111111
`
`1111111111111111111111111111111111111111111111111111111111111
`US007916781B2
`
`c12) United States Patent
`Jin et al.
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 7,916,781 B2
`Mar.29,2011
`
`f54)
`
`(75)
`
`SERIAL CONCATENATION OF
`INTERLEAVED CONVOLUTIONAL CODES
`FORMING TURBO-LIKE CODES
`
`Inventors: Hui Jin, Glen Gardner, NJ (US); Aamod
`Khandekar, Pasadena, CA (US);
`Robert J. McEliece, Pasadena, CA (US)
`
`(73)
`
`Assignee: California Institute of Technology,
`Pasadena, CA (US)
`
`( *)
`
`Notice:
`
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 424 days.
`
`(21)
`
`Appl. No.: 12/165,606
`
`(22)
`
`Filed:
`
`Jun. 30, 2008
`
`(65)
`
`Prior Publication Data
`
`US 2008/0294964 AI
`
`Nov. 27, 2008
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`5,181,207 A *
`111993 Chapman ...................... 714/755
`2/1995 Rhines eta!.
`5,392,299 A
`6/1996 Lin
`5,530,707 A
`511998 Seshadri et a!.
`5,751,739 A
`9/1998 Meyer
`5,802,115 A
`3/1999 Wang eta!.
`5,881,093 A
`1/2000 Wang
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`212000 Divsalar eta!.
`6,023,783 A
`212000 Chennakeshu eta!.
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`212000 Bliss
`6,032,284 A
`3/2000 Wang
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`7/2000 Miller et a!.
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`6,195,396 B1 *
`2/2001 Fang et al ..................... 375/261
`6,396,423 B1
`5/2002 Laumen et al.
`6,437,714 B1
`8/2002 Kim et al.
`6,732,328 B1 *
`5/2004 McEwen et al ............... 714/795
`6,859,906 B2
`2/2005 Hanunons eta!.
`7,089,477 B1
`8/2006 Divsalar eta!.
`(Continued)
`
`Related U.S. Application Data
`(63) Continuation of application No. 11/542,950, filed on
`Oct. 3, 2006, now Pat. No. 7,421,032, which is a
`continuation of application No. 09/861,102, filed on
`May 18, 2001, now Pat. No. 7,116,710, which is a
`continuation-in-part of application No. 09/922,852,
`filed on Aug. 18, 2000, now Pat. No. 7,089,477.
`
`(60) Provisional application No. 60/205,095, filed on May
`18, 2000.
`
`(51)
`
`Int. Cl.
`H04B 1166
`(2006.01)
`(52) U.S. Cl. ........ 375/240; 375/285; 375/296; 714/801;
`714/804
`(58) Field of Classification Search . ... ... ... ... .. ... 3 7 5/240,
`375/240.24, 254, 285, 295, 296, 260; 714/755,
`714/758,800,801,804,805
`See application file for complete search history.
`
`OTHER PUBLICATIONS
`
`Benedetto, S., et a!., "A Soft-Input Soft-Output APP Module for
`Iterative Decoding of Concatenated Codes," IEEE Communications
`Letters, 1(1):22-24, Jan. 1997.
`
`(Continued)
`
`Primary Examiner- Dac V Ha
`(74) Attorney, Agent, or Firm- Perkins Coie LLP
`
`(57)
`
`ABSTRACT
`
`A serial concatenated coder includes an outer coder and an
`inner coder. The outer coder irregularly repeats bits in a data
`block according to a degree profile and scrambles the
`repeated bits. The scrambled and repeated bits are input to an
`inner coder, which has a rate substantially close to one.
`
`22 Claims, 5 Drawing Sheets
`
`200~
`
`k '/ u
`
`k/
`u
`
`OUTER
`
`n/
`v
`\___ 202
`
`p
`
`n/
`w
`
`INNER
`
`\___ 204
`
`\___ 206
`
`Hughes, Exh. 1005, p. 1
`
`

