The present invention relates to communication systems, and more particularly to coded systems.
Communication systems employ coding to ensure reliable communication across noisy communication channels. These communication channels exhibit a fixed capacity that can be expressed in terms of bits per symbol at certain signal to noise ratio (SNR), defining a theoretical upper limit (known as the Shannon limit). As a result, coding design has aimed to achieve rates approaching this Shannon limit. Conventional coded communication systems have separately treated the processes of coding and modulation. Moreover, little attention has been paid to labeling of signal constellations.
A signal constellation provides a set of possible symbols that are to be transmitted, whereby the symbols correspond to codewords output from an encoder. One choice of constellation labeling involves Gray-code labeling. With Gray-code labeling, neighboring signal points differ in exactly one bit position. The prevailing conventional view of modulation dictates that any reasonable labeling scheme can be utilized, which in part is responsible for the paucity of research in this area.
With respect to coding, one class of codes that approach the Shannon limit is Low Density Parity Check (LDPC) codes. Traditionally, LDPC codes have not been widely deployed because of a number of drawbacks. One drawback is that the LDPC encoding technique is highly complex. Encoding an LDPC code using its generator matrix would require storing a very large, non-sparse matrix. Additionally, LDPC codes require large blocks to be effective; consequently, even though parity check matrices of LDPC codes are sparse, storing these matrices is problematic.
From an implementation perspective, a number of challenges are confronted. For example, storage is an important reason why LDPC codes have not become widespread in practice. Also, a key challenge in LDPC code implementation has been how to achieve the connection network between several processing engines (nodes) in the decoder. Further, the computational load in the decoding process, specifically the check node operations, poses a problem.
Therefore, there is a need for a bit labeling approach that supplements code performance of coded systems in general. There is also a need for using LDPC codes efficiently to support high data rates, without introducing greater complexity. There is also a need to improve performance of LDPC encoders and decoders.
These and other needs are addressed by the present invention, wherein an approach is provided for bit labeling of a signal constellation. An encoder, such as a Low Density Parity Check (LDPC) encoder, generates encoded signals by transforming an input message into a codeword represented by a plurality of set of bits. These bits are mapped non-sequentially (e.g., interleaving) a higher order constellation (Quadrature Phase Shift Keying (QPSK), 8-PSK, 16-APSK (Amplitude Phase Shift Keying), 32-APSK, etc. The above arrangement advantageously provides enhanced performance of the codes.
According to one aspect of an embodiment of the present invention, a method for transmitting encoded signals is disclosed. The method includes receiving one of a plurality of set of bits of a codeword from an encoder for transforming an input message into the codeword. The method also includes non-sequentially mapping the one set of bits into a higher order constellation. Further, the method includes outputting a symbol of the higher order constellation corresponding to the one set of bits based on the mapping.
According to another aspect of an embodiment of the present invention, a transmitter for generating encoded signals is disclosed. The transmitter includes an encoder configured to transform an input message into a codeword represented by a plurality of set of bits. Additionally, the transmitter includes logic configured to map non-sequentially one set of bits into a higher order constellation, wherein a symbol of the higher order constellation corresponding to the one set of bits is output based on the mapping.
According to another aspect of an embodiment of the present invention, a method for processing encoded signals is disclosed. The method includes demodulating a received encoded signal representing a codeword, wherein the encoded signal being modulated according to a non-sequential mapping of a plurality of bits corresponding to the codeword. The method also includes decoding the codeword associated with the encoded signal.
Still other aspects, features, and advantages of the present invention are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the present invention. The present invention is also capable of other and different embodiments, and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the present invention. Accordingly, the drawing and description are to be regarded as illustrative in nature, and not as restrictive.
The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:
A system, method, and software for bit labeling for signal constellations are described. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It is apparent, however, to one skilled in the art that the present invention may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the present invention.
Although the present invention is described with respect to LDPC codes, it is recognized that the bit labeling approach can be utilized with other codes. Further, this approach can be implemented with uncoded systems.
The LDPC codes that are generated by the transmitter 101 enables high speed implementation without incurring any performance loss. These structured LDPC codes output from the transmitter 101 avoid assignment of a small number of check nodes to the bit nodes already vulnerable to channel errors by virtue of the modulation scheme (e.g., 8-PSK).
