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: Methods and apparatuses for measuring a distance between two signal distributions in a common signal space are described. A measurement network is configured to receive first and second signal distributions as input and output a measurement of a Wasserstein distance between the first and second signal distributions. The measurement network may be implemented using a neural network.

Abstract: A number K of N sub-channels that are defined by a code and that have associated reliabilities for input bits at N input bit positions, are to be selected to carry bits that are to be encoded. A localization area that includes multiple sub-channels and is located below fewer than K of the N sub-channels in a partial order of the N sub-channels is determined based on one or more coding parameters. The fewer than K sub-channels of the N sub-channels above the localization area in the partial order are selected, and a number of sub-channels from those in the localization area are also selected. The selected fewer than K sub-channels and the number of sub-channels selected from those in the localization area together include K sub-channels to carry the bits that are to be encoded.

Abstract: Methods and apparatuses for measuring a distance between two signal distributions in a common signal space are described. A measurement network is configured to receive first and second signal distributions as input and output a measurement of a Wasserstein distance between the first and second signal distributions. The measurement network may be implemented using a neural network.

Abstract: A first error-detecting code (EDC) is computed based on a first segment of a block of information that is to be encoded, and a second EDC is computed based on at least a second segment of the block of information. The first EDC is masked with a first masking segment and the second EDC with a second masking segment to generate a first masked EDC and a second masked EDC. The first masking segment and the second masking segment are associated with a target receiver of the block of information. A codeword is generated based on a code and an input vector that includes the first segment, the first masked EDC, the second segment, and the second masked EDC. This type of coding could be useful to support early termination of blind detection at a decoder, for example.

Abstract: Methods and apparatuses for feature-driven communications are described. A set of features describing an observed subject is transmitted by a transmitting electronic device (ED) to a base station (BS). The BS translates the received features to another set of transmission features to be transmitted to a receiving ED. The receiving ED recovers information about the subject from the features received from the BS.

Abstract: A wireless network can generate candidate signal configurations for physical transmissions to or from a user equipment (UE) in a radio environment. The generation of candidate signal configurations can be performed using a first neural network that is associated with the UE. These signal configurations can then be evaluated using a second neural network that is associated with the radio environment. The second neural network can be trained using measurements from previous physical transmissions in the radio environment. The trained second neural network generates a reward value that is associated with the candidate signal configurations. The first neural network is then trained using the reward values from the second neural network to produce improved candidate signal configurations. When a signal configuration that produces a suitable reward value is generated, this signal configuration can be used for the physical transmission in the radio environment.

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: Methods and apparatuses for feature-driven machine-to-machine communications are described. At a feature encoder, features are extracted from sensed raw information, to generate features that compress the raw information by a compression ratio. The feature encoder implements a probabilistic encoder to generate the features, each feature providing information about a respective probability distribution that each represents one or more aspects of the subject. The probabilistic encoder is designed to provide a compression ratio that satisfies a predetermined physical channel capacity limit for a transmission channel. The features are transmitted over the transmission channel.

Abstract: A transmitter and receiver are provided for communication over a noisy channel in a wireless communications system. The transmitter and receiver use polar coding to provide reliability of data transmission over the noisy wireless channel. In addition, signature bits are inserted in some unreliable bit positions of the polar code. For a given codeword, the receiver with knowledge of the signature can more effectively decode the codeword. Cyclic redundancy check (CRC) bits may also included in the input vector to assist in decoding.

Abstract: Methods and systems are described which use a sensing system in cooperation with a wireless communication system. Coordinate information (which may be from the sensing system, from an electronic device, or from a network-side device) and signal-related information (which may be from the wireless system) are associated with each other. The associated information may be used for wireless communication management, such as beam management operations, among others.

Abstract: Coding sub-channel selection involves, in an embodiment, determining, from sub-channels that are defined by a code and that have associated reliabilities for input bits at input bit positions, a first number of the sub-channels to carry bits that are to be encoded. A second number of the sub-channels, greater than the first number, are selected. The second number of sub-channels are selected to provide exactly the first number sub-channels to be available to carry the bits that are to be encoded.

Abstract: A transmitter and receiver are provided for communication over a noisy channel in a wireless communications system. The transmitter and receiver use polar coding to provide reliability of data transmission over the noisy wireless channel. In addition, signature bits are inserted in some unreliable bit positions of the polar code. For a given codeword, the receiver with knowledge of the signature can more effectively decode the codeword. Cyclic redundancy check (CRC) bits may also included in the input vector to assist in decoding.

Abstract: Methods, apparatuses, and systems for implementing error-correction in communication systems, particularly wireless communication systems, are provided. A Polar code-based encoding method combines first and second pluralities of information bits and error-correcting code bits, and a plurality of frozen bits, into an input vector. The input vector is encoded according to a Polar code to produce a first codeword, which improves the probability of successfully transmitting and receiving the codeword over a physical channel in the communication system.

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: Systems and methods are disclosed for performing rate matching when using general polar codes. In one embodiment, a method of generating a codeword includes receiving bits at a polar encoder and encoding the bits using polar encoder kernels. The polar encoder kernels include a first kernel and a second kernel. The first kernel receives a set of input q-ary symbols and modifies the set of input q-ary symbols according to a first kernel generator matrix to produce a set of output q-ary symbols. The second kernel receives a set of input l-ary symbols, where l does not equal q, and modifies the set of input l-ary symbols according to a second kernel generator matrix to produce a set of output l-ary symbols. For example, the first kernel may be a binary kernel and the second kernel may be a Reed-Solomon (RS) based kernel.

Abstract: A signature-enabled Polar code encoder and decoder are provided. Signature bits are inserted in some unreliable bit positions. Different signature bits are inserted for different receivers. For a given codeword, only the receiver with knowledge of the signature can decode the codeword. Cyclic redundancy check (CRC) bits may be included in the input vector to assist in decoding.

Abstract: Systems and methods are disclosed that relate to performing rate matching when using polar codes. In one embodiment, a plurality of bits are received at a polar encoder. A value is obtained that corresponds to at least one of: a coding rate to be used to transmit the plurality of bits, and a number of coded bits to be used to transmit the plurality of bits. It is determined which range of values the value falls within, and an information sequence is obtained that corresponds to the range the value falls within. The plurality of bits are mapped to a subset of positions of an input vector according to the information sequence. The remaining positions of the input vector are set as frozen values that are known by a decoder. The input vector is then encoded in the polar encoder to generate a codeword.

Abstract: A first error-detecting code (EDC) is computed based on a first segment of a block of information that is to be encoded, and a second EDC is computed based on at least a second segment of the block of information. The first EDC is masked with a first masking segment and the second EDC with a second masking segment to generate a first masked EDC and a second masked EDC. The first masking segment and the second masking segment are associated with a target receiver of the block of information. A codeword is generated based on a code and an input vector that includes the first segment, the first masked EDC, the second segment, and the second masked EDC. This type of coding could be useful to support early termination of blind detection at a decoder, for example.

Abstract: Systems and methods for Polar encoding with a blockwise checksum are provided. The method involves processing a set of K information blocks to produce a blockwise checksum with u blocks, where K>=2, and u>=1, and where each information block or checksum block contains P bits. The blockwise checksum may, for example, be a Fletcher checksum. The Polar code may be based on an m-fold Kronecker product matrix. Then, an N-bit input vector is produced with P×K information bits and the P×u blockwise checksum bits, and with N?PK?Pu frozen bits, where N=2m where m>=2. The N-bit input vector is processed to produce a result equivalent to multiplying the input vector by a Polar code generator matrix to produce a codeword. The codeword is then transmitted or stored.