| 摘要 |
Systems and methods for decoding block and concatenated codes are provided. These include advanced iterative decoding techniques based on belief propagation algorithms, with particular advantages when applied to codes having higher density parity check matrices such as iterative soft-input soft-output and list decoding of convolutional codes, Reed-Solomon codes and BCH codes. Improvements are also provided for performing channel state information estimation including the use of optimum filter lengths based on channel selectivity and adaptive decision-directed channel estimation. These improvements enhance the performance of various communication systems and consumer electronics. Particular improvements are also provided for decoding HD radio signals, satellite radio signals, digital audio broadcasting (DAB) signals, digital audio broadcasting plus (DAB+) signals, digital video broadcasting-handheld (DVB-H) signals, digital video broadcasting-terrestrial (DVB-T) signals, world space system signals, terrestrial-digital multimedia broadcasting (T-DMB) signals, and China mobile multimedia broadcasting (CMMB) signals. These and other improvements enhance the decoding of different digital signals. |
| 主权项 |
1. A method for iteratively decoding a digital signal, the signal being an Orthogonal Frequency-Division Multiplexed (OFDM) signal comprising OFDM reference subcarriers, OFDM data subcarriers, and OFDM symbol intervals, the method comprising:
performing OFDM demodulation and subcarrier de-mapping of the digital signal into system control and data sequence symbols to obtain received distorted modulated symbols; performing initial channel state information estimation based on the received distorted modulated symbols, wherein said received distorted modulated symbols are carried by a plurality of OFDM data subcarriers and a plurality of OFDM reference subcarriers in at least one OFDM symbol interval; performing phase correction of the received distorted modulated symbols based on the initial channel state information estimation into coherent demodulated signals; performing symbol-to-bit demapping of the coherent demodulated signals by calculating log-likelihood ratios of the system control and data sequences symbols; producing, by a decoder, one or more logical channel signals by de-interleaving and demultiplexing the log-likelihood ratios of the system control and data sequences symbols; processing the one or more logical channel signals by producing, by the decoder, soft estimates of convolutional code coded bits using soft-input soft-output decoding of one or more convolutional codes associated with the one or more logical channels; calculating improved channel state information by performing at least one additional iteration of channel state information estimation based on at least some of said soft estimates of convolutional code coded bits; and performing enhanced convolutional decoding of a set of data associated with the digital signal using said improved channel state information, wherein enhanced decoding of the set of data associated with the digital signal comprises:
list soft-input soft-output decoding of a convolutional code to produce a sequence of soft convolutional code information bits and a list that includes at least some of most likely sequences of hard decisions of information bits outputs of the convolutional code;upon determining that any of hard decision sequences of said soft information bits outputs of the convolutional code do not correspond to a codeword, soft-input soft-output decoding of an outer code using said soft information bits outputs of the convolutional code, wherein said soft-input soft-output decoding of said outer code operates on log-likelihood ratios of information bits outputs of the convolutional code using message passing and comprises:
generating P>1 binary parity check matrices with at least L sparse columns, wherein L is the number of rows of the parity check matrix and up to L sparse columns contain only a single entry equal to 1 per column, wherein sparse columns of each of P parity check matrices correspond to different subsets of up to L bit log-likelihood ratios of L+R least reliable bit log-likelihood ratios, wherein R≧P is a configurable integer,iteratively decoding said log-likelihood ratios using said P parity check matrices with sparse columns to produce updated log-likelihood ratios and employing soft-input soft-output message passing decoding, wherein the number of iterations of said decoding is based on one of a predetermined number of iterations and a determination that at least one of said P matrices produces a valid codeword, andupon determining that decoding using said P parity check matrices produces no valid codeword, performing additional decoding based at least in part on algebraic decoding of the sequences of said updated log-likelihood ratios, andupon determining that a hard decision sequence of said soft information bits outputs of the convolutional code corresponds to a codeword of the outer code, using the hard decision sequence as a decoded signal. |
