Her Majesty the Queen in Right of Canada, As Represented by the Minister of Industry Through the Communication Research Centre

Her Majesty the Queen in Right of Canada, As Represented by the Minister

Cortina Systems Corporation

Her Majesty the Queen in Right of Canada As Represented by the Minister of Industry Through the Communications Research Centre Canada

Inphi Corporation

Her Majesty the Queen in Right of Canada, As Represented by the Minister of Industry Through the Communications Research Centre

Her Majesty the Queen in Right of Canada As Represented by the Minister of Indusrty, Though the Communications Research Centre Canada

John Lodge

Andrew Hunt

Paul Guinand

Stewart N Crozier

Arash Farhoodfar

Benjamin P Smith

Frank Robert Kschischang

Ron Kerr

Ken Gracie

Stewart Crozier

In staircase forward error correction coding, a stream of data symbols are mapped to data symbol positions in a sequence of two-dimensional symbol blocks B, a positive integer. Each of the symbol blocks has data symbol positions and coding symbol positions. Coding symbols for the coding symbol positions in each symbol block Bin the sequence are computed. The coding symbols are computed such that, for each symbol block Bthat has a preceding symbol block Band a subsequent symbol block Bin the sequence, symbols at symbol positions along one dimension of the preceding symbol block B, concatenated with the data symbols and the coding symbols along the other dimension in the symbol B, form a codeword of a FEC component code, and symbols at symbol positions along the one dimension of the symbol B, concatenated with the data symbols and the coding symbols along the other dimension in the subsequent symbol block B, form a codeword of the FEC component code. Thus, each row in [BB] and each column in for example, is a valid codeword.

Staircase forward error correction coding

In staircase forward error correction coding, a stream of data symbols are mapped to data symbol positions in a sequence of two-dimensional symbol blocks B, i a positive integer. Each of the symbol blocks has data symbol positions and coding symbol positions. Coding symbols for the coding symbol positions in each symbol block Bin the sequence are computed. The coding symbols are computed such that, for each symbol block Bthat has a preceding symbol block Band a subsequent symbol block Bin the sequence, symbols at symbol positions along one dimension of the preceding symbol block B, concatenated with the data symbols and the coding symbols along the other dimension in the symbol block B, form a codeword of a FEC component code, and symbols at symbol positions along the one dimension of the symbol block B, concatenated with the data symbols and the coding symbols along the other dimension in the subsequent symbol block B, form a codeword of the FEC component code. Thus, each row in [BB] and each column in for example, is a valid codeword.

The invention relates to a method and apparatus for acquiring a complex spreading code of a direct sequence spread spectrum signal (DSSS) by acquiring a state of a spreading code generator capable of generating the complex spreading code. A sequence of bipolar differential product values, which sign is independent on data transmitted by the DSSS signal, is obtained by combining in-phase and quadrature samples of the DSSS signal for adjacent chip intervals. This sequence is provided to a linear block decoder for obtaining a codeword of a linear block code, which is defined by a structure of the spreading generator and the differential product operation. The codeword is used to compute the state of the spreading code generator.

Spreading code acquisition for direct sequence spread spectrum signals

A method for lost speech samples recovery in speech transmission systems is disclosed. The method employs a waveform coder operating on digital speech samples. It exploits the composite model of speech, wherein each speech segment contains both periodic and colored noise components, and separately estimates these two components of the unreliable samples. First, adaptive FIR filters computed from received signal statistics are used to interpolate estimates of the periodic component for the unreliable samples. These FIR filters are inherently stable and typically short, since only strongly correlated elements of the signal corresponding to pitch offset samples are used to compute the estimate. These periodic estimates are also computed for sample times corresponding to reliable samples adjacent to the unreliable sample interval. The differences between these reliable samples and the corresponding periodic estimates are considered as samples of the noise component. These samples, computed both before and after the unreliable sample interval, are extrapolated into the time slot of the unreliable samples with linear prediction techniques. Corresponding periodic and colored noise estimates are then summed. All required statistics and quantities are computed at the receiver, eliminating any need for special processing at the transmitter. Gaps of significant duration, e.g., in the tens of milliseconds, can be effectively compensated.

Method for recovery of lost speech data

A method of decoding soft input information related to a transmitted word of a linear block code (n, k) and providing hard or soft output information is disclosed. The method comprises the steps of forming a reliability vector from the input information, identifying (n&#x2212;k) linearly independent least reliable symbols and k most reliable symbols, converting a parity check matrix of the linear block code to a pseudo-systematic form with respect to the least reliable symbols, calculating extrinsic information and composite information for the most reliable symbols using the soft input information and the pseudo-systematic parity check matrix, and calculating extrinsic information for the least reliable systems using composite information for the most reliable symbols.