`

`US 7,916,781 B2
`Page 2
`
`U.S. PATENT DOCUMENTS
`2001/0025358 A1
`9/2001 Eidson eta!.
`
`OTHER PUBLICATIONS
`
`Benedetto, S., eta!., "A Soft-Input Soft-Output Maximum A Poste(cid:173)
`riori (MAP) Module to Decode Parallel and Serial Concatenated
`Codes," The Telecommunications and Data Acquisition Progress
`Report (TDA PR 42-127), pp. 1-20, Nov. 1996.
`Benedetto, S., et al., "Bandwidth efficient parallel concatenated cod(cid:173)
`ing schemes," Electronics Letters, 31(24):2067-2069, Nov. 1995.
`Benedetto, S., eta!., "Design of Serially Concatenated Interleaved
`Codes," ICC 97, vol. 2, pp. 710-714, Jun. 1997.
`Benedetto, S., eta!., "Parallel Concatenated Trellis Coded Modula(cid:173)
`tion," ICC 96, vol. 2, pp. 974-978, Jun. 1996.
`Benedetto, S., eta!., "Serial Concatenated Trellis Coded Modulation
`with Iterative Decoding," Proceedings 1997 IEEE International
`Symposium on Information Theory (!SIT), Ulm, Germany, p. 8, Jun.
`29-Jul. 4, 1997.
`Benedetto, S., et al., "Serial Concatenation of Interleaved Codes:
`Performace Analysis, Design, and Iterative Decoding," The Telecom(cid:173)
`munications andDataAcquisitionProgress Report(TDAPR 42126),
`pp. 1-26, Aug. 1996.
`Benedetto, S., et a!., "Serial concatenation of interleaved codes:
`performance analysis, design, and iterative decoding," Proceedings
`1997 IEEE International Symposium on Information Theory (!SIT),
`Ulm, Germany, p. 106, Jun. 29-Jul. 4, 1997.
`Benedetto, S., et al., "Soft-Output Decoding Algorithms in Iterative
`Decoding of Turbo Codes," The Telecommunications and Data
`Acquisition Progress Report ( TDA P R 4 2-12 4), pp. 63-87, Feb. 1996.
`Berrou, C., eta!., "Near Shannon Limit Error--Correcting Coding
`and Decoding: Turbo Codes," ICC 93, vol. 2, pp. 1064-1070, May
`1993.
`Digital Video Broadcasting (DVB )-User guidelines for the second
`generation system for Broadcasting, Interactive Services, News
`Gathering and other broadband satellite applications (DVB-S2),
`ETSI TR 102 376 Vl.l.1 Technical Report, pp. 1-104 (p. 64), Feb.
`2005.
`Divsalar, D., et al., "Coding Theorems for 'Turbo-Like' Codes,"
`
`Proceedings of the 361h Annual Allerton Conference on Communica(cid:173)
`tion, Control, and Computing, Monticello, Illinois, pp. 201-210, Sep.
`1998.
`
`Divsalar, D., eta!., "Effective free distance of turbo codes," Electron(cid:173)
`ics Letters, 32(5):445-446, Feb. 1996.
`Divsalar, D., et al., "Hybrid Concatenated Codes and Iterative Decod(cid:173)
`ing," Proceedings 1997 IEEE International Symposium on Informa(cid:173)
`tion Theory (!SIT), Ulm, Germany, p. 10, Jun. 29-Jul. 4, 1997.
`Divsalar, D., eta!., "Low-Rate Turbo Codes for Deep-Space Com(cid:173)
`munications," Proceedings 1995 IEEE International Symposium on
`Information Theory (!SIT), Whistler, BC, Canada, p. 35, Sep. 1995.
`Divsalar, D., eta!., "Multiple Turbo Codes for Deep-Space Commu(cid:173)
`nications," The Telecommunications and Data Acquisition Progress
`Report (TDA PR 42-121), pp. 66-77, May 1995.
`Divsalar, D., eta!., "Multiple Turbo Codes," MIL COM '95, vol. 1, pp.
`279-285, Nov. 1995.
`Divsalar, D., et al., "On the Design of Turbo Codes," The Telecom(cid:173)
`munications and Data Acquisition Progress Report (TDA PR
`42-123), pp. 99-121, Nov. 1995.
`Divsalar, D., et a!., "Serial Turbo Trellis Coded Modulation with
`Rate-1 Inner Code," Proceedings 2000 IEEE International Sympo(cid:173)
`sium on Information Theory (!SIT), Sorrento, Italy, pp. 194, Jun.
`2000.
`Divsalar, D., eta!., "Turbo Codes for PCS Applications," IEEE ICC
`'95, Seattle, WA, USA, vol. 1, pp. 54-59, Jun. 1995.
`Jin, H., eta!., "Irregular Repeat-Accumulate Codes," 2nd Interna(cid:173)
`tional Symposium on Turbo Codes, Brest, France, 25 pages, Sep.
`2000.
`Jin, H., et al., "Irregular Repeat-Accumulate Codes," 2"d Interna(cid:173)
`tional Symposium on Turbo Codes &Related Topics, Brest, France, p.
`1-8, Sep. 2000.
`Richardson, T.J., eta!., "Design of Capacity-Approaching Irregular
`Low-Density Parity-Check Codes," IEEE Transactions on Informa(cid:173)
`tion Theory, 47(2):619-637, Feb. 2001.
`Richardson, T.J., eta!., "Efficient Encoding of Low-Density Parity(cid:173)
`Check Codes," IEEE Transactions on
`Information Theory,
`47(2):638-656, Feb. 2001.
`Wiberg, N., et a!., "Codes and Iterative Decoding on General
`Graphs," Proceedings 1995 IEEE International Symposium on Infor(cid:173)
`mation Theory (!SIT), Whistler, BC, Canada, p. 468, Sep. 1995.
`Aji, S.M., eta!., "The Generalized Distributive Law," IEEE Trans(cid:173)
`actions on Information Theory, 46(2):325-343, Mar. 2000.
`Tanner, R.M., "A Recursive Approach to Low Complexity Codes,"
`IEEE Transactions on Information Theory, 27(5):533-547, Sep.
`1981.
`* cited by examiner
`
`Hughes, Exh. 1005, p. 2
`
`

