Patent classifications
H04L25/024
TRANSMISSION RATE CONTROL BASED ON EMPIRICAL MI ESTIMATION
A first wireless device may generate a first pseudo-random data based on a seed known to a second wireless device, and may transmit a first training signal including first pseudo-random data to the second wireless device for a MI estimation at the second wireless device, the first pseudo-random data being modulated with a first modulation order. The second wireless device may estimate, based on the received first training signal and through the MI estimation, a reception quality associated with at least one modulation order lower than or equal to the first modulation order, and determine a second modulation order of the at least one modulation order lower than or equal to the first modulation order based on the MI estimation, the second modulation order being estimated to provide a reception quality greater than or equal to a reception quality threshold. The MI estimation may be periodic or aperiodic.
Methods, apparatus and systems for channel estimation and simultaneous beamforming training for multi-input multi-output (MIMO) communications
Methods, apparatuses, and systems to enable a channel estimation of more than one channel for Multi-Input Multi-Output (MIMO) communications in a wireless network is provided. The method includes determining a first set of complex numbers comprising first channel estimation signal associated with a first channel, determining a second set of complex numbers comprising second channel estimation signal associated with a second channel, and transmitting the first set of complex numbers and the second set of complex numbers via a physical layer (PHY) frame, wherein the second set of complex numbers are complex conjugates of the first set of complex numbers.
Received signal equalization of wireless transmissions
Example operations may include obtaining a first received signal of a first wireless transmission by a transmitting device of a wireless signal received at a receiving device. The operations may also include obtaining a second received signal of a second wireless transmission by the transmitting device that is a retransmission of the wireless signal also received at the receiving device. The operations may further include determining, based on the first received signal and the second received signal, an equalization of distortion of propagation of the wireless signal between the transmitting device and the receiving device. In addition, the operations may include generating an equalized signal based on the determined signal equalization, wherein the equalized signal is an estimate of the wireless signal as transmitted by the transmitting device.
Method for estimating the channel between a transceiver and a mobile communicating object
A channel estimation method. For at least one temporal difference observed between two sub-sequences of channel measurements, or channel estimations, consisting of complex vectors or scalars, the method includes: a first extrapolation on the basis of channel measurements or channel estimations of the sub-sequence preceding the temporal difference, going forward in time; a second extrapolation on the basis of channel measurements or channel estimations of the sub-sequence following the temporal difference, going backward in time; and calculation of a weighted average of the extrapolated estimations or measurements forward in time and of the extrapolated estimations or measurements backward in time, in order to obtain channel measurements or channel estimations regularly spaced apart in the temporal difference. The method is suitable for radio communications between a base station and a moving connected vehicle.
ANGULAR SPARSE CHANNEL RECOVERY USING HISTORY MEASUREMENTS
Compressive sensing (CS) channel recovery using history measurements. Both current and history measurements for AoAs estimation, and only use current measurement for coefficient estimation. The dominant angle of arrival (AoA) is estimated using history and current measurements. In Approach 1, the dominant AoA is invariant and the coefficients are uncorrelated. In Approach 2, the dominant AoA is invariant and the coefficients are fully correlated. The remaining AoAs are estimated. The coefficients corresponding to each estimated dominant AoA are estimated. And the channel is recovered.
METHODS, APPARATUS AND SYSTEMS FOR CHANNEL ESTIMATION AND SIMULTANEOUS BEAMFORMING TRAINING FOR MULTI-INPUT MULTI-OUTPUT (MIMO) COMMUNICATIONS
Methods, apparatuses, and systems to enable a channel estimation of more than one channel for Multi-Input Multi-Output (MIMO) communications in a wireless network is provided. The method includes determining a first set of complex numbers comprising first channel estimation signal associated with a first channel, determining a second set of complex numbers comprising second channel estimation signal associated with a second channel, and transmitting the first set of complex numbers and the second set of complex numbers via a physical layer (PHY) frame, wherein the second set of complex numbers are complex conjugates of the first set of complex numbers.
SYSTEMS AND METHODS FOR GENERATING SHARED KEYS, IDENTITY AUTHENTICATION AND DATA TRANSMISSION BASED ON SIMULTANEOUS TRANSMISSION ON WIRELESS MULTIPLE- ACCESS CHANNELS
Methods of half-duplex communication systems or full-duplex communication systems are provided. The half-duplex communication system includes n number user units-including a transmitting unit of transmitting units, wherein the transmitting unit including a channel estimation module, an identity update module and a modulation module; a receiving unit of receiving units including a demodulation module, a post-processing module and a reconciliation and verification module; a memory unit for storing prime identities, data to be transmitted and shared secret key; a control unit; an antenna connected to each of the transmitting units and each of the receiving units; and the methods are used for realizing a generation of shared secret keys, and an integrated identity verification and a data transmission using the half-duplex communication systems and the full-duplex communication systems.
Adaptive Cross-Layer Error Control Coding for Heterogeneous Application Environments
At a physical data-link in a network, a current status of a plurality of logical data-channels in the network is determined, using machine learning to infer the current status. A plurality of cross-layer error correction coding schemes for transmissions is adaptively adjusted, based on the determined current status, and based on an application transmitting data. Transmission of the data, and a plurality of information-exchange requirements, are supported, using the adaptively adjusted plurality of error correction coding schemes.
CHANNEL TRAINING ADAPTATION
A method may include detecting parameter(s) of communication between an AP and a STA. The method may include determining a training configuration for a channel estimation of the communication based on the parameter(s). The method may include transmitting a DL transmission or a trigger frame to the STA. The DL transmission may include a training block configured according to the training configuration. The trigger frame may include the training configuration and instructions for the STA to include a training block configured according to the training configuration in a UL transmission to the AP. The STA may be configured to determine the channel estimation of a channel of the communication using the training block of the DL transmission received at the STA. Alternatively, the method may also include determining the channel estimation of a channel of the communication using the training block of the UL transmission received at the AP.
System and Method for Configuring Channel State Information in a Communications System
A method for communicating in a wireless communications system includes generating a channel state information (CSI) process information element (IE) including a CSI process identifier, a non-zero padded CSI-reference signal (CSI-RS) identifier, an interference measurement resource (IMR) identifier, and channel quality indicator (CQI) report configuration information. The method also includes transmitting the CSI process IE.