The present application provides a data transmission method which includes: obtaining statistical characteristics of interferences; determining a total number of coding layers of multi-layer coding and a code rate and transmitting power of each coding layer according to the statistical characteristics of the interferences; processing to-be-transmitted information bits through data re-organization according to the determined total number of coding layers of the multi-layer coding to obtain information bits of each coding layer; coding the information bits of each coding layer respectively according to the determined code rate of each coding layer to obtain a coded data stream of each coding layer; processing the coded data stream of each coding layer through layer mapping and modulation according to the determined transmitting power of each coding layer to obtain a symbol stream to be transmitted; and transmitting the symbol stream to be transmitted.

Methods, systems, and devices are described for wireless communications. A transmitting device may generate first encoded bits by encoding first information bits using a polar code of a first size, N, and transmit the first encoded bits to a receiving device. After determining the receiving device failed to decode the encoded bits, the transmitting device may generate second encoded bits by encoding the first information bits using a polar code of a second size, 2N. In some cases, the transmitting device may use the first encoded bits and one or more copied information bits to generate the second encoded bits. The transmitting device may transmit the second encoded bits to the receiving device, along with an indication of the number of copied information bits used to generate the second encoded bits. The number of copied information bits may be based on changing channel conditions or transmission parameters.

Devices and methods described herein decode a sequence of coded symbols by guessing noise. In various embodiments, noise sequences are ordered, either during system initialization or on a periodic basis. Then, determining a codeword includes iteratively guessing a new noise sequence, removing its effect from received data symbols (e.g. by subtracting or using some other method of operational inversion), and checking whether the resulting data are a codeword using a codebook membership function. This process is deterministic, has bounded complexity, asymptotically achieves channel capacity as in convolutional codes, but has the decoding speed of a block code. In some embodiments, the decoder tests a bounded number of noise sequences, abandoning the search and declaring an erasure after these sequences are exhausted. Abandonment decoding nevertheless approximates maximum likelihood decoding within a tolerable bound and achieves channel capacity when the abandonment threshold is chosen appropriately.

Disclosed are devices, systems and methods for polar coding and decoding for correcting deletion and insertion errors caused by a communication channel. One exemplary method for error correction includes receiving a portion of a block of polar-coded symbols that includes d2 insertion or deletion symbol errors, the block comprising N symbols, the received portion of the block comprising M symbols; estimating, based on one or more recursive calculations in a successive cancellation decoder (SCD), a location or a value corresponding to each of the d errors; and decoding, based on estimated locations or values, the portion of the block of polar-coded symbols to generate an estimate of information bits that correspond to the block of polar-coded symbols, wherein the SCD comprises at least log.sub.2(N)+1 layers, each comprising up to d.sup.2N processing nodes arranged as N groups, each of the N groups comprising up to d.sup.2 processing nodes.

Devices and methods described herein decode a sequence of coded symbols by guessing noise. In various embodiments, noise sequences are ordered, either during system initialization or on a periodic basis. Then, determining a codeword includes iteratively guessing a new noise sequence, removing its effect from received data symbols (e.g. by subtracting or using some other method of operational inversion), and checking whether the resulting data are a codeword using a codebook membership function. This process is deterministic, has bounded complexity, asymptotically achieves channel capacity as in convolutional codes, but has the decoding speed of a block code. In some embodiments, the decoder tests a bounded number of noise sequences, abandoning the search and declaring an erasure after these sequences are exhausted. Abandonment decoding nevertheless approximates maximum likelihood decoding within a tolerable bound and achieves channel capacity when the abandonment threshold is chosen appropriately.

Devices and methods described herein decode a sequence of coded symbols by guessing noise. In various embodiments, noise sequences are ordered, either during system initialization or on a periodic basis. Then, determining a codeword includes iteratively guessing a new noise sequence, removing its effect from received data symbols (e.g. by subtracting or using some other method of operational inversion), and checking whether the resulting data are a codeword using a codebook membership function. This process is deterministic, has bounded complexity, asymptotically achieves channel capacity as in convolutional codes, but has the decoding speed of a block code. In some embodiments, the decoder tests a bounded number of noise sequences, abandoning the search and declaring an erasure after these sequences are exhausted. Abandonment decoding nevertheless approximates maximum likelihood decoding within a tolerable bound and achieves channel capacity when the abandonment threshold is chosen appropriately.

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.

Embodiments provide a method for transmitting, according to which the payload data included in the data packet is provided with at least one indicator, such that a degree of interference of the received data (e.g. already decided bits) provided by the receiver for receiving data packets (e.g. a simple cost-effective radio chip) can be determined based on the at least one indicator, such that the determined degree of interference can be considered during channel decoding of the channel-coded payload data for increasing efficiency of channel decoding.

Channel state information (CSI) scaling modules for use in a demodulator configured to demodulate a signal received over a transmission channel, the demodulator comprising a soft decision error corrector (e.g. LDPC decoder) configured to decode data carried on data symbols of the received signal based on CSI values. The CSI scaling module is configured to monitor the performance of the soft decision error corrector and in response to determining the performance of the soft decision error corrector is below a predetermined level, dynamically select a new CSI scaling factor based on the performance of the soft decision error corrector.

Systems and methods are disclosed for combining successive cancellation decoding of polar coding with channel estimation, using a non-elementary mixture of information and redundancy bits for both channel estimation and error correction. For example, select bits of the polar encoder output may be used for an implicit parity check. Reliably-decoded bits may be iteratively incorporated into the set of pilots. The result is a semi-blind approach for channel estimation, which may have applicability to common wireless communication systems, particularly a cellular control channel, or transmissions of short messages on a cellular data channel.