Channel estimation method and device based on compressed sensing theory

Abstract

The invention discloses a channel estimation method and device based on a compressed sensing theory. The method comprises the following steps of estimating channel responses at pilot positions according to received pilot signals, and obtaining an LS estimation result of a channel; constructing a channel correlation matrix according to the LS estimation result, and carrying out SVD decomposition onthe channel correlation matrix, thereby obtaining sets of eigenvalues and eigenvectors; estimating the channel multipath number through utilization of an MDL criterion according to the eigenvalues; solving a delay distribution parameter of the channel according to the eigenvectors and the channel multipath number; and computing a channel density measurement value G according to the delay distribution parameter obtained through estimation, and for a given density measurement threshold Gth, solving the channel. According to the method and the device, relatively precise time delay is provided through utilization of a classical subspace decomposition method; channel sensitivity represented by a classical OMP method is improved; according to a provided improvement method, resolution capabilityof the method for the channel time delay is improved theoretically; channel estimation accuracy is further improved; and system reliability is improved.

Description

technical field [0001] The invention belongs to the field of wireless communication, and in particular relates to a channel estimation method and device based on compressed sensing theory. Background technique [0002] At present, visible light communication technology has gradually become a research hotspot of various scientific researchers and communication companies due to its advantages in security, anti-interference, communication speed, etc. Visible light communication modulates the luminous intensity of the LED, usually by superimposing the AC modulation component containing the signal under a certain DC bias. Broad development prospects. [0003] At present, O-OFDM technology is the most widely used baseband modulation technology for visible light communication. In O-OFDM systems, channel estimation is a very important subject. At present, the sparse channel estimation technology based on compressed sensing has been more and more researched and applied. It takes a...

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Problems solved by technology

Under the theory of sparse compressed sensing, there are two commonly used sparse solution methods, one is convex optimization solution, the typical representative is the BP method, the reconstruction performance of this method is good, but the computational complexity is very high, which cannot meet the requirements of channel estimation. Real-time requirements; the other is the greedy method, which greatly reduces the amount of calculation compared to the convex optimization method; however, the OMP method, as a typical representative of the greedy method, has a certain degree of instability.

This instability causes the instability of the channel estimation performance, which shows a channel sensitivity in the simulation

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