Southeast University

Wen Zhong

Xiqi Gao

Wenjin Wang

Anan Lu

Bin Jiang

Chen Sun

Li You

Shi Jin

Dongming Wang

Xin Meng

Teer Ba

Ting Li

Meili Zhou

Long Qin

A massive multiple-input multiple-output (MIMO) robust precoding transmission method under imperfect channel state information (CSI), wherein the imperfect CSI obtained by the base station (BS) side of the massive MIMO system is modeled as an a posteriori statistical channel model including channel mean and channel variance information. The model considers the effects of channel estimation error, channel aging and spatial correlation. The BS performs the robust precoding transmission by using the a posteriori statistical channel model, so that the universality problem of the massive MIMO to various typical moving scenarios can be solved, and high spectral efficiency is achieved.

Massive MIMO robust precoding transmission method

The invention discloses a beam domain optical wireless communication method and system. A base station is equipped with an array of optical transceiver ports or transmitter/receiver ports and a lens, each optical transceiver port forms a beam with centralized energy through the lens, and the base station generates beams in different directions by using the optical transceiver port array and the lens, thereby realizing multi-beam coverage or large-scale beam coverage in a communication region. The base station transmits/receives signals of multiple or a large number of user terminals by using channel state information of each user terminal, and different optical transceiver ports transmit/receive signals in different directions, thereby realizing simultaneous communication and bidirectional communication between the base station and different user terminals.

Beam domain optical wireless communication method and system

Described herein is an omni-directional transmission scheme allowing signals to transmit from a base station to multiple users in massive MIMO systems with reduced pilot overhead and system complexity. The transmission scheme uses a low-dimensional space-time coding scheme to generate a K-dimensional vector signal, and based on the K-dimensional vector signal, using an omni-directional precoding matrix W to generate an M-dimensional vector signal for transmission over a large number of transmitting antennas, wherein the matrix W comprises M rows and K columns, and K is much smaller than M.

Omni-directional transmission in large-scale MIMO systems

A wireless communication method utilizes a large-scale antenna array, which is deployed at the base station and can be a one-dimensional or two-dimensional array and can form tens of beams over the area covered by the base station. The communications method utilizes beam domain division of spatial resources at the base station side utilizing an analog multi-beam forming network or a digital domain multi-beam forming method. The base station carries out wireless communication with multiple users with the same time frequency resource and with the communications process implemented in the beam domain. Scheduling is accomplished through the utilization of a deterministic unitary matrix to form beams. The unitary matrix is a correlation matrix of interference that includes a channel characteristics mode energy coupling matrix, the beam allocation providing beam sets of different users that are non-overlapping to distinguish users in the beam domain.

Wireless communication method utilizing a large-scale antenna array

A multi-antenna channel estimation method based on polyphase decomposition includes: receiving frequency domain received signals transformed using discrete fourier transformation (DFT) in pilot symbols; performing phase correction on the frequency domain received signals; performing polyphase decomposition on the frequency domain received signals which are corrected using phase correction and acquiring polyphase signals; performing interpolation on the polyphase signals and acquiring the estimation values of the multi-antenna channel parameters with various linear combinations on each frequency; acquiring decorrelation array based on the pilot structure of the transmission antenna and decorrelating the estimation values of the multi-antenna channel parameters with various linear combination on each frequency using the decorrelation array and acquiring channel parameters of the pilot symbols on each frequency; acquiring channel parameters of data symbols based on the channel parameters of the pilot symbols. With the present invention, the inversion problem in multi-antenna channel estimation is avoided with lower complexity, and results of the multi-antenna channel estimation method become more accurate since the DFT and filtering are performed in the interpolation after polyphase decomposition.

Multi-antenna channel estimation method based on polyphase decomposition

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