Such LDPC codes have a parallelizable decoding algorithm (unlike turbo codes), which advantageously involves simple operations such as addition, comparison and table look-up. Moreover, carefully designed LDPC codes do not exhibit any sign of error floor.
According to one embodiment of the present invention, the transmitter 101 generates, using a relatively simple encoding technique, LDPC codes based on parity check matrices (which facilitate efficient memory access during decoding) to communicate with the receiver 105. The transmitter 101 employs LDPC codes that can outperform concatenated turbo+RS (Reed-Solomon) codes, provided the block length is sufficiently large.
Encoder 203 generates signals from alphabet Y to a signal mapper 206, which provides a mapping of the alphabet Y to the symbols of the signal constellation corresponding to the modulation scheme employed by a modulator 205. This mapping, according to one embodiment of the present invention, follows a non-sequential scheme, such as interleaving. Exemplary mappings are more fully described below with respect to
The modulator 205 modulates the symbols of the signal constellation from the mapper 206 to signal waveforms that are transmitted to a transmit antenna 207, which emits these waveforms over the communication channel 103. The transmissions from the transmit antenna 207 propagate to a receiver, as discussed below.
The LDPC encoder 203 systematically encodes an information block of size kldpc, i=(i0, i1, . . . , ik
The task of the LDPC encoder 203 is to determine nldpc−kldpc parity bits (p0, p1, . . . pn
p0=p1=p2= . . . =pn
p0=p0⊕i0
p10491=p10491⊕i0
p16043=p16043⊕i0
p506=p506⊕i0
p12826=p12826⊕i0
p8065=p8065⊕i0
p8226=p8226⊕i0
p2767=p2767⊕i0
p240=p240⊕i0
p18673=p18673⊕i0
p9279=p9279⊕i0
p10579=p10579⊕i0
p20928=p20928⊕i0
(All additions are in GF(2)).
Then, for the next 359 information bits, im, m=1, 2, . . . , 359, these bits are accumulated at parity bit addresses {x+m mod 360×q} mod(nldpc−kldpc), where x denotes the address of the parity bit accumulator corresponding to the first bit i0, and q is a code rate dependent constant specified in Table 2. Continuing with the example, q=60 for rate 2/3. By way of example, for information bit i1, the following operations are performed:
p60=p60⊕i1
p10551=p10551⊕i1
p16103=p16103⊕i1
p566=p566⊕i1
p12886=p12886⊕i1
p8125=p8125⊕i1
p8286=p8286⊕i1
p2827=p2827⊕i1
p300=p300⊕i1
p18733=p18733⊕i1
p9339=p9339⊕i1
p10639=p10639⊕i1
p20988=p20988⊕i1
For the 361st information bit i360, the addresses of the parity bit accumulators are given in the second row of the Tables 3 through 10. In a similar manner the addresses of the parity bit accumulators for the following 359 information bits im, m=361, 362, . . . , 719 are obtained using the formula {x+m mod 360×q} mod(nldpc−kldpc), where x denotes the address of the parity bit accumulator corresponding to the information bit i360, i.e., the entries in the second row of the Tables 3-10. In a similar manner, for every group of 360 new information bits, a new row from Tables 3 through 10 are used to find the addresses of the parity bit accumulators.
After all of the information bits are exhausted, the final parity bits are obtained as follows. First, the following operations are performed, starting with i=1
pi=pi⊕pi−1,i=1,2, . . . ,nldpc−kldpc−1.
Final content of pi, i=0, 1, . . . , nldpc−kldpc−1 is equal to the parity bit pi.
As regards the BCH encoder 211, the BCH code parameters are enumerated in Table 11.
It is noted that in the above table, nbch=kldpc.
The generator polynomial of the t error correcting BCH encoder 211 is obtained by multiplying the first t polynomials in the following list of Table 12:
BCH encoding of information bits m=(mk
The above LDPC codes, in an exemplary embodiment, can be used to variety of digital video applications, such as MPEG (Motion Pictures Expert Group) packet transmission.
Returning the receiver 303, the LDPC decoder 305 is considered a message passing decoder, whereby the decoder 305 aims to find the values of bit nodes. To accomplish this task, bit nodes and check nodes iteratively communicate with each other. The nature of this communication is described below.
