A scheduling-free multi-user detection method

A multi-user detection and variance technology, applied in transmission monitoring, machine-to-machine/machine-type communication services, digital transmission systems, etc. The effect of improving modeling accuracy

Active Publication Date: 2020-12-29
XI AN JIAOTONG UNIV
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  • Abstract
  • Description
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Problems solved by technology

[0006] In order to overcome the problem of channel estimation error in the multi-user detection in the NOMA system, the purpose of the present invention is to provide a scheduling-free multi-user detection method. First, the channel noise v=[v 1 ,v 2 ...,v N ] T Carry out mixed Gaussian modeling, and then use the sparse Bayesian learning algorithm to eliminate the channel estimation error by iterating the channel H and the transmitted signal α

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  • A scheduling-free multi-user detection method
  • A scheduling-free multi-user detection method
  • A scheduling-free multi-user detection method

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Embodiment Construction

[0045] The present invention will be further described below in conjunction with the accompanying drawings, including embodiments of the present invention. The described embodiments are only for explaining the present invention and do not represent all embodiments.

[0046] The embodiment of the present invention considers a typical NOMA uplink, including a base station, K users, and N transmission subcarriers (Nk After spreading sequence s k It is modulated to N subcarriers for transmission, and all active user signals are superimposed on the subcarriers. The received signal at the base station terminal carrier n can be expressed as:

[0047]

[0048] Among them, g nk Indicates the channel gain of user k on subcarrier n; s nk Indicates the spreading sequence s k The nth component of ; α k Indicates the sending signal of the kth user; v n Indicates the noise on subcarrier n.

[0049] Combine all received signals and express in matrix form as:

[0...

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Abstract

The invention relates to a scheduling-free multi-user detection method, which comprises the following steps of A, clustering N components of a received signal y = [y1, y2,... yN] T into L classes by utilizing a hybrid Gaussian clustering algorithm, establishing a noise hybrid Gaussian model, and obtaining a final L value; step B, constructing a layered Bayesian prior model, deducing a weight wl, aGaussian component variance channel H and an updating formula of a transmitting signal alpha in the noise mixing Gaussian model, and performing multiple iterations to obtain a transmitting signal estimation value which is a multi-user detection result. According to the invention, a sparse Bayesian learning algorithm is used to iteratively calculate the channel estimation and emission signal estimation values, the channel estimation errors are eliminated, and the multi-user detection performance is improved.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a scheduling-free multi-user detection method. Background technique [0002] With the development of wireless communication technology, the existing fourth-generation mobile communication system obviously cannot meet the requirements of large capacity, low delay and high speed in the future. In the 5G era, the communications industry hopes to realize the ideal of "Internet of Everything". The communication system will no longer be based on communication between people, but a large number of machines and equipment will be connected to the communication network. Existing spectrum resources are already in short supply, and it is necessary to consider accommodating more users on the same spectrum resource, that is, to increase spectrum utilization. [0003] Traditional multiple access technologies are all about orthogonal multiplexing of resources, limited by time-fr...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B17/391H04L25/02H04W4/70
CPCH04L25/024H04L25/0256H04B17/391H04W4/70
Inventor 李锋彭伊婷陈伟
Owner XI AN JIAOTONG UNIV
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