In an advanced adaptive modulation and coding (AMC) scheme, the code rate and the parity-check matrix (PCM) for low-density parity-check (LDPC) codes are adapted according to modulation formats and variable-iteration receivers. The degree distribution for the PCM adaptation is designed by heuristic optimization to minimize the required SNR via an extrinsic information transfer (EXIT) trajectory analysis for finite-iteration decoding. The method uses dynamic window decoding by generating spatially coupled PCM for quasi-cyclic LDPC convolutional coding. The method also provides a way to jointly optimize labeling and decoding complexity for high-order and high-dimensional modulations.

Techniques are described for protecting miscorrection in a codeword. In one example, the techniques include obtaining a first set of data to be encoded using a product code comprising one or more constituent codes, and generating a second set of data by performing a miscorrection avoidance procedure on the first set of data. The miscorrection avoidance procedure decreases a probability of miscorrection at a decoder. The techniques further includes jointly encoding the first and the second set of data using an encoding procedure corresponding to the product code to generate at least one encoded codeword, and storing the encoded codeword in the memory.

A memory circuit, such as an embedded DRAM array, stores information as groups of bits or data using information coding in storage and retrieval data, instead of each bit being stored separately. Write data words can be mapped to storage format words that are stored and defined by a Hadamard matrix. The storage format word is stored as charge levels in an addressable memory location. For retrieving stored data, charge levels are read from the storage cells and interpreted to a valid storage format word. Hadamard code maximal likelihood decoding can be used to derive a read data word corresponding to a previously written write data word. The write data word is then output as the result of a read of the selected addressable location, or a portion thereof. The mapping can be two or more Hadamard matrix mappings concatenated for each of a plurality of storage format words.

Error correction is proposed in which a syndrome calculation is carried out in a code domain of a second code and an efficient error correction algorithm is carried out in a code domain of a first code.

A method for data transmission includes receiving a first data stream for transmission to a mobile device, segmenting the first data stream to produce a first plurality of data segments and receiving a second data stream, where the second data stream including location information for the mobile device. The method continues by segmenting the second data stream to produce a second plurality of data segments, dividing a data segment of the first plurality of data segments into a first plurality of data blocks and then dividing a data segment of the second plurality of data segments into a second plurality of data blocks, where the data segment of the first plurality of data segments is time aligned with the data segment of the second plurality of data segments. A data matrix is then created from the first and second plurality of data blocks and then based on the data matrix transmitting a first data block from each of the first and second plurality of data blocks to a first relay unit. Finally, based on the data matrix a second data block from each of the first and second plurality of data blocks is transmitted to a second relay unit.

Methods, systems, and machine-readable mediums utilizing context information to create decoding feedback information to improve decoder accuracy and/or performance. In some examples, the context information is from layers of a network stack above the layers in which the decoders are present. The context information may be or be based upon information about previously received and decoded data and/or information about the sender to provide decoding feedback information to the decoder that is used either to correct a previous decoding error or to inform the decoder on which of a plurality of decoding choices is more likely to be correct. This may increase decoding performance by decreasing errors and in some examples, reducing the complexity of choices by eliminating certain decoding possibilities and thus increasing decoder efficiency.