1 to 7) to the elements 1 in the matrix of
After this selection, the routine proceeds to step S27. After the end of step S26 as well, the routine proceeds to step S27.
Step S27: After determining the non-binary non-zero elements shown in
At step S29, so long as i>N (in
The above explanation of the operation was made assuming the case where both the binary parity check matrix (
Above, the method of construction of a parity check matrix based on the present invention was explained in detail, but the idea of the present invention can also be realized as a parity check matrix construction system. One example will be shown below.
This parity check matrix construction system 10 is a parity check matrix construction system for constructing a non-binary parity check matrix defining a non-binary LDPC code. Here, the matrix setter 11 sets a binary parity check matrix of a binary LDPC code (
Further, the parity check matrix output unit 14 determines the non-zero elements (1 to 7) in the non-binary parity check matrices by said selected non-binary elements and outputs the non-binary parity check matrix.
The above explained parity check matrix construction method (
First, looking at the transmitter 20, this transmitter 20 is a transmitter including an LDPC encoder 22 which receives as input information bits Ib to be encoded and transmitted and encodes these by a non-binary LDPC code, a encoding side parity check matrix holder 23 which holds a non-binary parity check matrix used at the time of this coding, and a modulator 25 which modulates the encoded information bits Ib from the LDPC encoder 22 and transmits them to the reception side.
The point to note here is that the encoding side parity check matrix holder 23 holds the non-binary parity check matrix which is identical to the one used at transmitter side.
This transmitter 20 is further provided with an input side converter 21 provided at the input side of the LDPC encoder 22 for converting the binary data constituted by the information bits Ib to non-binary n-ary symbols and an output side converter 24 provided at the output side of the LDPC encoder 22 for converting the information bits comprised of the non-binary n-ary symbols encoded by the LDPC encoder 22 to binary data.
Said input side converter 21 makes the LDPC encoder 22 operating by the n-ary elements match with the binary information bits Ib, taking as an example the case of GF(4), by performing the conversion to n-ary elements of
00->0
1->1
10->2
11->3
(GF(2)->GF(4)), while
said output side converter 24 makes the output of the n-ary elements from the LDPC encoder 22 operate on a binary basis, similarly taking as an example the case of GF(4), by performing the binary conversion of
0->00
1->01
2->10
3->11
(GF(4)->GF(2)).
Looking at the receiver 40 shown at the bottom part of
The point to note here is that the decoding side parity check matrix holder 44 holds the non-binary parity check matrix constructed by the parity check matrix construction system 10 (
This receiver 40 is further provided with an input side converter 42 provided at the input side of the LDPC decoder 43 for converting the binary demodulated bits expressed with likelihood from the demodulator 41 to non-binary n-ary symbols and an output side converter 45 provided at the output side of the LDPC decoder 43 for converting the information bits Ib comprised of the non-binary n-ary symbols decoded by the LDPC decoder 43 to binary data. That is, this output side converter 45 performs the conversions:
0->00
1->01
2->10
3->11
(GF(4)->GF(2)).
On the other hand, said input side converter 42 is suitably called a likelihood converter from its functions. This groups the binary likelihood obtained from the demodulator 41 for every q bits and converts each to one symbol non-binary likelihood. As an example, the conversion GF(2)->GF(4) becomes:
Q0=P00P10
Q0=P00P11
Q2=P01P10
Q3=P01P11.
Here, P10 is the probability of the first bit before conversion being 0, while Q0 expresses the probability of the symbol after conversion being 0. The thus obtained symbol likelihood is input to the decoder 43.
In this decoder 43, the already explained Tanner graph is used for decoding the LDPC code.
Next, a modification of the transmitter 20 shown in
On the other hand, the non-binary LDPC code is used for information of a short code length where high quality (Q0S) communication is required such as control information or broadcast information in a cellular network. If illustrating the above idea, the result becomes
Expressing this overall, this transmitter 20′ is a transmitter where the transmission information to be encoded and transmitted includes first transmission information of a long code length (for example, Ib) and second information of a shorter code length than said first transmission information and requiring a higher quality than said first information (for example Ict or Ibr). This transmitter 20′ is provided with a binary LDPC encoder 26b which receives as input first transmission information (Ib) and encodes this by a binary LDPC code, non-binary LDPC encoders (22ct, 22br) which receive as input second transmission information (Ict, Ibr) and encode these by a non-binary LDPC code, a first modulator 25b which modulates the encoded output from the binary LDPC encoder 26b, second modulators (25ct, 25br) which modulate the encoded outputs from the non-binary LDPC encoder (22ct, 22br), and a transmitting mean (28, 29) which combines the modulated outputs from these first and second modulators and transmits the result to the reception side.
