Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication is provided which allows high accuracy estimation of frequency offset, high accuracy estimation of a transmission path fluctuation and high accuracy synchronization/signal detection. Pilot symbol mapping is provided for forming pilot carriers by assigning orthogonal sequences to corresponding subcarriers among OFDM signals which are transmitted at the same time from respective antennas in the time domain. Even when pilot symbols are multiplexed among a plurality of channels (antennas), this allows frequency offset/phase noise to be estimated with high accuracy.

A processor-implemented method includes receiving a signal representing a first encoded data and calculating an estimated timing offset and/or an estimated frequency offset associated with the signal. A correction of at least one of a timing offset or a frequency offset of the signal is performed based on the estimated timing offset and/or the estimated frequency offset, to produce a modified signal. An effective channel is subsequently detected based on the signal or the modified signal. A second encoded data is generated based on the modified signal, a known vector, at least one left singular vector of the effective channel, and at least one right singular vector of the effective channel. A signal representing the second encoded data is transmitted to a communication device for identification of contents of a message at a different processor.

Methods, apparatus and systems for wireless sensing using multiple groups of wireless devices are described. In one example, a described system comprises: heterogeneous wireless devices in a venue, and a processor. A particular device is configured to communicate with a first device through a first wireless channel based on a first protocol using a first radio, and configured to communicate with a second device through a second wireless channel based on a second protocol using a second radio. The processor is configured for: obtaining a time series of channel information (TSCI) of the second wireless channel based on a wireless signal communicated between the particular device and the second device; computing a pairwise sensing analytics based on the TSCI; and computing a combined sensing analytics based on the pairwise sensing analytics. The particular device transmits the combined sensing analytics to the first device, to perform a wireless sensing task.

Aspects of the disclosure provide a receiver. The receiver includes a receiving (Rx) estimation controller configured to set a bit load of a subcarrier in a bit allocation table (BAT) at a transmitter, a receiving unit configured to receive, from the transmitter, a bit sequence that is loaded to the subcarrier based on the bit load of the subcarrier in the BAT wherein the bit sequence is transmitted through a channel from the transmitter to the receiving unit, and a channel estimator configured to estimate a condition of the channel based on the bit sequence that is loaded to the subcarrier.

The present disclosure relates to methods and devices for Channel State Information, (CSI) prediction. More particularly the disclosure pertains to predicting CSI for a dynamic channel that is varying over time, e.g. because the receiver is moving. This object is obtained by a method performed in a first wireless node of predicting CSI of a dynamic wireless channel H between the first wireless node and a second wireless node. The method comprises deriving channel covariance estimates C.sub.k(n), . . . , C.sub.k(n−M) of the dynamic wireless channel H, estimating one or more channel properties of the dynamic wireless channel H, wherein one of the estimated channel properties defines a spectrum spread of the dynamic wireless channel H, and determining a covariance prediction filter, based on the estimated one or more channel properties. The method further comprises predicting one or more channel covariance estimates Ĉ.sub.k(n+N|n) by applying the determined covariance prediction filter to the derived channel covariance estimates C.sub.k(n), . . . , C.sub.k(n−M) and calculating a predicted CSI using the predicted covariance estimates Ĉ.sub.k(n+N|n). Hence, this disclosure proposes predicting CSI by predicting channel covariance using a methodology which implies deriving optimal covariance prediction filters.

A method for adjusting an antenna configuration of the terminal device (30) in a cellular communication system (10). The system (10) includes a base station (20) and a terminal device (30) having a plurality of antenna elements (40-43). In the terminal device (30) a plurality of preset antenna configurations is provided. Each antenna configuration defines at least one reception parameter for the plurality of antenna elements (40-43). For each antenna configuration of the plurality of preset antenna configurations the antenna configuration is applied to the plurality of antenna elements (40-43) and a reception characteristic of a signal transmission from the base station (20) is determined. Based on the plurality of reception characteristics one antenna configuration is selected and applied to the plurality of antenna elements (40-43) for further signal transmissions.

Methods and apparatus for communication between terminals and an access node in a multiuser multicarrier communications network are described. The access node may be a satellite access node. Terminals are configured to perform initial estimation and tracking of channel offsets and to estimate channel offsets for future packets to be transmitted by the terminal. In some embodiments the channel offsets comprise mobility related channel offsets due to the relative movement between the access node and the plurality of terminals. Transmissions from the terminals to the access node are pre-compensated for the channel offsets, so that the aggregate signal received by the access node occupies a bandwidth greater or equal to the maximum signal bandwidth of any individual terminal. Terminal transmissions may overlap in frequency and time on the ground, but arrive orthogonally at the access node.

In wireless communications for a 20 megahertz (MHz) channel bandwidth, a first device may determine a high efficiency long training field (HE-LTF) mode. The first device may generate an HE-LTF symbol by using a portion or an entirety of an HE-LTF sequence corresponding to the channel bandwidth and HE-LTF mode. The first device may transmit, in the channel bandwidth, a high efficiency physical layer protocol data unit (HE PPDU) that includes the HE-LTF symbol. A second device may receive, in the 20 MHz channel bandwidth, a downlink HE PPDU that includes an HE-LTF symbol. The second device may obtain, from the HE-LTF symbol, a portion or an entirety of an HE-LTF sequence corresponding to the channel bandwidth and an HE-LTF mode of the HE-LTF symbol. The downlink HE PPDU may be the HE PPDU from the first device. Other methods, apparatus, and computer-readable media are also disclosed.

A method for transmitting and receiving signals, performed by a terminal, in a C-RAN environment, includes sequentially transmitting fixed beams; receiving, from at least one first TRP determined as TRP(s) performing signal transmission and reception with the terminal among the plurality of TRPs, control information including information on whether to transmit a reference signal for reception of downlink data and an index of a transmission beam selected for uplink transmission; and receiving the downlink data from the at least one first TRP, and demodulating the downlink data by using a reception beam weight derived from a weight used for transmission of the fixed beams or by using the reference signal.

A method may include generating an estimated time offset based on a reference signal in a communication system, and adjusting a transform window in the communication system based on the estimated time offset, wherein the estimated time offset is generated based on machine learning. Generating the estimated time offset may include applying the machine learning to one or more channel estimates. Generating the estimated time offset may include extracting one or more features from one or more channel estimates, and generating the estimated time offset based on the one or more features. Extracting the one or more features may include determining a correlation between a first channel and a second channel. The correlation may include a frequency domain correlation between the first channel and the second channel. Extracting the one or more features may include extracting a subset of a set of features of the one or more channel estimates.