Abstract: Sub-matrix-based implementation of LDPC (Low Density Parity Check) decoder. A novel approach is presented by which an LDPC coded signal is decoded by processing 1 sub-matrix at a time. A low density parity check matrix corresponding to the LDPC code includes rows and columns of sub-matrices. For example, when performing bit node processing, 1 or more sub-matrices in a column are processed; when performing check node processing, 1 or more sub-matrices in a row are processed. If desired, when performing bit node processing, the sub-matrices in each column are successively processed together (e.g., all column 1 sub-matrices, all column 2 sub-matrices, etc.). Analogously, when performing check node processing, the sub-matrices in each row can be successively processed together (e.g., all row 1 sub-matrices, all row 2 sub-matrices in row 2, etc.).

Abstract: Partial-parallel implementation of LDPC (Low Density Parity Check) decoder. A novel approach is presented by which a selected number of cycles is performed during each of bit node processing and check node processing when performing error correction decoding of an LDPC coded signal. The number of cycles of each of bit node processing and check node processing need not be the same. At least one functional block, component, portion of hardware, or calculation can be used during both of the bit node processing and check node processing thereby conserving space with an efficient use of processing resources. At a minimum, a semi-parallel approach can be performed where 2 cycles are performed during each of bit node processing and check node processing. Alternatively, more than 2 cycles can be performed for each of bit node processing and check node processing.

Abstract: Iterative metric updating when decoding LDPC (Low Density Parity Check) coded signals and LDPC coded modulation signals. A novel approach is presented for updating the bit metrics employed when performing iterative decoding of LDPC coded signals. This bit metric updating is also applicable to decoding of signals that have been generated using combined LDPC coding and modulation encoding to generate LDPC coded modulation signals. In addition, the bit metric updating is also extendible to decoding of LDPC variable code rate and/or variable modulation signals whose code rate and/or modulation may vary as frequently as on a symbol by symbol basis. By ensuring that the bit metrics are updated during the various iterations of the iterative decoding processing, a higher performance can be achieved than when the bit metrics remain as fixed values during the iterative decoding processing.

Abstract: Single stage implementation of min*, max*, min and/or max to perform state metric calculation in soft-in soft-out (SISO) decoder. This allows for calculation of state metrics in an extremely efficient, fast manner. When performing min or max calculations, comparisons are made using 2 element combinations of the available inputs. Subsequently, logic circuitry employs the results of the 2 element comparisons the smallest (min) or largest (max) input. The max or min implementations may be employed as part of the max* and/or min* implementations. For max* and/or min* implementations, simultaneous calculation of appropriate values is performed while determining which input is the smallest or largest. Thereafter, the determination of which input is the smallest or largest is used to select the appropriate resultant value (of the values calculated) for max* and/or min*. Various degrees of precision are employed for the log correction values within the max* and/or min* implementations.

Abstract: Variable modulation within combined LDPC (Low Density Parity Check) coding and modulation coding systems. A novel approach is presented for variable modulation encoding of LDPC coded symbols. In addition, LDPC encoding, that generates an LDPC variable code rate signal, may also be performed as well. The encoding can generate an LDPC variable code rate and/or modulation signal whose code rate and/or modulation may vary as frequently as on a symbol by symbol basis. Some embodiments employ a common constellation shape for all of the symbols of the signal sequence, yet individual symbols may be mapped according different mappings of the commonly shaped constellation; such an embodiment may be viewed as generating a LDPC variable mapped signal. In general, any one or more of the code rate, constellation shape, or mapping of the individual symbols of a signal sequence may vary as frequently as on a symbol by symbol basis.

Abstract: Efficient construction of LDPC (Low Density Parity Check) codes with corresponding parity check matrix having CSI (Cyclic Shifted Identity) sub-matrices. These constructed LDPC codes can be implemented in multiple-input-multiple-output (MIMO) communication systems. One LDPC code construction approach uses CSI sub-matrix shift values whose shift values are checked instead of non-zero element positions within the parity check matrix (or its corresponding sub-matrices). When designing an LDPC code, this approach is efficient to find and avoid cycles (or loops) in the LDPC code's corresponding bipartite graph. Another approach involves GRS (Generalized Reed-Solomon) code based LDPC code construction. These LDPC codes can be implemented in a wide variety of communication devices, including those implemented in wireless communication systems that comply with the recommendation practices and standards being developed by the IEEE 802.11n Task Group (i.e., the Task Group that is working to develop a standard for 802.