`

`U.S. Patent
`
`Mar.29,2011
`
`Sheet 1 of 5
`
`US 7,916,781 B2
`
`~ ,._
`\...
`
`N
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`Cl
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`.,._
`
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`
`Hughes, Exh. 1005, p. 3
`
`

`

`U.S. Patent
`
`Mar.29,2011
`
`Sheet 2 of 5
`
`US 7,916,781 B2
`
`_)
`
`cc
`UJ z
`z
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`Hughes, Exh. 1005, p. 4
`
`

`

`U.S. Patent
`
`Mar.29,2011
`
`Sheet 3 of 5
`
`US 7,916,781 B2
`
`Variable Node
`Fraction of nodes
`degree i
`, .... -,
`,
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`302
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`
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`
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`
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`
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`
`Hughes, Exh. 1005, p. 5
`
`

`

`U.S. Patent
`
`Mar. 29, 2011
`
`Sheet 4 of 5
`
`US 7,916,781 B2
`
`®--------
`
`FIG. 5A
`
`304
`
`w
`
`v
`
`304
`
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`
`Hughes, Exh. 1005, p. 6
`
`

`

`U.S. Patent
`
`Mar.29,2011
`
`Sheet 5 of 5
`
`US 7,916,781 B2
`
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`Hughes, Exh. 1005, p. 7
`
`

