Abstract: Operational parameter adaptable LDPC (Low Density Parity Check) decoder. A novel means is presented by which LDPC coded signal can be decoded, and any one or more operational parameters can be adjusted during the decoding processing. For example, the original information extracted from a received LDPC coded signal (e.g., log likelihood ratios (LLRs)), can be modified during (or before) the iterative decoding processing performed in accordance with decoding an LDPC coded signal. Such modification of an operational parameter can include any one or combination of scaling, compression (and expansion/decompression), adding an offset to or subtracting an offset from, scaling, rounding, and/or some other modification of an operational parameter. The bit (or variable) edge messages and/or the check edge messages can also undergo modification during decoding processing.

Abstract: Multi-code LDPC (Low Density Parity Check) decoder. Multiple LDPC coded signals can be decoded using hardware provisioned for a minimum requirement needed to decode each of the multiple LDPC coded signals. In embodiments where each LDPC matrix (e.g., employed to decode each LDPC coded signal) includes a common number of non-null sub-matrices, then a same number of memories are employed when decoding each LDPC coded signal. However, those particular memories employed can be different subsets for when decoding each LDPC coded signal. In embodiments where each LDPC code includes a different number of non-null sub-matrices within its respective LDPC matrix, then a different number of memories are employed when decoding each LDPC coded signal. Various degrees of parallelism in decoding can also be employed in which different numbers of bit engines and check engines can be employed when decoding different LDPC coded signals.

Abstract: Multi-code LDPC (Low Density Parity Check) decoder. Multiple LDPC coded signals can be decoded using hardware provisioned for a minimum requirement needed to decode each of the multiple LDPC coded signals. In embodiments where each LDPC matrix (e.g., employed to decode each LDPC coded signal) includes a common number of non-null sub-matrices, then a same number of memories are employed when decoding each LDPC coded signal. However, those particular memories employed can be different subsets for when decoding each LDPC coded signal. In embodiments where each LDPC code includes a different number of non-null sub-matrices within its respective LDPC matrix, then a different number of memories are employed when decoding each LDPC coded signal. Various degrees of parallelism in decoding can also be employed in which different numbers of bit engines and check engines can be employed when decoding different LDPC coded signals.

Abstract: Multi-code LDPC (Low Density Parity Check) decoder. Multiple LDPC coded signals can be decoded using hardware provisioned for a minimum requirement needed to decode each of the multiple LDPC coded signals. In embodiments where each LDPC matrix (e.g., employed to decode each LDPC coded signal) includes a common number of non-null sub-matrices, then a same number of memories are employed when decoding each LDPC coded signal. However, those particular memories employed can be different subsets for when decoding each LDPC coded signal. In embodiments where each LDPC code includes a different number of non-null sub-matrices within its respective LDPC matrix, then a different number of memories are employed when decoding each LDPC coded signal. Various degrees of parallelism in decoding can also be employed in which different numbers of bit engines and check engines can be employed when decoding different LDPC coded signals.

Abstract: Distributed processing LDPC (Low Density Parity Check) decoder. A means is presented herein that includes an LDPC decoding architecture leveraging a distributed processing technique (e.g., daisy chain) to increase data throughput and reduce memory storage requirements. Routing congestion and critical path latency are also improved thereby. Each daisy chain includes a number of registers, and a number of localized MUXs (e.g., MUXs having merely 2 inputs each). The means presented herein also does not contain any barrel shifters, high fan-in multiplexers, or interconnection networks; therefore, the critical path is relatively short and it can also be pipelined to further increase data throughput. If desired, a communication device can include multiple configurations of such daisy chains to accommodate the decoding of various LDPC coded signals (e.g., such as for an application and/or communication device that must decoded LDPC codes using different low density parity check matrices).

Abstract: Distributed processing LDPC (Low Density Parity Check) decoder. A means is presented herein that includes an LDPC decoding architecture leveraging a distributed processing technique (e.g., daisy chain) to increase data throughput and reduce memory storage requirements. Routing congestion and critical path latency are also improved thereby. Each daisy chain includes a number of registers, and a number of localized MUXs (e.g., MUXs having merely 2 inputs each). The means presented herein also does not contain any barrel shifters, high fan-in multiplexers, or interconnection networks; therefore, the critical path is relatively short and it can also be pipelined to further increase data throughput. If desired, a communication device can include multiple configurations of such daisy chains to accommodate the decoding of various LDPC coded signals (e.g., such as for an application and/or communication device that must decoded LDPC codes using different low density parity check matrices).