From check nodes to bit nodes, each check node provides to an adjacent bit node an estimate (“opinion”) regarding the value of that bit node based on the information coming from other adjacent bit nodes. For instance, in the above example if the sum of n4, n5 and n8 “looks like” 0 to m1, then m1 would indicate to n1 that the value of n1 is believed to be 0 (since n1+n4+n5+n8=0); otherwise m1 indicate to n1 that the value of n1 is believed to be 1. Additionally, for soft decision decoding, a reliability measure is added.
From bit nodes to check nodes, each bit node relays to an adjacent check node an estimate about its own value based on the feedback coming from its other adjacent check nodes. In the above example n1 has only two adjacent check nodes m1 and m3. If the feedback coming from m3 to n1 indicates that the value of n1 is probably 0, then n1 would notify m1 that an estimate of n1's own value is 0. For the case in which the bit node has more than two adjacent check nodes, the bit node performs a majority vote (soft decision) on the feedback coming from its other adjacent check nodes before reporting that decision to the check node it communicates. The above process is repeated until all bit nodes are considered to be correct (i.e., all parity check equations are satisfied) or until a predetermined maximum number of iterations is reached, whereby a decoding failure is declared.
H(n−k)xn=[A(n−k)xkB(n−k)x(n−k)],
where B is lower triangular.
Any information block i=(i0, i1, . . . , ik−1) is encoded to a codeword c=(i0, i1, . . . , ik−1, p0, p1, . . . pn−k−1) using HcT=0, and recursively solving for parity bits; for example,
a00i0+a01i1+ . . . +a0,k−1ik−1+p0=0Solve p0,
a10i0+a11i1+ . . . +a1,k−1ik−1+b10p0+p1=0Solve p1
Under this scheme, there is no need to iterate between the LDPC decoder 305 (
Alternatively, 8-PSK, 16-APSK and 32-APSK constellation labeling can be chosen as shown in
On the other hand, for systems that do not require very low FER, Gray labeling without any iteration between LDPC decoder 305 and 8-PSK bit metric generator 307 may be more suitable because re-generating 8-PSK bit metrics before every LDPC decoder iteration causes additional complexity. Moreover, when Gray labeling is used, re-generating 8-PSK bit metrics before every LDPC decoder iteration yields only very slight performance improvement. As mentioned previously, Gray labeling without iteration may be used for systems that require very low FER, provided an outer code is implemented.
The choice between Gray labeling and non-Gray labeling depends also on the characteristics of the LDPC code. Typically, the higher bit or check node degrees, the better it is for Gray labeling, because for higher node degrees, the initial feedback from LDPC decoder 305 to 8-PSK (or similar higher order modulation) bit metric generator 307 deteriorates more with non-Gray labeling.
When 8-PSK (or similar higher order) modulation is utilized with a binary decoder, it is recognized that the three (or more) bits of a symbol are not received “equally noisy”. For example with Gray 8-PSK labeling, the third bit of a symbol is considered more noisy to the decoder than the other two bits. Therefore, the LDPC code design does not assign a small number of edges to those bit nodes represented by “more noisy” third bits of 8-PSK symbol so that those bits are not penalized twice.
The 8-PSK bit metric generator 307 communicates with the LDPC decoder 305 to exchange a priori probability information and a posteriori probability information, which respectively are represented as u, and a. That is, the vectors u and a respectively represent a priori and a posteriori probabilities of log likelihood ratios of coded bits.
The 8-PSK bit metric generator 307 generates the a priori likelihood ratios for each group of three bits as follows. First, extrinsic information on coded bits is obtained:
ej=aj−ujj=0,1,2.
Next, 8-PSK symbol probabilities, pi i=0, 1, . . . , 7, are determined.
*yj=−f(0,ej)j=0, 1, 2 where f(a,b)=max(a,b)+LUTf(a,b) with LUTf(a,b)=ln(1+e−|a-b|)
Next, the bit metric generator 307 determines a priori log likelihood ratios of the coded bits as input to LDPC decoder 305, as follows:
u0=f(d0+p0,d1+p1,d2+p2,d3+p3)−f(d4+p4,d5+p5,d6+p6,d7+p7)−e0
u1=f(d0+p0,d1+p1,d4+p4,d5+p5)−f(d2+p2,d3+p3,d6+p6,d7+p7)−e1
u2=f(d0+p0,d2+p2,d4+p4,d6+p6)−f(d1+p1,d3+p3,d5+p5,d7+p7)−e2
It is noted that the function ƒ(.) with more than two variables can be evaluated recursively; e.g. ƒ(a,b,c)=ƒ(ƒ(a,b),c).