`

`US 7,916,781 B2
`
`1
`SERIAL CONCATENATION OF
`INTERLEAVED CONVOLUTIONAL CODES
`FORMING TURBO-LIKE CODES
`
`CROSS-REFERENCE TO RELATED
`APPLICATIONS
`
`This application is a continuation of U.S. application Ser.
`No. 11/542,950, filed Oct. 3, 2006 now U.S. Pat. No. 7,421,
`032, which is a continuation of U.S. application Ser. No.
`09/861,102, filed May 18,2001, now U.S. Pat. No. 7,116,710,
`which claims the priority ofU.S. Provisional Application Ser.
`No. 60/205,095, filed May 18, 2000, and is a continuation(cid:173)
`in-part ofU.S. application Ser. No. 09/922,852, filed Aug. 18,
`2000, now U.S. Pat. No. 7,089,477. The disclosure of the
`prior applications are considered part of (and are incorporated
`by reference in) the disclosure of this application.
`
`GOVERNMENT LICENSE RIGHTS
`
`The U.S. Government has a paid-up license in this inven(cid:173)
`tion and the right in limited circumstances to require the
`patent owner to license others on reasonable terms as pro(cid:173)
`vided for by the terms of Grant No. CCR-9804793 awarded
`by the National Science Foundation.
`
`BACKGROUND
`
`5
`
`2
`into two or more sub-blocks, and bits in different sub-blocks
`are repeated a different number of times according to a
`selected degree profile. The outer coder may include a
`repeater with a variable rate and an interleaver. Alternatively,
`the outer coder may be a low-density generator matrix
`(LDGM) coder.
`The repeated and scrambled bits are input to an inner coder
`that has a rate substantially close to one. The inner coder may
`include one or more accumulators that perform recursive
`10 modulo two addition operations on the input bit stream.
`The encoded data output from the inner coder may be
`transmitted on a channel and decoded in linear time at a
`destination using iterative decoding techniques. The decod-
`15 ing techniques may be based on a Tanner graph representation
`of the code.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`20
`
`FIG. 1 is a schematic diagram of a prior "turbo code"
`system.
`FIG. 2 is a schematic diagram of a coder according to an
`embodiment.
`FIG. 3 is a Tanner graph for an irregular repeat and accu-
`25 mulate (IRA) coder.
`FIG. 4 is a schematic diagram of an IRA coder according to
`an embodiment.
`FIG. SA illustrates a message from a variable node to a
`check node on the Tanner graph of FIG. 3.
`FIG. SB illustrates a message from a check node to a
`variable node on the Tanner graph of FIG. 3.
`FIG. 6 is a schematic diagram of a coder according to an
`alternate embodiment.
`FIG. 7 is a schematic diagram of a coder according to
`35 another alternate embodiment.
`
`DETAILED DESCRIPTION
`
`Properties of a channel affect the amount of data that can be
`handled by the channel. The so-called "Shannon limit" 30
`defines the theoretical limit of the amount of data that a
`channel can carry.
`Different techniques have been used to increase the data
`rate that can be handled by a channel. "Near Shannon Limit
`Error-Correcting Coding and Decoding: Turbo Codes," by
`Berrou eta!. ICC, pp 1064-1070, (1993), described a new
`"turbo code" technique that has revolutionized the field of
`error correcting codes. Turbo codes have sufficient random(cid:173)
`ness to allow reliable communication over the channel at a
