8 results about "MIMO-OFDM" patented technology

The invention discloses a pilot optimization method for large-scale MIMO channel estimation based on structural compressed sensing. The method comprises the steps of establishing a channel estimation model for a large-scale MIMO-OFDM (Multiple-Input-Multiple-Output-Orthogonal Frequency Division Multiplexing) system when pilots are placed in an overlapping mode; simplifying the channel estimation model for the large-scale MIMO-OFDM system, thereby enabling the channel estimation model to correspond to a structural compressed sensing model; and obtaining an optimum pilot matrix through utilization of a pilot optimization algorithm. Through adoption of the optimum pilot matrix, according to the channel estimation of the large-scale MIMO system based on structural compressed sensing, the mean square errors MSEs of the channel estimation are clearly reduced, and the channel estimation performance is improved.

The application discloses a lightweight deep receiver construction method and system, a receiver, equipment and a medium, wherein the construction method comprises the following steps: constructing a MU-MIMO OFDM uplink transmission system based on non-orthogonal superimposed pilot transmission to obtain an original training data set; constructing a lightweight deep receiver, wherein the lightweight deep receiver is based on time domain shift and frequency domain shift operations; and performing multiple iteration model training and convergence on the lightweight deep receiver by using the original training data set. By designing an uplink transmission system based on non-orthogonal superimposed pilot transmission to enhance the frequency spectrum usage rate, and then constructing a lightweight deep receiver based on time domain shift and frequency domain shift to perform model training, since the pilot structure is stable and the data symbols are random, the shift operation effectively enhances the separability of the two, so that the lightweight deep receiver can realize the decoupling of data and pilot in the non-orthogonal superimposed pilot scene, and the decoding accuracy of the data stream is significantly improved.

Systems and methods are disclosed herein for a Convex Reduction of Amplitude (CRAM) based processing scheme for a Multiple Input Multiple Output (MIMO) Orthogonal Division Multiplexing (OFDM) transmitter system. In one embodiment, a method performed by a processing system for a MIMO OFDM transmitter system comprises precoding frequency-domain input signals to provide frequency-domain precoded signals for multiple subcarriers. The method further comprises processing the frequency-domain precoded signals in accordance with a CRAM-based processing scheme to provide time-domain precoded signals for respective transmit branches of the MIMO OFDM transmitter system. The CRAM-based processing scheme uses projection matrices for the subcarriers, respectively, to project clipping energy into a null space of the MIMO OFDM transmitter system. Further, the projection matrices are a function of static or semi-static information that defines the null space of the MIMO OFDM transmitter system.

The invention discloses a lightweight depth receiver construction method and system, a receiver, equipment and a medium, and the construction method comprises the steps: constructing an MU-MIMO OFDM uplink transmission system based on non-orthogonal superposition pilot frequency transmission, so as to obtain an original training data set; a lightweight depth receiver is constructed, and the lightweight depth receiver operates based on time domain shifting and frequency domain shifting; and carrying out multiple iteration model training and convergence on the lightweight depth receiver by using the original training data set. An uplink transmission system based on non-orthogonal superposition pilot frequency transmission is designed to enhance the spectrum utilization rate, then a lightweight depth receiver based on time domain shift and frequency domain shift is constructed to carry out model training, and since the pilot frequency structure is stable and data symbols have randomness, the shift operation effectively enhances the separability of the pilot frequency structure and the data symbols, and the accuracy of the model training is improved. The lightweight depth receiver can realize decoupling of data and pilot frequency in a non-orthogonal superposition pilot frequency scene, and the decoding accuracy of a data stream is remarkably improved.

The application discloses a millimeter wave LOS-MIMO OFDM phase noise estimation compensation method and system, which places a local pilot sequence in a corresponding position of an information sequence after coding and modulation, obtains a received signal r through frequency down-conversion and filtering sampling, extracts a received pilot sequence r from the received signal r through a demultiplexing module at a receiving end, divides a continuous part r p and a discrete part r p,1 in the received pilot, p,2 calculates an autocorrelation matrix of r p,1 and a cross-correlation vector of r p,1 and s p,1 , then performs minimum mean square error estimation on a phase noise spectrum Φ to obtain an estimated value, obtains a time domain part phase noise after IFFT, and then utilizes the discrete pilot to estimate a residual phase angle, so that the estimation and compensation of the phase noise are completed. The application is convenient for subsequent software processing, and can realize the suppression of the millimeter wave OFDM system phase noise under a lower implementation complexity through design according to the minimum mean square error criterion.

The channel tracking control method includes the following operations: during a preamble code period of a packet, determining a noise power according to a preamble code of the packet, the preamble code being transmitted via a plurality of subcarriers; determining a truncation standard value corresponding to a subcarrier in the plurality of subcarriers according to a noise attenuation factor of a channel detection circuit; determining a signal-to-noise ratio of the subcarrier according to the truncation standard value and the noise power; and controlling a channel tracking circuit to stop tracking the channel response of the subcarrier within the payload period of the packet according to the signal-to-noise ratio and a target signal-to-noise ratio.