The operation of the LDPC decoder 305 utilizing non-Gray mapping is now described. In step 1001, the LDPC decoder 305 initializes log likelihood ratios of coded bits, v, before the first iteration according to the following (and as shown in
vn→k
Here, vn→k
In step 1003, a check node, k, is updated, whereby the input v yields the output w. As seen in
wk→n1,wk→n
wk→n
The function g( ) is defined as follows:
g(a,b)=sign(a)×sign(b)×{min(|a|,|b|)}+LUTg(a,b),
where LUTg(a,b)=ln(1+e−|a+b|)−ln(1+e−|a−b|). Similar to function ƒ, function g with more than two variables can be evaluated recursively.
Next, the decoder 305, per step 1205, outputs a posteriori probability information (
Per step 1007; it is determined whether all the parity check equations are satisfied. If these parity check equations are not satisfied, then the decoder 305, as in step 1009, re-derives 8-PSK bit metrics and channel input un. Next, the bit node is updated, as in step 1011. As shown in
In step 1013, the decoder 305 outputs the hard decision (in the case that all parity check equations are satisfied):
The above approach is appropriate when non-Gray labeling is utilized. However, when Gray labeling is implemented, the process of
Referring to
Under the forward-backward approach to computing these outgoing messages, forward variables, ƒ1, ƒ2, . . . , ƒdc, are defined as follows:
In step 1301, these forward variables are computed, and stored, per step 1303.
Similarly, backward variables, b1, b2, . . . , bdc, are defined by the following:
In step 1305, these backward variables are then computed. Thereafter, the outgoing messages are computed, as in step 1307, based on the stored forward variables and the computed backward variables. The outgoing messages are computed as follows:
wk→1=b2
wk→i=g(ƒi−1,bi+1)i=2,3, . . . ,dc−1
wk→dc=ƒdc−1
Under this approach, only the forward variables, ƒ2, ƒ3, . . . , ƒdc, are required to be stored. As the backward variables bi are computed, the outgoing messages, wk→i, are simultaneously computed, thereby negating the need for storage of the backward variables.
The computation load can be further enhance by a parallel approach, as next discussed.
γk=g(vn
It is noted that the g( . . . ) function can also be expressed as follows:
Exploiting the recursive nature of the g( . . . ) function, the following expression results:
Accordingly, wk→n
The ln(.) term of the above equation can be obtained using a look-up table LUTx that represents the function ln|ex−1| (step 1313). Unlike the other look-up tables LUTf or LUTg, the table LUTx would likely requires as many entries as the number of quantization levels. Once γk is obtained, the calculation of wk→n
The computational latency of γk is advantageously log2(dc).
Two general approaches exist to realize the interconnections between check nodes and bit nodes: (1) a fully parallel approach, and (2) a partially parallel approach. In fully parallel architecture, all of the nodes and their interconnections are physically implemented. The advantage of this architecture is speed.
The fully parallel architecture, however, may involve greater complexity in realizing all of the nodes and their connections. Therefore with fully parallel architecture, a smaller block size may be required to reduce the complexity. In that case, for the same clock frequency, a proportional reduction in throughput and some degradation in FER versus Es/No performance may result.
The second approach to implementing LDPC codes is to physically realize only a subset of the total number of the nodes and use only these limited number of “physical” nodes to process all of the “functional” nodes of the code. Even though the LDPC decoder operations can be made extremely simple and can be performed in parallel, the further challenge in the design is how the communication is established between “randomly” distributed bit nodes and check nodes. The decoder 305 (of
In other words, the approach of the present invention facilitates memory access during check node and bit node processing. The values of the edges in the bipartite graph can be stored in a storage medium, such as random access memory (RAM). It is noted that for a truly random LDPC code during check node and bit node processing, the values of the edges would need to be accessed one by one in a random fashion. However, such a conventional access scheme would be too slow for a high data rate application. The RAM of
As seen in
Based on Table 14, an edge RAM of size 576×392 is sufficient to store the edge metrics for all the code rates of 1/2, 2/3, 3/4, and 5/6.