Abstract: Communication device architecture for in-place constructed LDPC (Low Density Parity Check) code. Intelligent design of LDPC codes having similar characteristics there between allows for a very efficient hardware implementation of a communication device that is operative to perform encoding of respective information bit groups using more than one type of LDPC codes. A switching module can select any one of the LDPC codes within an in-place LDPC code for use by an LDPC encoder circuitry to generate an LDPC coded signal. Depending on which sub-matrices of a superimposed LDPC matrix are enabled or disabled, one of the LDPC matrices from within an in-place LDPC code matrix set may be selected. A corresponding, respective generator matrix may be generated from each respective LDPC matrix. Selection among the various LDPC codes may be in accordance with a predetermined sequence, of based operating conditions of the communication device or communication system.

Abstract: Low complexity communication device employing in-place constructed LDPC (Low Density Parity Check) code. Intelligent design of LDPC codes having similar characteristics there between allows for a very efficient hardware implementation of a communication device that is operative to perform decoding of more than one type of LDPC coded signals. A common basis of decoder hardware (e.g., decoder circuitry) is employed when decoding all of the various types of LDPC coded signals that such a communication device can decode. However, all of the decoder hardware is only employed to decode signals corresponding to the lowest code rate LDPC code supported by the communication device. A first subset of the decoder hardware is employed to decode signals corresponding to the second to lowest code rate LDPC code, a second subset (being less than the first subset) is employed to decode signals corresponding to the third to lowest code rate LDPC code, etc.

Abstract: Selective merge and partial reuse LDPC (Low Density Parity Check) code construction for limited number of layers Belief Propagation (BP) decoding. Multiple LDPC matrices may be generated from a base code, such that multiple/distinct LDPC coded signals may be encoded and/or decoded within a singular communication device. Generally speaking, a first LDPC matrix is modified in accordance with one or more operations thereby generating a second LDPC matrix, and the second LDPC matrix is employed in accordance with encoding an information bit thereby generating an LDPC coded signal (alternatively performed using an LDPC generator matrix corresponding to the LDPC matrix) and/or decoding processing of an LDPC coded signal thereby generating an estimate of an information bit encoded therein. The operations performed on the first LDPC matrix may be any one of, or combination of, selectively merging, deleting, partially re-using one or more sub-matrix rows, and/or partitioning sub-matrix rows.

Abstract: A baseband unit includes an input/output interface and a processing module. The input/output interface module receives a data word of outbound data and outputs a plurality of outbound symbols. The processing module converts the data word into a bit repetitive data word; encodes the bit repetitive data word to produce an encoded data block; and converts the encoded data block into the plurality of outbound symbols.

Abstract: Accumulating LDPC (Low Density Parity Check) decoder. The accumulating decoding architecture described herein is applicable to LDPC codes operating on a parity check matrix, H, consisting of CSI (Cyclic Shifted Identity) sub-matrices (or matrix sub-blocks) or permuted identity sub-matrices (or matrix sub-blocks). In such a structure, the entire LDPC matrix is broken into square sub-matrices such that each sub-matrix consists of either a CSI sub-matrix or a permuted identity sub-matrix, or a null matrix. The iterative decoding process operates by updating of APP (a posteriori probability) or gamma (?) values and check edge message (?) values, and this by updating one or more individual rows within a number of sub-matrix rows (or all sub-matrix or sub-block rows) are processed in parallel. The amount of parallelism is specified by the designer and is typically an integer divisor of the sub-matrix (or sub-block) size.

Abstract: Permuted accelerated LDPC (Low Density Parity Check) decoder. This decoding approach operates by processing, in parallel, selected rows for multiple individual LDPC matrix rows from various sub-matrix rows (e.g., first group of rows from a first sub-matrix row, second group of rows from a second sub-matrix row, etc.). A memory structure of daisy chains is employed for memory management of APP (a posteriori probability) values and also for check edge messages/intrinsic information (?) values. A first group of daisy chains may be employed for memory management of the APP values, and a second group of daisy chains may be employed for memory management of the check edge messages. These daisy chains operate to effectuate the proper alignment of APP (or gamma(?)) values and check edge message/intrinsic information (?) values for their respective updating in successive decoding iterations.

Abstract: LDPC coding systems for 60 GHz millimeter wave based physical layer extension. LDPC (Low Density Parity Check) encoding in cooperation with sub-carrier interleaving, in the context of orthogonal frequency division multiplexing (OFDM), and appropriate symbol mapping is performed in accordance with transmit processing as may be performed within a communication device. In a receiving communication device, receive processing may be performed on a received signal based on the type of LDPC, sub-carrier interleaving, and symbol mapping thereof. The LDPC code employed in accordance with such LDPC encoding may have a partial-tree like structure. In addition, appropriate manipulation of the bits assigned to respective sub-carriers may be performed to ensure that the bits emplaced in the MSB (Most Significant Bit) location of various symbols has some desired diversity (e.g., from different codewords, from appropriately different locations within a given codeword, etc.).