Here, the non-binary LDPC encoders (22ct, 22br) perform the above encoding by the non-binary parity check matrix constructed by the parity check matrix construction system 10 (
Specifically, the binary LDPC encoder 26b receives as input the information bits Ib in wireless communication as said first transmission information, while the non-binary LDPC encoder 22ct receives as input control information Ict in wireless communication as said second transmission information.
Further, the binary LDPC encoder 26b receives as input the information bits Ib in wireless communication as said first transmission information, while the non-binary LDPC encoder 22br receives as input the broadcast information Ibr in wireless communication as said second transmission information.
Still further, the system is provided with input side converters (21ct, 21br) provided at the input sides of the LDPC encoders (22ct, 22br) for converting binary data constituted by second transmission information (Ict, Ibr) to non-binary n-ary symbols and output side converters (24ct, 24br) provided at the output sides of LDPC encoders (22ct, 22br) for converting second transmission information (Ict, Ibr) comprised of non-binary n-ary symbols encoded by the LDPC encoders (22ct, 22br) to binary data.
The above transmitting means (28, 29) is comprised of a time switch 28 and transmission antenna 29, the coding information transmitted from this transmission antenna 29 is transmitted to the receiver (corresponding to 40 in
Finally, the grounds by which the above upper limit length is derived by
Lmin+2[(Lmin−2)/4]
will be explained in detail.
Consider a regular LDPC code with a column weight of 2. As explained above, a cycle where the determinant of the corresponding partial matrix is 0 has a corresponding codeword. However, not all of the codewords correspond to cycles. Codewords are classified into two types: codewords corresponding to cycles (cycle codewords) and codewords not corresponding to cycles (non-cycle codewords). For example, the (partial) parity check matrix H shown in
The present invention was explained above with reference to the provision of an algorithm selecting the elements of the parity check matrix of the non-binary LDPC code so that there are no codewords with small weight corresponding to short length cycles. Even if applying this algorithm to cycles of a certain length or more, if there are non-cycle codewords of less weight, there is no longer any merit to application of this.
Therefore, it is learned that the maximum weight of the cycle codewords avoided by application of the algorithm of the present invention may be one smaller than the smallest weight of the non-cycle codewords. To find the smallest weight of the non-cycle codewords, the fact that in a regular LDPC code with a column weight of 2, the partial parity check matrices corresponding to the codewords always include cycles inside is utilized. Further, to facilitate understanding of the problem, the charts such as
First, a chart corresponding to the cycle of the shortest length (Lmin=2k) is prepared (corresponding to top halves of
Therefore, in this case, the algorithm of the present invention should be applied to cycles shorter than a cycle corresponding to a codeword of the weight 5 (length 10). That is, the maximum length of the cycles considered becomes 8. Generalizing this, as shown in
L0=Lmin+[(Lmin−2)/4]
Filing Document | Filing Date | Country | Kind | 371c Date |
---|---|---|---|---|
PCT/EP2006/003789 | 3/30/2006 | WO | 00 | 5/20/2009 |
Publishing Document | Publishing Date | Country | Kind |
---|---|---|---|
WO2007/112767 | 10/11/2007 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
20030235166 | Son et al. | Dec 2003 | A1 |
20060020870 | Hocevar | Jan 2006 | A1 |
20070011568 | Hocevar | Jan 2007 | A1 |
20080141098 | Chae et al. | Jun 2008 | A1 |
20090259915 | Livshitz et al. | Oct 2009 | A1 |
20100211847 | Livshitz et al. | Aug 2010 | A1 |
20110307755 | Livshitz et al. | Dec 2011 | A1 |
Number | Date | Country | |
---|---|---|---|
20090287981 A1 | Nov 2009 | US |