14 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 invention discloses a depth receiver construction method, an application system, a receiver, equipment and a medium, and the construction method comprises the steps: constructing an MU-MIMO OFDM uplink transmission system, so as to obtain an original training data set; a depth receiver is constructed, and the depth receiver is based on a multi-head self-attention mechanism; and performing multi-time iterative model training and convergence on the depth receiver by using the original training data set. A reliable training data set is obtained by designing a standard-meeting MU-MIMO OFDM uplink transmission system, and model training is carried out by constructing a depth receiver based on a multi-head self-attention mechanism, so that accurate decoding of data streams in a non-orthogonal superposition pilot frequency transmission scheme is effectively realized; therefore, there is no need to design a plurality of independent modules and solve the problem of cooperative work among the modules, and the bit error rate performance is superior to that of a traditional receiver scheme.

In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The method is a method for wireless communication of a wireless device. The wireless device generates a time-domain cyclic shift code set for a transmit antenna set. Each time-domain cyclic shift code in the set corresponds to one shift in a Doppler frequency domain. The wireless device applies the time-domain cyclic shift code set to transmit signals from the transmit antenna set to simultaneously: perform Doppler division multiplexing for transmit antenna port diversity and execute beam sweeping for beam management. The wireless device transmits the signals using the transmit antenna set.

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 present invention discloses a design method for ReIMV - OMP channel estimation based on MIMO OFDM systems. This method proves that a new matrix can be constructed by taking one frame from the IMV model, which contains the effective information for recovering the non - zero positions. After reducing the dimension to the MMV model and further combining with a random Gaussian vector to reduce the dimension to the SMV model, the non - zero positions can be recovered from the simplified SMV model. The simulation results verify the effectiveness of this algorithm, which not only helps to improve the estimation accuracy of the non - zero positions of the channel, but also has better MSE and BER performance than the BOOMP algorithm that also utilizes the common sparsity of MIMO channels.

The invention relates to the technical field of target state detection, and discloses a multi-moving target state anti-interference detection method based on an MIMO OFDM communication system, which comprises the following steps: a base station based on the MIMO OFDM communication system transmits a downlink OFDM detection signal, and if the signal is reflected by a moving target and an interference source, receiving data is obtained; estimating the angles of the moving target and the interference source; designing a receiving beam based on the estimated moving target angle and interference source angle through a beam former, enabling the receiving beam to be aligned with a target signal direction, introducing an interference receiving gain upper bound as a constraint, and obtaining a receiving signal only containing all target information; and demodulated receiving signals are processed by using a target state joint solving method based on subspace decomposition and rotation invariance, and joint estimation of the speed and the distance of each moving target is completed respectively. According to the method, the problem of insufficient precision of joint detection in a multi-dimensional domain in the prior art is solved, and the method has the characteristics of low complexity and high precision.

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.

Methods, apparatuses, and storage media are for phase noise resilient hybrid beamforming comprising using a deep neural network (DNN) for pre distortion of a signal for communication including mmWave and MIMO orthogonal frequency division multiplexing (MIMO OFDM) transmission, where symbol indices of each frame of the signal treated as exogenous variables of the DNN.

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.

A method realized by a MIMO OFDM transmitter (100) of a base station for transmitting data to at least a first user equipment (21) having MIMO OFDM receiver (200) using a first service type having a first numerology (M) and to a second user equipment (22) having MIMO OFDM receiver (200) using a second service type having a second numerology (N), where said first numerology (M) and said second numerology (N) are different than each other, characterized by comprising following steps: receiving at least a first input signal having n number of OFDM symbols to be transmitted to the first user equipment (21); applying n number of inverse fast Fourier transform (IFFT) to the first input signal, adding a first virtual cyclic prefix (411) to each OFDM sample and generating first OFDM symbols (410) for the first service; applying a first fast Fourier transform (FFT) having larger FFT size than n and m to first OFDM symbols; receiving (410) at least a second input signal having m number OFDM samples to be transmitted to the second user equipment (22); applying m number of inverse fast Fourier transform (IFFT) to the second input signal, adding a second virtual cyclic prefix (421) to each OFDM sample and generating second OFDM symbols (420) for the second service; where first cyclic prefix and second cyclic prefix are different than each other; and first cyclic prefix and second cyclic prefix are lower in size than the largest cyclic prefix in a predetermined numerology table; applying the first fast Fourier transform (FFT) to second OFDM symbols (420); multiplexing (420) first OFDM symbols (410) and second OFDM symbols (420) depending on number of transmitting antennas (190); applying Inverse Fast Fourier Transform (IFFT) to multiplexed first OFDM symbols (410), second OFDM symbols (420), adding an encapsulating prefix (310) and generating encapsulating OFDM symbols (300) for each transmitting antenna; transmitting encapsulating OFDM symbols (300) symbols through transmitting antennas (190).

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.