`high data rate near capacity. However, they still retain suffi(cid:173)
`cient structure to allow practical encoding and decoding algo(cid:173)
`rithms. Still, the technique for encoding and decoding turbo
`codes can be relatively complex.
`A standard turbo coder 100 is shown in FIG. 1. A block of
`k information bits is input directly to a first coder 102. A k bit
`interleaver 106 also receives the k bits and interleaves them
`prior to applying them to a second coder 104. The second
`coder produces an output that has more bits than its input, that
`is, it is a coderwithratethatis less than 1. The coders 102,104
`are typically recursive convolutional coders.
`Three different items are sent over the channel 150: the
`original k bits, first encoded bits 110, and second encoded bits
`112. At the decoding end, two decoders are used: a first
`constituent decoder 160 and a second constituent decoder
`162. Each receives both the original k bits, and one of the
`encoded portions 110, 112. Each decoder sends likelihood
`estimates of the decoded bits to the other decoders. The esti(cid:173)
`mates are used to decode the uncoded information bits as
`corrupted by the noisy channel.
`
`FIG. 2 illustrates a coder 200 according to an embodiment.
`40 The coder 200 may include an outer coder 202, an interleaver
`204, and inner coder 206. The coder may be used to format
`blocks of data for transmission, introducing redundancy into
`the stream of data to protect the data from loss due to trans(cid:173)
`mission errors. The encoded data may then be decoded at a
`45 destination in linear time at rates that may approach the chan(cid:173)
`nel capacity.
`The outer coder 202 receives the uncoded data. The data
`may be partitioned into blocks of fixed size, say k bits. The
`outer coder may be an (n,k) binary linear block coder, where
`50 n>k. The coder accepts as input a block u ofk data bits and
`produces an output block v ofn data bits. The mathematical
`relationship between u and vis v=T0u, where T0 is an nxk
`matrix, and the rate of the coder is kin.
`The rate of the coder may be irregular, that is, the value of
`55 T 0 is not constant, and may differ for sub-blocks of bits in the
`data block. In an embodiment, the outer coder 202 is a
`repeater that repeats the k bits in a block a number of times q
`to produce a block with n bits, where n=qk. Since the repeater
`has an irregular output, different bits in the block may be
`60 repeated a different number of times. For example, a fraction
`of the bits in the block may be repeated two times, a fraction
`of bits may be repeated three times, and the remainder of bits
`may be repeated four times. These fractions define a degree
`sequence, or degree profile, of the code.
`The inner coder 206 may be a linear rate-1 coder, which
`means that then-bit output block x can be written as x=Tiw,
`where Tiis anonsingularnxnmatrix. The innercoder210 can
`
`SUMMARY
`
`A coding system according to an embodiment is config(cid:173)
`ured to receive a portion of a signal to be encoded, for
`example, a data block including a fixed number of bits. The 65
`coding system includes an outer coder, which repeats and
`scrambles bits in the data block. The data block is apportioned
`
`Hughes, Exh. 1005, p. 8
`
`

