Nationaluniversity of Ireland, Maynooth

Massachusetts Institute of Technology

Boston University

Kenneth R Duffy

Muriel Medard

Amit Solomon

Alejandro Cohen

Flavio Du Pin Calmon

Wei An

Linda M Zeger

Rabia Tugce Yazicigil Kirby

Mark M Christiansen

Vaibhav Bansal

Jiange Li

Described is a decoder suitable for use with any communication or storage system. The described decoder has a modular decoder hardware architecture capable of implementing a noise guessing process and due to its dependency only on noise, the decoder design is independent of any encoder, thus making it a universal decoder. Hence, the decoder architecture described herein is agnostic to any coding scheme.

Universal guessing random additive noise decoding (GRAND) decoder

Described are concepts, systems, devices and methods that enhance decoding performance of channels subject to correlated noise. The concepts, systems, devices and methods can be used with any combination of codes, code-rates and decoding techniques. In embodiments, a continuous realization of effective noise is estimated from a lead channel by subtracting its decoded output from its received signal. This estimate is then used to improve the accuracy of decoding of an otherwise orthogonal channel that is experiencing correlated effective noise. In this approach, channels aid each other through the post-decoding provision of estimates of effective noise. In some embodiments, the lead channel is not pre-determined, but is chosen dynamically based on which of a plurality of decoders completes first, or using soft information including an estimate of effective noise that is least energetic or most likely to have occurred.

Noise recycling

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.

Decoding signals by guessing noise

The present application concerns an iterative bit-flipping decoding method using symbol or bit reliabilities, which is a variation of GRAND decoding and is denoted by ordered reliability bits GRAND (ORBGRAND). It comprises receiving a plurality of demodulated symbols from a noisy transmission channel; and receiving for the plurality of demodulated symbols, information indicating a ranked order of reliability of at least the most unreliable information contained within the plurality of demodulated symbols. A sequence of putative noise patterns from a most likely pattern of noise affecting the plurality of symbols through one or more successively less likely noise patterns is provided. Responsive to the information contained within the plurality of symbols not corresponding with an element of a code-book comprising a set of valid codewords, a first in the sequence of putative noise patterns is used to invert the most unreliable information of the information contained within the plurality of symbols to obtain a potential codeword, and responsive to the potential codeword not corresponding with an element of the code-book, repeatedly: a next likely noise pattern from the sequence of putative noise patterns is applied to invert a noise effect on the received plurality of demodulated symbols to provide a potential codeword, each successive noise pattern indicating an inversion of information for one or more demodulated symbols for a next more reliable combination of information contained within the plurality of symbols, until the potential codeword corresponds with an element of the code-book.

Iterative bit flip decoding based on symbol reliabilities

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. In various embodiments, soft information is used to generate a symbol mask that identifies the collection of symbols that are suspected to differ from the channel input, and only these are subject to guessing. This decoder embodies or approximates maximum likelihood (optionally with soft information) decoding for any code. In some embodiments, the decoder tests abounded number of noise sequences, abandoning the search and declaring an erasure after these sequences are exhausted.

Decoding concatenated codes by guessing noise

Secrecy scheme systems and associated methods using list source codes for enabling secure communications in communications networks are provided herein. Additionally, improved information-theoretic metrics for characterizing and optimizing said secrecy scheme systems and associated methods are provided herein. One method of secure communication comprises receiving a data file at a first location, encoding the data file using a list source code to generate an encoded file, encrypting a select portion of the data file using a key to generate an encrypted file, and transmitting the encoded file and the encrypted file to an end user at a destination location, wherein the encoded file cannot be decoded at the destination location until the encrypted file has been received and decrypted by the end user, wherein the end user possesses the key.

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Dublin, Ireland

Kenneth R Duffy