The present invention relates to method of transmitting and receiving signals and a corresponding apparatus. One aspect of the present invention relates to a method of receiving a signal, which includes an L1 signaling region where the L1 signaling has an adaptive L1 block structure for increased spectrum efficiency in a channel bonding environment.

The present invention relates to method of transmitting and receiving signals and a corresponding apparatus. One aspect of the present invention relates to a method of receiving a signal, which includes an L1 signaling region where the L1 signaling has an adaptive L1 block structure for increased spectrum efficiency in a channel bonding environment.

A transmitting apparatus is disclosed. The transmitting apparatus includes an encoder to perform channel encoding with respect to bits and generate a codeword, an interleaver to interleave the codeword, and a modulator to map the interleaved codeword onto a non-uniform constellation according to a modulation scheme, and the constellation may include constellation points defined based on various tables according to the modulation scheme.

A coding and modulation apparatus and method are presented. The apparatus comprises an encoder that encodes input data into cell words, and a modulator that modulates said cell words into constellation values of a non-uniform constellation. The modulator is configured to use, based on the total number M of constellation points of the constellation and the code rate, a non-uniform constellation from one or several groupsof constellations each comprising one or more constellations.

Probabilistic constellation shaping (PCS) is applied to a desired probability distribution over the 2-D constellation points. Constellation points are partitioned into multiple disjoint sets in which all the constellation points within a subset have the same energy level (i.e., amplitude) or distance from the origin on the complex plane. Each of the sets may be further subdivided into smaller disjoint sets of constellation points to facilitate labeling of the constellation points. The sets may be indexed from 0 to the total number of disjoint sets to form an index set. The desired distribution may then be applied over the index set either using a distribution matcher (DM) or using a lookup table. The desired distribution may be generated before forward error correction (FEC) encoding that preserves the generated amplitude distribution through FEC encoding of data bits. The scheme may map the FEC encoded data bits to the constellation points, such that the probability of occurrence of each signal set (with a specific energy level) follows the desired probability distribution within a fixed codeword length. In addition, PCS can be applied to both square and non-square constellations, which may or may not be arranged on a Cartesian grid.

A method pertaining to optimization of resource unit (RU) and segment parser design for aggregated and multi-RU operations in extreme high-throughput (EHT) systems involves coding data for a station (STA) to provide a stream of coded bits. The method also involves processing the stream of coded bits to provide processed bits, including parsing the stream of coded bits to a combination of multiple RUs assigned to the STA in a proportional round-robin fashion. The method further involves transmitting the processed bits to the STA over the combination of multiple RUs.

A signal processing device includes: a memory; and a processor coupled to the memory and configured to: perform soft decision of a value of, among bit strings, a predetermined bit string encoded with a soft decision code from a symbol assigned to, according to each value of the bit strings, the bit strings having been subject to encoding of an outer code with a turbo product code and encoding of an inner code with the soft decision code; decode the predetermined bit string with the soft decision code on a basis of a result of the soft decision; individually perform, from the symbol, the soft decision of a value of each bit string other than the predetermined bit string among the bit strings; and decode the bit strings with the turbo product code on a basis of a result of the decoding and a result of the soft decision.

The present disclosure discloses an adaptive MIMO detection method and system. The method includes the following steps: a) determining whether a Signal to Noise Ratio of a data packet is greater than a set threshold for Signal to Noise Ratio, and if yes, performing ZF preprocessing on the channel matrix, and if not, performing MMSE preprocessing on the channel matrix; b) performing sorted QR decomposition on the channel matrix processed in step a) to obtain a plurality of decomposition matrices; c) determining whether a condition number of the channel matrix of the data packet is greater than a set threshold for condition number of the channel, and if yes, Lattice Reduction is performed on the decomposition matrices obtained in step b); d) determining whether an estimated value of an interference term of the channel matrix is greater than a threshold for the estimated value of the interference term of the channel matrix, and if yes, SIC detection mode is selected for MIMO detection on the data packets, and if not, K-best detection mode is selected for MIMO detection on the data packets; and e) according to processing results from steps a) to d), performing MIMO detection on the data packet.

A method for monitoring an unmanned aerial vehicle (UAV) includes a processor obtaining a datagram based on monitoring data for a UAV-detector communication between the UAV and one or more detectors. The monitoring data indicates at least one of a location of the UAV or a location of a control station in communication with the UAV. The method further includes determining a risk level by retrieving pre-stored risk information associated with the UAV based on the datagram.

A method for monitoring an unmanned aerial vehicle (UAV) includes a processor obtaining a datagram based on monitoring data for a UAV-detector communication between the UAV and one or more detectors. The monitoring data indicates at least one of a location of the UAV or a location of a control station in communication with the UAV. The method further includes determining a risk level by retrieving pre-stored risk information associated with the UAV based on the datagram.