`

`US 7,916,781 B2
`
`3
`have a rate that is close to 1, e.g., within 50%, more preferably
`10% and perhaps even more preferably within 1% of 1.
`In an embodiment, the inner coder 206 is an accumulator,
`which produces outputs that are the modulo two (mod-2)
`partial sums of its inputs. The accumulator may be a truncated
`rate-1 recursive convolutional coder with the transfer func(cid:173)
`tion 1/(1 +D). Such an accumulator may be considered a block
`coder whose input block [xu ... , xn] and output block
`[y 1 , . . . , y nl are related by the formula
`
`4
`accumulator code. The interleaver 204 in FIG. 2 may be
`excluded due to the randonmess already present in the struc(cid:173)
`ture of the LDGM code.
`If the permutation performed in permutation block 310 is
`fixed, the Tanner graph represents a binary linear block code
`with k information bits (u1 , . . . , uk) and r parity bits
`(x 1 , . . . , xr), as follows. Each of the information bits is
`associated with one of the information nodes 302, and each of
`10 the parity bits is associated with one of the parity nodes 306.
`The value of a parity bit is determined uniquely by the con(cid:173)
`dition that the mod-2 sum of the values of the variable nodes
`connected to each of the check nodes 304 is zero. To see this,
`set x0 =0. Then if the values of the bits on the ra edges coming
`15 out the permutation box are
`
`Xj = Xj-1 + .L V(j-l)R+i
`
`R
`
`i-1
`
`20
`
`40
`
`where "EB" denotes mod-2, or exclusive-OR (XOR), addition.
`An advantage of this system is that only mod-2 addition is 25
`necessary for the accumulator. The accumulator may be
`embodied using only XOR gates, which may simplify the
`design.
`The bits output from the outer coder 202 are scrambled
`before they are input to the inner coder 206. This scrambling
`may be performed by the interleaver 204, which performs a
`pseudo-random permutation of an input block v, yielding an
`output block w having the same length as v.
`The serial concatenation of the interleaved irregular repeat
`code and the accumulate code produces an irregular repeat 35
`and accumulate (IRA) code. An IRA code is a linear code, and
`as such, may be represented as a set of parity checks. The set
`of parity checks may be represented in a bipartite graph,
`called the Tanner graph, of the code. FIG. 3 shows a Tanner
`graph 300 of an IRA code with parameters (f1 , . . . , ~; a),
`where f,~O, ~,f,=1 and "a" is a positive integer. The Tanner
`graph includes two kinds of nodes: variable nodes (open
`circles) and check nodes (filled circles). There are k variable
`nodes 302 on the left, called information nodes. There are r 45
`variable nodes 306 on the right, called parity nodes. There are
`r=(U,if,)/a check nodes 304 connected between the informa(cid:173)
`tion nodes and the parity nodes. Each information node 3 02 is
`connected to a number of check nodes 304. The fraction of
`information nodes connected to exactly i check nodes is f,.
`For example, in the Tanner graph 300, each of the f2 informa(cid:173)
`tion nodes are connected to two check nodes, corresponding
`to a repeat of q=2, and each of the f3 information nodes are
`connected to three check nodes, corresponding to q=3.
`Each check node 304 is connected to exactly "a" informa(cid:173)
`tion nodes 302. In FIG. 3, a=3. These connections can be
`made in many ways, as indicated by the arbitrary permutation
`of the ra edges joining information nodes 302 and check
`nodes 304 in permutation block 310. These connections cor- 60
`respond to the scrambling performed by the interleaver 204.
`In an alternate embodiment, the outer coder 202 may be a
`low-density generator matrix (LDGM) coder that performs
`an irregular repeat of the k bits in the block, as shown in FIG.
`4. As the name implies, an LDGM code has a sparse (low- 65
`density) generator matrix. The IRA code produced by the
`coder 400 is a serial concatenation of the LDGM code and the
`
`50
`
`55
`
`(V1 , . . . , vrJ, then we have the recursive formula for j=
`1, 2, ... , r. This is in effect the encoding algorithm.
`Two types of IRA codes are represented in FIG. 3, a non(cid:173)
`systematic version and a systematic version. The nonsystem(cid:173)
`atic version is an (r,k) code, in which the codeword corre(cid:173)
`sponding to the information bits (uu ... , uk) is (xu ... , xr).
`The systematic version is a (k+r, k) code, in which the code-
`
`The rate of the nonsystematic code is
`
`a
`Rnsys = ~ijj
`
`The rate of the systematic code is
`
`a
`R - - - (cid:173)
`sys-a+Lifi
`;
`
`For example, regular repeat and accumulate (RA) codes
`can be considered nonsystematic IRA codes with a=1 and
`exactly one f, equal to 1, say fq = 1, and the rest zero, in which
`case Rnsys simplifies to R=1/q.
`The IRA code may be represented using an alternate nota(cid:173)
`tion. Let "A, be the fraction of edges between the information
`nodes 302 and the check nodes 304 that are adjacent to an
`information node of degree i, and let p, be the fraction of such
`edges that are adjacent to a check node of degree i+2 (i.e., one
`that is adjacent to i information nodes). These edge fractions
`may be used to represent the IRA code rather than the corre(cid:173)
`sponding node fractions. Define "A(x)=~,"A,x'- 1 and p(x)=
`~,p,x'- 1 to be
`
`lc;/i
`J; = Pi U
`
`the generating functions of these sequences. The pair ("A, p) is
`called a degree distribution. For L(x)=~,f,x,,
`
`Hughes, Exh. 1005, p. 9
`
`