As noted, under this exemplary scenario, a group of 392 bit nodes and 392 check nodes are selected for processing at a time. For 392 check node processing, q=dc−2 consecutive rows are accessed from the top edge RAM 1501, and 2 consecutive rows from the bottom edge RAM 1503. The value of dc depends on the specific code, for example dc=7 for rate 1/2, dc=10 for rate 2/3, dc=16 for rate 3/4 and dc=22 for rate 5/6 for the above codes. Of course other values of for other codes are possible. In this instance, q+2 is the degree of each check node.
For bit node processing, if the group of 392 bit nodes has degree 2, their edges are located in 2 consecutive rows of the bottom edge RAM 1503. If the bit nodes have degree d>2, their edges are located in some d rows of the top edge RAM 1501. The address of these d rows can be stored in non-volatile memory, such as Read-Only Memory (ROM). The edges in one of the rows correspond to the first edges of 392 bit nodes, the edges in another row correspond to the second edges of 392 bit nodes, etc. Moreover for each row, the column index of the edge that belongs to the first bit node in the group of 392 can also be stored in ROM. The edges that correspond to the second, third, etc. bit nodes follow the starting column index in a “wrapped around” fashion. For example, if the jth edge in the row belongs to the first bit node, then the (j+1)st edge belongs to the second bit node, (j+2)nd edge belongs to the third bit node, . . . , and (j−1)st edge belongs to the 392th bit node.
With the organization shown in
The computer system 1600 may be coupled via the bus 1601 to a display 1611, such as a cathode ray tube (CRT), liquid crystal display, active matrix display, or plasma display, for displaying information to a computer user. An input device 1613, such as a keyboard including alphanumeric and other keys, is coupled to the bus 1601 for communicating information and command selections to the processor 1603. Another type of user input device is cursor control 1615, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to the processor 1603 and for controlling cursor movement on the display 1611.
According to one embodiment of the invention, generation of LDPC codes is provided by the computer system 1600 in response to the processor 1603 executing an arrangement of instructions contained in main memory 1605. Such instructions can be read into main memory 1605 from another computer-readable medium, such as the storage device 1609. Execution of the arrangement of instructions contained in main memory 1605 causes the processor 1603 to perform the process steps described herein. One or more processors in a multi-processing arrangement may also be employed to execute the instructions contained in main memory 1605. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement the embodiment of the present invention. Thus, embodiments of the present invention are not limited to any specific combination of hardware circuitry and software.
The computer system 1600 also includes a communication interface 1617 coupled to bus 1601. The communication interface 1617 provides a two-way data communication coupling to a network link 1619 connected to a local network 1621. For example, the communication interface 1617 may be a digital subscriber line (DSL) card or modem, an integrated services digital network (ISDN) card, a cable modem, or a telephone modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface 1617 may be a local area network (LAN) card (e.g. for Ethernet™ or an Asynchronous Transfer Model (ATM) network) to provide a data communication connection to a compatible LAN. Wireless links can also be implemented. In any such implementation, communication interface 1617 sends and receives electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information. Further, the communication interface 1617 can include peripheral interface devices, such as a Universal Serial Bus (USB) interface, a PCMCIA (Personal Computer Memory Card International Association) interface, etc.
The network link 1619 typically provides data communication through one or more networks to other data devices. For example, the network link 1619 may provide a connection through local network 1621 to a host computer 1623, which has connectivity to a network 1625 (e.g. a wide area network (WAN) or the global packet data communication network now commonly referred to as the “Internet”) or to data equipment operated by service provider. The local network 1621 and network 1625 both use electrical, electromagnetic, or optical signals to convey information and instructions. The signals through the various networks and the signals on network link 1619 and through communication interface 1617, which communicate digital data with computer system 1600, are exemplary forms of carrier waves bearing the information and instructions.