Abstract: Efficient construction of LDPC (Low Density Parity Check) codes with corresponding parity check matrix having CSI (Cyclic Shifted Identity) sub-matrices. These constructed LDPC codes can be implemented in multiple-input-multiple-output (MIMO) communication systems. One LDPC code construction approach uses CSI sub-matrix shift values whose shift values are checked instead of non-zero element positions within the parity check matrix (or its corresponding sub-matrices). When designing an LDPC code, this approach is efficient to find and avoid cycles (or loops) in the LDPC code's corresponding bipartite graph. Another approach involves GRS (Generalized Reed-Solomon) code based LDPC code construction. These LDPC codes can be implemented in a wide variety of communication devices, including those implemented in wireless communication systems that comply with the recommendation practices and standards being developed by the IEEE 802.11n Task Group (i.e., the Task Group that is working to develop a standard for 802.

Abstract: Variable code rate and signal constellation turbo trellis coded modulation (TTCM) codec. A common trellis is employed at both ends of a communication system (in an encoder and decoder) to code and decode data at different rates. The encoding employs a single TTCM encoder whose output bits may be selectively punctured to support multiple modulations (constellations and mappings) according to a rate control sequence. A single TTCM decoder is operable to decode each of the various rates at which the data is encoded by the TTCM encoder. The rate control sequence may include a number of rate controls arranged in a period that is repeated during encoding and decoding. Either one or both of the encoder and decoder may adaptively select a new rate control sequence based on operating conditions of the communication system, such as a change in signal to noise ratio (SNR).

Abstract: Communication decoder employing single trellis to support multiple code rates and/or multiple modulations. A single trellis is employed by the decoder to decode a plurality of encoded symbols. Each of the plurality of encoded symbols is governed by a rate control. A rate control sequence, having a period, is used to decode the plurality of encoded symbols that may be arranged within a frame. Various parameters of the plurality of encoded symbols may vary on a symbol by symbol basis; these parameters may include modulation, constellation, mapping, and/or bandwidth efficiency. For example, various symbols may be encoded differently, yet they may all be decoded using the same trellis. The functionality of this decoder may be implemented within a variety of different decoder embodiments including a trellis code modulation (TCM) decoder, a turbo trellis code modulation (TTCM) decoder, and/or a parallel concatenated turbo code modulation (PC-TCM) decoder.

Abstract: A method for parallel concatenated (Turbo) encoding and decoding. Turbo encoders receive a sequence of input data tuples and encode them. The input sequence may correspond to a sequence of an original data source, or to an already coded data sequence such as provided by a Reed-Solomon encoder. A turbo encoder generally comprises two or more encoders separated by one or more interleavers. The input data tuples may be interleaved using a modulo scheme in which the interleaving is according to some method (such as block or random interleaving) with the added stipulation that the input tuples may be interleaved only to interleaved positions having the same modulo-N (where N is an integer) as they have in the input data sequence. If all the input tuples are encoded by all encoders then output tuples can be chosen sequentially from the encoders and no tuples will be missed.

Abstract: System correcting random and/or burst errors using RS (Reed-Solomon) code, turbo/LDPC (Low Density Parity Check) code and convolutional interleave. A novel approach is presented that combines different coding types within a communication system to perform various types of error correction. This combination of accommodating different coding types may be employed at either end of a communication channel (e.g., at a transmitter end when performing encoding and/or at a receiver end when performing decoding). By combining different coding types within a communication system, the error correcting capabilities of the overall system is significantly improved. The appropriate combination of turbo code and/or LDPC code along with RS code allows for error correction or various error types including random error and burst error (or impulse noise).

Abstract: System correcting random and/or burst errors using RS (Reed-Solomon) code, turbo/LDPC (Low Density Parity Check) code and convolutional interleave. A novel approach is presented that combines different coding types within a communication system to perform various types of error correction. This combination of accommodating different coding types may be employed at either end of a communication channel (e.g., at a transmitter end when performing encoding and/or at a receiver end when performing decoding). By combining different coding types within a communication system, the error correcting capabilities of the overall system is significantly improved. The appropriate combination of turbo code and/or LDPC code along with RS code allows for error correction or various error types including random error and burst error (or impulse noise).

Abstract: AMP (Accelerated Message Passing) decoder adapted for LDPC (Low Density Parity Check) codes. A novel approach is presented by which the LDPC coded signals may be decoded in a more efficient, faster, and less computationally intensive manner. Soft bit information, generated from decoding a higher layer square sub-matrix of a parity check matrix of the LDPC code, is employed to assist in the decoding of other square sub-matrices in subsequent layers. This approach allows the decoding of an LDPC code whose parity check matrix has column weight more than 1 (e.g., 2 or more), thereby allowing a much broader selection of LDPC codes to be employed in various communication systems. This approach also provides much improvement in terms of BER/BLER as a function of Eb/No (or SNR), and it can provide comparable (if not better) performance when performing significantly fewer (e.g., up to 50% fewer) decoding iterations that other approaches.