`

`US 7,916,781 B2
`
`5
`The rate of the systematic IRA code given by the
`
`6
`An erasure E output means that the receiver does not know
`how to demodulate the output. Similarly, when 1 is transmit(cid:173)
`ted, the receiver can receive either 1 or E. Thus, for the BEC,
`yE{O, E, 1}, and
`
`1-1
`"'
`LJPi/j
`Rate= 1+ ~AJ/j
`[
`
`m0 (u) =
`
`{
`
`+co if y = 0
`if y = E
`0
`-co if y = 1
`
`10
`
`In the BSC, there are two possible inputs (0,1) and two
`possible outputs (0, 1 ). The BSC is characterized by a set of
`conditional probabilities relating all possible outputs to pos(cid:173)
`sible inputs. Thus, for the BSC yE{O, 1 },
`
`mo(u) =
`
`log--
`
`p l 1- p
`
`1-p
`-log-(cid:173)
`p
`
`if y = 0
`
`if y = 1
`
`25
`
`In theAWGN, the discrete-time input symbols X take their
`values in a finite alphabet while channel output symbols Y can
`take any values along the real line. There is assumed to be no
`distortion or other effects other than the addition of white
`Gaussian noise. In an AWGN with a Binary Phase Shift
`Keying (BPSK) signaling which maps 0 to the symbol with
`30 amplitude v'Es and 1 to the symbol with amplitude -v'Es,
`output yER, then
`
`degree distribution is given by
`"Belief propagation" on the Tanner Graph realization may
`be used to decode IRA codes. Roughly speaking, the belief
`propagation decoding technique allows the messages passed 15
`on an edge to represent posterior densities on the bit associ(cid:173)
`ated with the variable node. A probability density on a bit is a
`pair of non-negative real numbers p(O), p(1) satisfYing p(O)+
`p(1)=1, where p(O) denotes the probability of the bit being 0,
`p(1) the probability of it being 1. Such a pair can be repre- 20
`sented by its log likelihood ratio, m=log(p(O)/p(1 )). The out(cid:173)
`going message from a variable node u to a check node v
`represents information about u, and a message from a check
`node u to a variable node v represents information about u, as
`shown in FIGS. SA and SB, respectively.
`The outgoing message from a node u to a node v depends
`on the incoming messages from all neighbors w of u except v.
`Ifu is a variable message node, this outgoing message is
`
`m(u--+v)= ~m(w--+u)+m0 (u)
`"'*'
`
`where m 0 (u) is the log-likelihood message associated with u. 35
`Ifu is a check node, the corresponding formula is
`
`m(u--+v) n m(w--+u)
`"'*'
`
`tanh---
`2
`
`tanh--- =
`2
`
`40
`
`where N0/2 is the noise power spectral density.
`The selection of a degree profile for use in a particular
`transmission channel is a design parameter, which may be
`affected by various attributes of the channel. The criteria for
`selecting a particular degree profile may include, for example,
`the type of channel and the data rate on the channel. For
`example, Table 1 shows degree profiles that have been found
`to produce good results for an A WGN channel model.
`
`Before decoding, the messages m(w---;.u) and m(u---;.v) are
`initialized to be zero, and m 0 (u) is initialized to be the log(cid:173)
`likelihood ratio based on the channel received information. If 45
`the channel is memoryless, i.e., each channel output only
`relies on its input, andy is the output of the channel code bit
`u, then m 0 (u)=log(p(u=Oiy)/p(u=11y)). After this initializa(cid:173)
`tion, the decoding process may run in a fully parallel and local
`manner. In each iteration, every variable/check node receives so
`messages from its neighbors, and sends back updated mes(cid:173)
`sages. Decoding is terminated after a fixed number of itera(cid:173)
`tions or detecting that all the constraints are satisfied. Upon
`termination, the decoder outputs a decoded sequence based
`on the messages
`
`55
`
`m(u) = ~ Wm(w--+ u).
`
`60
`
`TABLE 1
`
`a
`
`2
`
`"A2
`"A3
`"AS
`M
`"AlO
`"All
`"Al2
`"Al3
`"Al4
`"Al6
`"A27
`"A28
`Rate
`aGA
`a*
`(Eb/NO) *(dB)
`S.L. (dB)
`
`0.139025
`0.2221555
`
`0.638820
`
`0.078194
`0.128085
`0.160813
`0.036178
`
`0.108828
`0.487902
`
`0.333364
`1.1840
`1.1981
`0.190
`-0.4953
`
`0.333223
`1.2415
`1.2607
`-0.250
`-0.4958
`
`4
`
`0.054485
`0.104315
`
`0.126755
`0.229816
`0.016484
`
`0.450302
`0.017842
`0.333218
`1.2615
`1.2780
`-0.371
`-0.4958
`
`Thus, on various channels, iterative decoding only differs
`in the initial messages m 0 (u). For example, consider three
`memoryless channel models: a binary erasure channel
`(BEC); a binary symmetric channel (BSC); and an additive
`white Gaussian noise (AGWN) channel.
`In the BEC, there are two inputs and three outputs. When 0
`is transmitted, the receiver can receive either 0 or an erasure E.
`
`Table 1 shows degree profiles yielding codes of rate
`approximately 1/3 fortheAWGN channel and witha=2, 3, 4.
`For each sequence, the Gaussian approximation noise thresh-
`65 old, the actual sum-product decoding threshold and the cor(cid:173)
`responding energy per bit (E6)-noise power (N0 ) ratio in dB
`are given. Also listed is the Shannon limit (S.L.).
`
`Hughes, Exh. 1005, p. 10
`
`