The computer system 1600 can send messages and receive data, including program code, through the network(s), network link 1619, and communication interface 1617. In the Internet example, a server (not shown) might transmit requested code belonging to an application program for implementing an embodiment of the present invention through the network 1625, local network 1621 and communication interface 1617. The processor 1603 may execute the transmitted code while being received and/or store the code in storage device 169, or other non-volatile storage for later execution. In this manner, computer system 1600 may obtain application code in the form of a carrier wave.
The term “computer-readable medium” as used herein refers to any medium that participates in providing instructions to the processor 1603 for execution. Such a medium may take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical or magnetic disks, such as storage device 1609. Volatile media include dynamic memory, such as main memory 1605. Transmission media include coaxial cables, copper wire and fiber optics, including the wires that comprise bus 1601. Transmission media can also take the form of acoustic, optical, or electromagnetic waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, CDRW, DVD, any other optical medium, punch cards, paper tape, optical mark sheets, any other physical medium with patterns of holes or other optically recognizable indicia, a RAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read.
Various forms of computer-readable media may be involved in providing instructions to a processor for execution. For example, the instructions for carrying out at least part of the present invention may initially be borne on a magnetic disk of a remote computer. In such a scenario, the remote computer loads the instructions into main memory and sends the instructions over a telephone line using a modem. A modem of a local computer system receives the data on the telephone line and uses an infrared transmitter to convert the data to an infrared signal and transmit the infrared signal to a portable computing device, such as a personal digital assistance (PDA) and a laptop. An infrared detector on the portable computing device receives the information and instructions borne by the infrared signal and places the data on a bus. The bus conveys the data to main memory, from which a processor retrieves and executes the instructions. The instructions received by main memory may optionally be stored on storage device either before or after execution by processor.
Accordingly, the various embodiments of the present invention provide an approach is provided for bit labeling of a signal constellation. An encoder, such as a Low Density Parity Check (LDPC) encoder, generates encoded signals by transforming an input message into a codeword represented by a plurality of set of bits. These bits are mapped non-sequentially (e.g., interleaving) a higher order constellation (Quadrature Phase Shift Keying (QPSK), 8-PSK, 16-APSK (Amplitude Phase Shift Keying), 32-APSK, etc. The above arrangement advantageously provides enhanced performance of the codes.
While the present invention has been described in connection with a number of embodiments and implementations, the present invention is not so limited but covers various obvious modifications and equivalent arrangements, which fall within the purview of the appended claims.
