Abstract:
A polarization stream architecture is described. A transmitter may implement a reverse polarization stream to shape a first source signal in a first signal space to a first target signal in a second signal space. The reverse polarization stream is implemented as a cascade of reverse polarization steps. Each reverse polarization step includes a shuffle function, a split function, a scaling function and an offset function. Machine-learning techniques may be used to implement the scaling function and the offset function. A receiver may implement a polarization stream to recover the source signal.
Abstract:
Systems and methods of communicating using asymmetric polar codes are provided which overcome the codeword length constraints of systems and methods of communicating that use traditional polar codes. Used herein, asymmetric polar codes refers to a polarizing linear block code of any arbitrary length that is constructed by connecting together constituent polar codes of unequal length. Asymmetric polar codes may be known by other names. In comparison to conventional solutions for variable codeword length, asymmetric polar codes may provide more flexibility, improved performance, and/or reduced complexity of decoding, encoding, or code design. The system and method provide a flexible, universal, and well-defined coding scheme and to provide sound bit-error correction performance and low decoding latency (compared with current length-compatible methods which can be used with current hardware designs). For the most part, the provided embodiments can be implemented with nearly all available current encoding/decoding polar code techniques.
Abstract:
An ordered number sequence may be determined based on an ordered sub-channel sequence specifying an order of N sub-channels that are defined by a code and that have associated reliabilities for input bits at N input bit positions. The ordered number sequence represents the ordered sub-channel sequence as a sequence of fewer than N numbers. The numbers in the ordered number sequence indicate the sub-channels, by representing numbers of the sub-channels for example, from different subsets of the N sub-channels, that appear in the order specified by the ordered sub-channel sequence. Using ordered number sequences, longer ordered sub-channel sequences could be constructed from smaller ordered sub-channel sequences, and/or sub-channels that to be selected from a longer ordered sub-channel sequence could be divided into two or more parts, with each part to be selected from shorter ordered sub-channel sequences.
Abstract:
Embodiments of this disclosure enhance the error detection performance of parallel polar encoding by cross-concatenating parity bits between segments of information bits transmitted over different sets of sub-channels. In one embodiment, a first segment of information bits is transmitted over a first set of sub-channels, and at least a second segment of information bits, and a masked parity bit, are transmitted over a second set of sub-channels. A value of the masked parity bit is equal to a bitwise combination of a first parity bit computed from the first segment of information bits and a second parity bit computed from the second segment of information bits. The bitwise combination may be a bitwise AND, a bitwise OR, or a bitwise XOR of the respective parity bits.
Abstract:
Methods for encoding and decoding Polar codes are provided, together with apparatuses for performing the methods. An encoding method combines first and second sequences of information bits and CRC bits and a plurality of frozen bits into an input vector. The input vector is multiplied by a generator matrix for a Polar code to produce a concatenated codeword. A decoding method receives such a codeword and produces a decoded vector by generating successive levels of a decision tree. For a first number of levels of the decision tree, paths beyond a first maximum number of most probable paths are discarded. For a second number of levels of the decision tree, paths beyond a second maximum number of most probable paths are discarded. In some cases, the decoding method may have improved performance compared to some decoding methods for non-concatenated codewords.
Abstract:
Methods and apparatuses relating to QR decomposition using a multiple execution unit processing system are provided. A method includes receiving input values at the processing system and generating a first set of values based on the input values, where at least some of the first values are computed in parallel. A second set of values are generated recursively based on values in the first set. A third set of values are generated based on values in the second set, where at least some of the values in the third set are computed in parallel. The recursive component may be simplified to consist of one or more low latency operations. The processing performance of operations relating to QR decomposition may therefore be improved by using the parallelism available in multiple execution unit systems.
Abstract:
Embodiments are provided for an asynchronous processor with an asynchronous Instruction fetch, decode, and issue unit. The asynchronous processor comprises an execution unit for asynchronous execution of a plurality of instructions, and a fetch, decode and issue unit configured for asynchronous decoding of the instructions. The fetch, decode and issue unit comprises a plurality of resources supporting functions of the fetch, decode and issue unit, and a plurality of decoders arranged in a predefined order for passing a plurality of tokens. The tokens control access of the decoders to the resources and allow the decoders exclusive access to the resources. The fetch, decode and issue unit also comprises an issuer unit for issuing the instructions from the decoders to the execution unit
Abstract:
Some embodiments of the present disclosure relate to inferencing using a trained deep neural network. Inferencing may, reasonably, be expected to be a mainstream application of 6G wireless networks. Agile, robust and accurate inferencing is important for the success of AI applications. Aspects of the present application relate to introducing coding theory into inferencing in a distributed manner. It may be shown that redundant wireless bandwidths and edge units help to ensure agility, robustness and accuracy in coded inferencing networks.
Abstract:
A codeword is generated based on a segmentation transform and a Polarization-Assisted Convolutional (PAC) code that includes an outer convolutional code and a polar code, and based on separate encoding of respective different segments of convolutionally encoded input bits according to the polar code. Each segment of the respective segments includes multiple bits of the convolutionally encoded input bits for which the separate encoding of the segment is independent of the separate encoding of other segments. Separate decoding may be applied to segments of such a codeword to decode convolutionally encoded input bits corresponding to the separately encoded segments of the convolutionally encoded input bits.
Abstract:
Embodiment techniques map parity bits to sub-channels based on their row weights. The row weight for a sub-channel may be viewed as the number of "ones" in the corresponding row of the Kronecker matrix or as a power of 2 with the exponent (i.e. the hamming weight) being the number of "ones" in the binary representation of the sub-channel index (further described below). In one embodiment, candidate sub-channels that have certain row weight values are reserved for parity bit (s). Thereafter, K information bits may be mapped to the K most reliable remaining sub-channels, and a number of frozen bits (e.g. N-K) may be mapped to the least reliable remaining sub-channels. Parity bits may then mapped to the candidate sub-channels, and parity bit values are determined based on a function of the information bits.