`

`US 7,916,781 B2
`
`7
`As the parameter "a" is increased, the performance
`improves. For example, for a=4, the best code found has an
`iterative decoding threshold of E6/N0=-0.371 dB, which is
`only 0.12 dB above the Shannon limit.
`The accumulator component of the coder may be replaced
`by a "double accumulator" 600 as shown in FIG. 6. The
`double accumulator can be viewed as a truncated rate 1 con(cid:173)
`volutional coder with transfer function 1/(1 +D+D2
`).
`Alternatively, a pair of accumulators may be the added, as
`shown in FIG. 7. There are three component codes: the 10
`"outer" code 700, the "middle" code 702, and the "inner"
`code 704. The outer code is an irregular repetition code, and
`the middle and inner codes are both accumulators.
`IRA codes may be implemented in a variety of channels,
`including memoryless channels, such as the BEC, BSC, and 15
`AWGN, as well as channels having non-binary input, non(cid:173)
`symmetric and fading channels, and/or channels with
`memory.
`A number of embodiments have been described. Neverthe(cid:173)
`less, it will be understood that various modifications may be 20
`made without departing from the spirit and scope of the
`invention. Accordingly, other embodiments are within the
`scope of the following claims.
`What is claimed is:
`1. A method of encoding a signal, comprising:
`receiving a block of data in the signal to be encoded, the
`block of data including information bits;
`performing a first encoding operation on at least some of
`the information bits, the first encoding operation being a
`linear transform operation that generates L transformed 30
`bits; and
`performing a second encoding operation using the L trans(cid:173)
`formed bits as an input, the second encoding operation
`including an accumulation operation in which the L
`transformed bits generated by the first encoding opera- 35
`tion are accumulated, said second encoding operation
`producing at least a portion of a codeword, wherein Lis
`two or more.
`2. The method of claim 1, further comprising:
`outputting the codeword, wherein the codeword comprises 40
`parity bits.
`3. The method of claim 2, wherein outputting the codeword
`comprises:
`outputting the parity bits; and
`outputting at least some of the information bits.
`4. The method of claim 3, wherein outputting the codeword
`comprises:
`outputting the parity bits following the information bits.
`5. The method of claim 2, wherein performing the first
`encoding operation comprises transforming the at least some 50
`of the information bits via a low density generator matrix
`transformation.
`6. The method of claim 5, wherein generating each of the L
`transformed bits comprises mod-2 or exclusive-OR snnnning
`of bits in a subset of the information bits.
`7. The method of claim 6, wherein eachofthe subsets of the
`information bits includes a same number of the information
`bits.
`8. The method of claim 6, wherein at least two of the
`information bits appear in three subsets of the information 60
`bits.
`9. The method of claim 6, wherein the information bits
`appear in a variable number of subsets.
`10. The method of claim 2, wherein performing the second
`encoding operation comprises using a first of the parity bits in 65
`the accumulation operation to produce a second of the parity
`bits.
`
`45
`
`25
`
`55
`
`8
`11. The method of claim 10, wherein outputting the code(cid:173)
`word comprises outputting the second of the parity bits imme(cid:173)
`diately following the first of the parity bits.
`12. The method of claim 2, wherein performing the second
`encoding operation comprises performing one of a mod-2
`addition and an exclusive-OR operation.
`13. A method of encoding a signal, comprising:
`receiving a block of data in the signal to be encoded, the
`block of data including information bits; and
`performing an encoding operation using the information
`bits as an input, the encoding operation including an
`accumulation ofmod-2 or exclusive-OR sums of bits in
`subsets of the information bits, the encoding operation
`generating at least a portion of a codeword,
`wherein the information bits appear in a variable number of
`subsets.
`14. The method of claim 13, further comprising:
`outputting the codeword, wherein the codeword comprises
`parity bits.
`15. The method of claim 14, wherein outputting the code-
`word comprises:
`outputting the parity bits; and
`outputting at least some of the information bits.
`16. The method of claim 15, wherein the parity bits follow
`the information bits in the codeword.
`17. The method of claim 13, wherein each of the subsets of
`the information bits includes a constant number of the infor(cid:173)
`mation bits.
`18. The method of claim 13, wherein performing the
`encoding operation further comprises:
`performing one of the mod-2 addition and the exclusive(cid:173)
`OR snnnning of the bits in the subsets.
`19. A method of encoding a signal, comprising:
`receiving a block of data in the signal to be encoded, the
`block of data including information bits; and
`performing an encoding operation using the information
`bits as an input, the encoding operation including an
`accumulation ofmod-2 or exclusive-OR sums of bits in
`subsets of the information bits, the encoding operation
`generating at least a portion of a codeword, wherein at
`least two of the information bits appear in three subsets
`of the information bits.
`20. A method of encoding a signal, comprising:
`receiving a block of data in the signal to be encoded, the
`block of data including information bits; and
`performing an encoding operation using the information
`bits as an input, the encoding operation including an
`accumulation ofmod-2 or exclusive-OR sums of bits in
`subsets of the information bits, the encoding operation
`generating at least a portion of a codeword, wherein
`performing the encoding operation comprises:
`mod-2 or exclusive-OR adding a first subset of information
`bits in the collection to yield a first sum;
`mod-2 or exclusive-OR adding a second subset of infor(cid:173)
`mation bits in the collection and the first sum to yield a
`second sum.
`21. A method comprising:
`receiving a collection of information bits;
`mod-2 or exclusive-OR adding a first subset of information
`bits in the collection to yield a first parity bit;
`mod-2 or exclusive-OR adding a second subset of infor(cid:173)
`mation bits in the collection and the first parity bit to
`yield a second parity bit; and
`outputting a codeword that includes the first parity bit and
`the second parity bit.
`
`Hughes, Exh. 1005, p. 11
`
`

`