This application is a continuation of U.S. patent application (Ser. No. 11/186,265) filed Jul. 21, 2005, now U.S. Pat. No. 7,577,207, issued Aug. 18, 2009 and entitled “Bit Labeling for Amplitude Phase Shift Constellation Used With Low Density Parity Check (LDPC) Codes,” which itself is a continuation of U.S. patent application (Ser. No. 10/613,877) filed Jul. 3, 2003, now U.S. Pat. No. 6,963,622, issued Jul. 3, 2003 and entitled “Bit Labeling for Amplitude Phase Shift Constellation Used With Low Density Parity Check (LDPC) Codes,” which itself claims the benefit of the earlier filing date under 35 U.S.C. §119(e) of, U.S. Provisional Patent Application (Ser. No. 60/456,220) filed Mar. 20, 2003, entitled “Description LDPC and BCH Encoders,” U.S. Provisional Patent Application (Ser. No. 60/393,457) filed Jul. 3, 2002, entitled “Code Design and Implementation Improvements for Low Density Parity Check Codes,” U.S. Provisional Patent Application (Ser. No. 60/398,760) filed Jul. 26, 2002, entitled “Code Design and Implementation Improvements for Low Density Parity Check Codes,” U.S. Provisional Patent Application (Ser. No. 60/403,812) filed Aug. 15, 2002, entitled “Power and Bandwidth Efficient Modulation and Coding Scheme for Direct Broadcast Satellite and Broadcast Satellite Communications,” U.S. Provisional Patent Application (Ser. No. 60/421,505), filed Oct. 25, 2002, entitled “Method and System for Generating Low Density Parity Check Codes,” U.S. Provisional Patent Application (Ser. No. 60/421,999), filed Oct. 29, 2002, entitled “Satellite Communication System Utilizing Low Density Parity Check Codes,” U.S. Provisional Patent Application (Ser. No. 60/423,710), filed Nov. 4, 2002, entitled “Code Design and Implementation Improvements for Low Density Parity Check Codes,” U.S. Provisional Patent Application (Ser. No. 60/440,199) filed Jan. 15, 2003, entitled “A Novel Solution to Routing Problem in Low Density Parity Check Decoders,” U.S. Provisional Patent Application (Ser. No. 60/447,641) filed Feb. 14, 2003, entitled “Low Density Parity Check Code Encoder Design,” U.S. Provisional Patent Application (Ser. No. 60/456,220) filed Mar. 20, 2003, entitled “Description LDPC and BCH Encoders,” U.S. Provisional Patent Application (Ser. No. 60/469,356) filed May 9, 2003, entitled “Description LDPC and BCH Encoders,” U.S. Provisional Patent Application (Ser. No. 60/482,112) filed Jun. 24, 2003, entitled “Description LDPC and BCH Encoders,” and U.S. Provisional Patent Application (Ser. No. 60/482,107) filed Jun. 24, 2003, entitled “Description LDPC and BCH Encoders”; the entireties of which are incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
4709377 | Martinez et al. | Nov 1987 | A |
5099484 | Smelser | Mar 1992 | A |
5371471 | Chennakeshu et al. | Dec 1994 | A |
5467132 | Fazel et al. | Nov 1995 | A |
5559990 | Cheng et al. | Sep 1996 | A |
5949796 | Kumar | Sep 1999 | A |
6031874 | Chennakeshu et al. | Feb 2000 | A |
6075408 | Kullstam et al. | Jun 2000 | A |
6097703 | Larsen et al. | Aug 2000 | A |
6115427 | Calderbank et al. | Sep 2000 | A |
6216200 | Yeager | Apr 2001 | B1 |
6292917 | Sinha et al. | Sep 2001 | B1 |
6347124 | Antia et al. | Feb 2002 | B1 |
6405338 | Sinha et al. | Jun 2002 | B1 |
6438180 | Kavcic et al. | Aug 2002 | B1 |
6510536 | Crozier et al. | Jan 2003 | B1 |
6518892 | Shen et al. | Feb 2003 | B2 |
6539367 | Blanksby et al. | Mar 2003 | B1 |
6553535 | Asada et al. | Apr 2003 | B1 |
6567465 | Goldstein et al. | May 2003 | B2 |
6633856 | Richardson et al. | Oct 2003 | B2 |
6662290 | Choi | Dec 2003 | B2 |
6665361 | Christodoulides et al. | Dec 2003 | B1 |
6715121 | Laurent | Mar 2004 | B1 |
6718508 | Lodge et al. | Apr 2004 | B2 |
6751770 | Morelos-Zaragoza | Jun 2004 | B2 |
6769091 | Classon et al. | Jul 2004 | B2 |
6785863 | Blankenship et al. | Aug 2004 | B2 |
6829308 | Eroz et al. | Dec 2004 | B2 |
6857097 | Yedidia et al. | Feb 2005 | B2 |
6895547 | Eleftheriou et al. | May 2005 | B2 |
6901119 | Cideciyan et al. | May 2005 | B2 |