Abstract: Multi-code LDPC (Low Density Parity Check) decoder. Multiple LDPC coded signals can be decoded using hardware provisioned for a minimum requirement needed to decode each of the multiple LDPC coded signals. In embodiments where each LDPC matrix (e.g., employed to decode each LDPC coded signal) includes a common number of non-null sub-matrices, then a same number of memories are employed when decoding each LDPC coded signal. However, those particular memories employed can be different subsets for when decoding each LDPC coded signal. In embodiments where each LDPC code includes a different number of non-null sub-matrices within its respective LDPC matrix, then a different number of memories are employed when decoding each LDPC coded signal. Various degrees of parallelism in decoding can also be employed in which different numbers of bit engines and check engines can be employed when decoding different LDPC coded signals.

Abstract: Distributed processing LDPC (Low Density Parity Check) decoder. A means is presented herein that includes an LDPC decoding architecture leveraging a distributed processing technique (e.g., daisy chain) to increase data throughput and reduce memory storage requirements. Routing congestion and critical path latency are also improved thereby. Each daisy chain includes a number of registers, and a number of localized MUXs (e.g., MUXs having merely 2 inputs each). The means presented herein also does not contain any barrel shifters, high fan-in multiplexers, or interconnection networks; therefore, the critical path is relatively short and it can also be pipelined to further increase data throughput. If desired, a communication device can include multiple configurations of such daisy chains to accommodate the decoding of various LDPC coded signals (e.g., such as for an application and/or communication device that must decoded LDPC codes using different low density parity check matrices).

Abstract: LDPC (Low Density Parity Check) decoder employing distributed check into variable node architecture. A means of decoding processing is presented in which at least one portion of the check node processing functionality is actually integrated into the variable/bit node processing functionality (e.g., distributed check node embodiment). In alternative embodiments, at least one portion of the variable/bit node processing functionality is actually integrated into the check node processing functionality (e.g., distributed variable/bit node embodiment). In even other embodiments, some check node processing functionality is moved and integrated into the variable/bit node processing functionality, and some variable/bit node processing functionality is also moved and integrated into the check node processing functionality (e.g., combined distributed embodiment).

Abstract: Operational parameter adaptable LDPC (Low Density Parity Check) decoder. A novel means is presented by which LDPC coded signal can be decoded, and any one or more operational parameters can be adjusted during the decoding processing. For example, the original information extracted from a received LDPC coded signal (e.g., log likelihood ratios (LLRs)), can be modified during (or before) the iterative decoding processing performed in accordance with decoding an LDPC coded signal. Such modification of an operational parameter can include any one or combination of scaling, compression (and expansion/decompression), adding an offset to or subtracting an offset from, scaling, rounding, and/or some other modification of an operational parameter. The bit (or variable) edge messages and/or the check edge messages can also undergo modification during decoding processing.

Abstract: A method and apparatus are disclosed for reducing the computational complexity of the RSSE technique. The apparatus and associated method does not assume that the signal energy of a pulse that has gone through a channel is always concentrated primarily in the initial taps, as is true for a minimum phase channel. The present invention, however, recognizes that the signal energy is often concentrated in just a few channel coefficients, with the remaining channel coefficients being close to zero. A receiver apparatus and associated method is disclosed for reducing the number of channel coefficients to be processed with a high complexity cancellation algorithm from L to V+K which contain the majority of the signal energy, while processing the L−(K+V) non-selected coefficients with a lower complexity algorithm. By only processing the intersymbol interference caused by a reduced number of channel coefficients (i.e.

Abstract: A block-parallel decoding algorithm and corresponding decoder architecture utilizes a set of interconnected processing nodes configured in the form of a probability dependency graph. The probability dependency graph is characterized at least in part by a code used to encode blocks of bits or symbols, and the processing nodes implement a block-parallel decoding process for blocks of the bits or symbols to be decoded. The probability dependency graph may be, for example, a bipartite probability dependency graph which includes a set of N variable nodes and a set of T check nodes, with one of the N variable nodes being associated with each of N bits or symbols of a given block to be decoded. A single iteration of the block-parallel decoding process produces within the variable nodes an updated estimate for every bit or symbol in the given block, and may produce within the variable nodes an a-posteriori probability associated with the decoded bit or symbol for a soft-decision decoder.