Abstract: Construction of LDPC (Low Density Parity Check) codes using GRS (Generalized Reed-Solomon) code. A novel approach is presented by which a GRS code may be employed to generate a wide variety of types of LDPC codes. Such GRS based LDPC codes may be employed within various types of transceiver devices implemented within communication systems. This approach may be employed to generate GRS based LDPC codes particular designed for various application arenas. As one example, such a GRS based LDPC code may be specifically designed for use in communication systems that operate in accordance with any standards and/or recommended practices of the IEEE P802.3an (10GBASE-T) Task Force.

Abstract: Construction of Irregular LDPC (Low Density Parity Check) codes using RS (Reed-Solomon) codes or GRS (Generalized Reed-Solomon) codes. A novel approach is presented by which a wide variety of irregular LDPC codes may be generated using GRS or RS codes. These irregular LDPC codes can provide better overall performance than regular LDPC codes in terms of providing for lower BER (Bit Error Rate) as a function of SNR (Signal to Noise Ratio). Such an irregular LDPC code may be appropriately designed using these principles thereby generating a code that is suitable for use in wireless communication systems including those that comply with the recommendation practices and standards being developed by the IEEE (Institute of Electrical & Electronics Engineers) 802.11n Task Group (i.e., the Task Group that is working to develop a standard for 802.11 TGn (High Throughput)).

Abstract: LDPC (Low Density Parity Check) coding and interleaving implemented in multiple-input-multiple-output (MIMO) communication systems. Initially, a novel approach is presented by which a wide variety of irregular LDPC codes may be generated using GRS or RS codes. These irregular LDPC codes can provide better overall performance than regular LDPC codes in terms of providing for lower BER (Bit Error Rate) as a function of SNR (Signal to Noise Ratio). A variety of communication device types are also presented that may employ the error correcting coding using a GRS-based irregular LDPC code, along with appropriately selected interleaving, to provide for even better performance. These communication devices may be implemented to in wireless communication systems including those that comply with the recommendation practices and standards being developed by the IEEE 802.11n Task Group (i.e., the Task Group that is working to develop a standard for 802.11 TGn (High Throughput)).

Abstract: Amplifying magnitude metric of received signals during iterative decoding of LDPC code and LDPC coded modulation. By appropriately selecting a metric coefficient value that is used to calculate the initial conditions when decoding LDPC coded signals, a significant reduction in BER may be achieved at certain SNRs. The appropriate selection of the metric coefficient value may be performed depending on the particular SNR at which a communication system is operating. By adjusting this metric coefficient value according to the given LDPC code, modulation, and noise variance, the overall performance of the decoding may be significantly improved. The convergence speed is slowed down so that the decoder will not go to the wrong codeword, and the moving range of the outputs of the decoder is restricted so that the output will not oscillate too much and will eventually move to the correct codeword.

Abstract: LDPC (Low Density Parity Check) coded 128 DSQ (Double Square QAM) constellation modulation and its associated labeling. A novel means is introduced by which a constellation may be arranged and mapping in its symbols may be determined to provide for improved performance. One application area in which this may be employed is transmission over twisted pair (typically copper) cabling existent within data centers of various networks. The operation of the IEEE 802.3 Ethernet local area networks currently being used (as well as those currently under development) would benefit greatly by employing the various principles presented herein. When this novel approach of an LDPC coded 128 DSQ constellation modulation combined with TH (Tomlinson-Harashima) preceding is employed within a communication device at a transmitter end of a communication channel (i.e., in a transmitter and/or a transceiver), the overall operation of a communication system may improve significantly when compared to prior techniques.

Abstract: A short length LDPC (Low Density Parity Check) code and modulation adapted for high speed Ethernet applications. In some instances, the short length-LDPC code and modulation may be employed within the recommended practices currently being developed by the IEEE 802.3an (10GBASE-T) Task Force. The IEEE 802.3an (10GBASE-T) Task Force has been commissioned to develop and standardize communications protocol adapted particularly for Ethernet operation over 4 wire twisted pair cables. A new LDPC code, some possible embodiments of constellations and the corresponding mappings, as well as possible embodiments of various parity check matrices, H, of the LDPC code are presented herein to provide for better overall performance than other proposed LDPC codes existent in the art of high speed Ethernet applications. Moreover, this proposed LDPC code may be decoded using a communication device having much less complexity than required to decode other proposed LDPC codes existent in this technology space.

Abstract: Fast min*? (min-star-minus) or max*? (max-star-minus) circuit in LDPC (Low Density Parity Check) decoder. A novel and efficient approach by which certain of the calculations required to perform check node processing within various types of decoders is presented. The functionality and architectures presented herein are applicable to LDPC decoders and may also be employed within other types of decoders that are operable to decode other types of coded signals as well. The parallel and sometimes simultaneous calculation and determination of certain parts of the overall resultant of the max*? and/or min*? processing allows for very fast operation when compared to prior art approaches.