6938196 | Richardson et al. | Aug 2005 | B2 |
6950461 | Goldstein et al. | Sep 2005 | B2 |
6963622 | Eroz et al. | Nov 2005 | B2 |
6985536 | Oelcer et al. | Jan 2006 | B2 |
7000177 | Wu et al. | Feb 2006 | B1 |
7017106 | Shen et al. | Mar 2006 | B2 |
7116710 | Jin et al. | Oct 2006 | B1 |
7184486 | Wu et al. | Feb 2007 | B1 |
7191378 | Eroz et al. | Mar 2007 | B2 |
7421644 | Mantha et al. | Sep 2008 | B2 |
7620880 | Niu et al. | Nov 2009 | B2 |
20020002695 | Kschischang et al. | Jan 2002 | A1 |
20020021770 | Beerel et al. | Feb 2002 | A1 |
20020042899 | Tzannes et al. | Apr 2002 | A1 |
20020048329 | Tran et al. | Apr 2002 | A1 |
20020051499 | Cameron et al. | May 2002 | A1 |
20020051501 | Demjanenko et al. | May 2002 | A1 |
20020071504 | Chen et al. | Jun 2002 | A1 |
20020101915 | Zhang et al. | Aug 2002 | A1 |
20020136317 | Oelcer et al. | Sep 2002 | A1 |
20020136318 | Gorokhov et al. | Sep 2002 | A1 |
20020141507 | Morgan et al. | Oct 2002 | A1 |
20020150167 | Demjanenko et al. | Oct 2002 | A1 |
20020153938 | Baudelot et al. | Oct 2002 | A1 |
20020188906 | Kurtas et al. | Dec 2002 | A1 |
20030014718 | De Souza et al. | Jan 2003 | A1 |
20030023917 | Richardson et al. | Jan 2003 | A1 |
20030033570 | Khannanov et al. | Feb 2003 | A1 |
20030033575 | Richardson et al. | Feb 2003 | A1 |
20030037298 | Eleftheriou et al. | Feb 2003 | A1 |
20030058958 | Shokrollahi et al. | Mar 2003 | A1 |
20030065989 | Yedida et al. | Apr 2003 | A1 |
20030074626 | Coker et al. | Apr 2003 | A1 |
20030079171 | Coe | Apr 2003 | A1 |
20030079172 | Yamagishi et al. | Apr 2003 | A1 |
20030081691 | Sutskover et al. | May 2003 | A1 |
20030091098 | Manninen et al. | May 2003 | A1 |
20030104788 | Kim | Jun 2003 | A1 |
20030126551 | Mantha et al. | Jul 2003 | A1 |
20030152158 | Torres et al. | Aug 2003 | A1 |
20030179768 | Lusky et al. | Sep 2003 | A1 |
20030187899 | Ohta | Oct 2003 | A1 |
20030203721 | Berezdivin et al. | Oct 2003 | A1 |
20030207696 | Willenegger et al. | Nov 2003 | A1 |
20030223507 | De Gaudenzi et al. | Dec 2003 | A1 |
20040034827 | Shen et al. | Feb 2004 | A1 |
20040034828 | Hocevar | Feb 2004 | A1 |
20040039983 | Brossier et al. | Feb 2004 | A1 |
20040047433 | Mogre et al. | Mar 2004 | A1 |
20040064779 | Vasic et al. | Apr 2004 | A1 |
20040093554 | Hung | May 2004 | A1 |
20040098659 | Bjerke et al. | May 2004 | A1 |
20040196861 | Rinchiuso et al. | Oct 2004 | A1 |
20050005231 | Sun et al. | Jan 2005 | A1 |
20050063484 | Eroz et al. | Mar 2005 | A1 |
20050149841 | Kyung et al. | Jul 2005 | A1 |
20050257124 | Richardson et al. | Nov 2005 | A1 |
20050278606 | Richardson et al. | Dec 2005 | A1 |
20060156181 | Ha et al. | Jul 2006 | A1 |
20080282127 | Mantha et al. | Nov 2008 | A1 |
Number | Date | Country |
---|---|---|
0998087 | May 2000 | EP |
1093231 | Apr 2001 | EP |
07-050598 | Feb 1995 | JP |
2002-094405 | Mar 2002 | JP |
WO 02056559 | Jul 2002 | WO |
WO 02099976 | Dec 2002 | WO |
WO 02103631 | Dec 2002 | WO |
03001726 | Jan 2003 | WO |
WO 03065591 | Aug 2003 | WO |
WO 03088504 | Oct 2003 | WO |
WO 2004019268 | Mar 2004 | WO |
2004077733 | Sep 2004 | WO |
Number | Date | Country | |
---|---|---|---|
20100107032 A1 | Apr 2010 | US |
Number | Date | Country | |
---|---|---|---|
60456220 | Mar 2003 | US | |
60393457 | Jul 2002 | US | |
60398760 | Jul 2002 | US | |
60403812 | Aug 2002 | US | |
60421505 | Oct 2002 | US | |
60421999 | Oct 2002 | US | |
60440199 | Jan 2003 | US | |
60447641 | Feb 2003 | US | |
60469356 | May 2003 | US | |
60482107 | Jun 2003 | US | |
60482112 | Jun 2003 | US | |
60423710 | Nov 2002 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 11186265 | Jul 2005 | US |
Child | 12498968 | US | |
Parent | 10613877 | Jul 2003 | US |
Child | 11186265 | US |