A method for receiving data by a terminal in a wireless communication system according to the present document comprises: receiving a channel signal and a reference signal (RS) from a base station; and generating a sequence by filtering the RS, and decoding the channel signal on the basis of the generated sequence, wherein the filtering is zero forcing (ZF) filtering, and the decoding of the channel signal is a selection of one parameter from among parameter sets generated in accordance with a colored-noise machine learning process.

Apparatus and methods are disclosed for transmitting and receiving data in a wireless communication network. Apparatus for transmitting data in a wireless communication network comprises a real modulation branch for modulating a first segment of a bit sequence to obtain a real modulated signal, a complex modulation branch for modulating a second segment of the bit sequence to obtain a complex modulated signal, a signal dividing unit configured to divide the bit sequence into a plurality of alternating first segments and second segments, and to send the first segments and the second segments to the real modulation branch and the complex modulation branch respectively, and a transmitter configured to transmit the real and complex modulated signals. Apparatus and methods are also disclosed for demultiplexing a plurality of data streams, using wide linear zero forcing with successive interference cancellation.

A method and apparatus are provided, where a data sequence for transmission is identified (1002) as part of evaluating transmitter performance involving multiple physical antennas. The data sequence is mapped (1004) to the multiple physical antennas to be involved in the transmission. The data sequence is then transmitted (1006) using the multiple physical antennas from which a signal quality metric of a transmitter corresponding to a difference between a received signal associated with the transmission of each respective data symbol of the data sequence and a respective ideal location of a predefined constellation point associated with the data symbol that was transmitted can be determined, wherein an error vector magnitude involving an aggregated difference associated with the data sequence involving the transmission via the multiple physical antennas is determined.

Various embodiments of the present invention solve the problem of generating intermediate-time information useable to drive ZFE adaptation (for example, in connection with a digital receiver). Further, various embodiments of the present invention increase flexibility by enabling user-specified over-peaking and/or under-peaking (i.e. configurable equalizer tuning) with respect to a ZFE convergence (or lock) criterion.

This invention presents methods for signal detection and transmission in MU-MIMO wireless communication systems, for inverse matrix approximation error calculation, for adaptively selecting the number of multiplexed UEs in a MU-MIMO group, for adaptively choosing a modulation and channel coding scheme appropriate for the quality of MU-MIMO channels with the approximation error of matrix inverse being incorporated.

The present disclosure relates to a method and an apparatus for reducing or eliminating interferences between resource blocks in a transmitter and/or a receiver of a filter bank multicarrier system is provided. According to at least one embodiment, the method comprises performing discrete Fourier transform (DFT) on a data symbol vector to be transmitted thereby generating a DFT-spread data symbol vector, performing a cyclic shift operation on the DFT-spread data symbol vector to arrange a small magnitude element of the DFT-spread data symbol vector at an edge of a resource block allocated to the DFT-spread data symbol vector, and performing filter bank multicarrier (FBMC) modulation on a cyclically shifted DFT-spread data symbol vector.

Disclosed is a low-complexity linear equalization method for an Orthogonal Time Frequency Space (OTFS) system. The method may include: receiving a time domain signal passing through a linear time-varying (LTV) channel; sampling the time domain signal to obtain a sampled signal; demodulating the sampled signal to obtain a demodulated signal; performing a Symplectic Finite Fourier Transform (SFFT) on the demodulated signal to obtain a sampled delay-Doppler domain signal; determining an effective channel matrix in a delay-Doppler domain under a restriction of a rectangular window according to a time domain channel matrix; determining a linear equalization matrix according to the effective channel matrix; and equalizing the sampled delay-Doppler domain signal in a low-complexity way according to the linear equalization matrix. The disclosure also discloses a linear equalization device of an OTFS system for realizing the linear equalization method and a computer-readable storage medium.

What is disclosed is a method for wireless communication comprising receiving a wireless communication via a receiver of the mobile communication device, deriving a demodulation reference signal from a first plurality of symbols of the wireless communication; creating a channel estimation matrix using the demodulation reference signal; inverting the channel estimation matrix to obtain a channel pseudo-inverse matrix; deriving a tracking reference signal from a second plurality of symbols of the wireless communication; calculating a phase shift for one or more additional symbols based on the tracking reference signal; determining a corrected channel pseudo-inverse matrix for the one or more additional symbols by adjusting the channel pseudo-inverse matrix according to the calculated phase shift; and controlling the receiver to accomplish data detection using the corrected channel pseudo-inverse matrix on one or more orthogonal frequency division multiplexing subcarriers.

A detection method for a MIMO system receiver in which a linear detection is carried out in order to provide an equalised vector. This equalised vector is represented in a reduced basis obtained from the reduction of the channel matrix. It undergoes an iterative noise cancellation process in the representation according to the reduced basis. Upon each iteration, a search is carried out for the component of the equalised vector in the reduced basis located the furthest from an area unperturbed by noise surrounding the product constellation with a tolerance margin, and the point representative of the equalised vector of this area by subtracting therefrom a noise vector in the direction of this component, the module whereof is equal to a fraction of the tolerance margin. The iterative cancellation converges when the equalised vector belongs to the area unperturbed by noise.

A communication device includes a zero-forcing equalizer that receives a receipt signal and execute zero-forcing equalization on the receipt signal, a partial response equalizer that receives the receipt signal and execute partial response equalization on the receipt signal, a first weighted value calculator that calculates a first weighted value based on signal quality of the receipt signal output from the zero-forcing equalizer, a second weighted value calculator that calculates a second weighted value based on signal quality of the receipt signal output from the partial response equalizer, and an estimator that estimates a maximum likelihood sequence by supplying the first weighted value to state transition based on output by the zero-forcing equalizer and supplying the second weighted value to state transition based on output by the partial response equalizer.