Soft input decoding for linear codes

A method for generating new forward error correction codes, called skew codes, for the reliable transmission of data in noisy channels is disclosed. The method involves adding additional sets of parity equations across the third dimension of a cubic array of bits. The parity equations are applied to the cubic array such that the rectangular patterns of one square array do not match up with a rectangular pattern in another square array. By selecting skew mapping parameters of the parity equations from a set of quadratic residues of prime numbers according to specific design rules, the resulting codes are well suited to low-complexity high-speed iterative decoding, and have error correction performance and error detection capability, particularly for applications requiring high code rates. An improved decoding method for decoding skew codes and any code that is defined by a set of sum-to-identity parity equations initially decoded using an algorithm that provides confidence values on all the symbols at every symbol time is also disclosed. Generally, the improved decoding method will make hard decisions based upon the soft decisions passed from the failed iterative decoding system to provide a valid code word, through manipulation of the parity check matrix and reduction of its columns and rows.

High-performance error-correcting codes with skew mapping

A method of creating tail-biting recursive systematic convolutional and turbo codes, and the associated encoders, are described herein. According to the method, symbols from the set of data to be transmitted are used to preset the starting state of the encoder, and are replaced in a systematic set by an equivalent number of tail-biting symbols that force the ending state of the encoder to be the same as the starting state. The presetting of the starting state allows for simpler calculations in choosing the tail-biting symbols, and allows a message to be transmitted with a reduced number of symbols The reduction in the number of symbols used for overhead in this invention provides an increase in the data transmission rate.

Tail-biting turbo-code encoder and associated decoder

Methods of reduced-complexity max-log-APP processing are disclosed for use with Turbo and Turbo-like decoders. The invented methods of decoding are derived from max-log-APP processing and significantly lower the processing required for decoding convolutional codes by eliminating a portion of the calculations conventionally associated with max-log-APP processing. The disclosed embodiments provide simplified methods of metric combining based on determining the bits of an MLSE sequence with different alternative approaches. Also disclosed is an early stopping method that uses the reduced-complexity max-log-APP decoder to reduce the average number of decoding operations required by an iterative Turbo decoder.

Reduced-complexity max-log-APP decoders and related turbo decoders

Interleavers based on golden-section increments are disclosed for use with Turbo and Turbo-like error-correcting codes. The interleavers have a tendency to maximally spread the error-bursts generated by an error-burst channel or decoder, independent of the error-burst length. The code block size uniquely defines a golden section increment without having to perform a time consuming search for the best increment value. The disclosed embodiments include golden relative prime interleavers, golden vector interleavers and dithered golden vector interleavers. Also disclosed are methods to reduce the size of memory required for storing the interleaving indexes.

Interleaving with golden section increments

A method of encoding data is described herein. According to the method, source data elements are coded using one or more product codes having a common component code. The resulting one or more primary product codewords consist of a plurality of first codewords of the common component code. One or more first sets of codewords of the common component code are assembled such that each of the first sets comprises two or more distinct first codewords forming part of a same primary product codeword. Each of the codewords of each of the first sets is codeword-mapped to a second codeword of the common component code using a one-to-one codeword-mapping. One or more second sets of second codewords are provided, where each second set corresponds to a first set of codewords. The codeword-mapping includes re-ordering, according to a known interleaving pattern, the symbols within a codeword. The codeword-mappings are such that if all of the codewords of a first set are from a same primary product codeword, then some codeword-mappings applied to the codewords of the first set are different, and if two or more repetitions of a same codeword are included in a single first set, then the codeword-mappings applied to those repetitions are different. Each set of second codewords is coded using a systematic code so as to generate a secondary product codeword for a product code having as component codes the common component code and the systematic code. Then, the primary product codewords and the non-systematic portion of the secondary product codewords are provided as encoded output data.

High-performance low-complexity error-correcting codes

The invention comprises an enhancement to max-log-APP processing that significantly reduces performance degradation associated with introducing the 'max' approximation into log-APP computations, while still maintaining lower computational complexity associated with max-log-APP processing. This enhancement is achieved by adjusting extrinsic information produced by a max-log-APP process where the magnitude of the extrinsic information is reduced, for example, by multiplying it with a scale factor between 0 and 1.

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Dunrobin, Canada

John Lodge