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OFDM (Orthogonal Frequency Division Multiplexing) symbol timing and frequency offset estimation method based on particle swarm optimization (PSO) algorithm

A technology of particle swarm optimization and symbolic timing, applied in the direction of multi-frequency code system, etc., can solve problems such as time-consuming, large amount of calculation, complicated synchronization process, etc.

Inactive Publication Date: 2013-07-03
HOHAI UNIV CHANGZHOU
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Problems solved by technology

The entire synchronization process is complex, computationally intensive, and time-consuming

Method used

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  • OFDM (Orthogonal Frequency Division Multiplexing) symbol timing and frequency offset estimation method based on particle swarm optimization (PSO) algorithm
  • OFDM (Orthogonal Frequency Division Multiplexing) symbol timing and frequency offset estimation method based on particle swarm optimization (PSO) algorithm
  • OFDM (Orthogonal Frequency Division Multiplexing) symbol timing and frequency offset estimation method based on particle swarm optimization (PSO) algorithm

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Embodiment Construction

[0046] Below in conjunction with the accompanying drawings, specific embodiments of the present invention are given to further illustrate the present invention.

[0047] In the embodiment of the present invention, the figure 1 The shown OFDM transmission system contains timing and frequency synchronization modules, figure 1 In the process, the sender performs channel coding and digital modulation on the signal to be transmitted, inserts the pilot signal, and then performs serial / parallel conversion, divides the OFDM symbol into N parallel sub-signals, and passes the inverse fast Fourier transform (IFFT ) respectively modulates each sub-signal to N sub-carriers to realize multi-carrier modulation, and the signal is transformed from the frequency domain to the time domain. After parallel / serial conversion, a cyclic prefix (CP) is added to form a complete digital signal of OFDM symbols. After digital-to-analog conversion (DAC), it is modulated to the transmission frequency by up...

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Abstract

The invention discloses an OFDM (Orthogonal Frequency Division Multiplexing) symbol timing and frequency offset estimation method based on a particle swarm optimization (PSO) algorithm. The OFDM symbol timing and frequency offset estimation method comprises a scheme designing process and a scheme implementation process, wherein the scheme designing process comprises a step of establishing a corresponding relationship between an OFDM symbol timing and frequency offset combined estimation parameter and each parameter of an PSO algorithm; and the scheme implementation process comprises a step of finishing a task of searching an OFDM symbol timing and frequency offset combined optimal position. The OFDM symbol timing and frequency offset estimation method can be used for realizing the accurate estimation on symbol timing and frequency offset, effectively overcoming the influence of the integer frequency offset in a conventional OFDM symbol synchronization algorithm to symbol timing estimation and realizing the purpose of accurately estimating the OFDM symbol timing and the frequency offset. The computation complexity can be reduced and the OFDM symbol synchronization time is shortened on the precision of not reducing the performance; and the OFDM symbol timing and frequency offset estimation method is a simple and practical method for realizing the OFDM symbol timing and the frequency synchronization in a packet bursting wireless transmission system.

Description

technical field [0001] The invention relates to a method for jointly estimating OFDM symbol timing and frequency offset based on a PSO algorithm, and belongs to the technical field of wireless mobile communication. Background technique [0002] The particle swarm optimization (PSO) algorithm is an evolutionary (EA) computing technology developed in recent years based on swarm intelligence methods. It was first proposed by Eberhart and Kennedy in 1995, and its basic idea was inspired by the modeling method of bird group predation behavior and the results of simulation research. Similar to the genetic algorithm, it also starts from a random solution, finds the optimal solution of the problem through multiple iterations, and evaluates the quality of the solution through fitness. However, its rules are simpler than the genetic algorithm. There is no "mutation" and "crossover" operations of the genetic algorithm. It just uses the particles to follow the current optimal solution ...

Claims

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Application Information

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IPC IPC(8): H04L27/26
Inventor 康桂华康鸿博孟景波
Owner HOHAI UNIV CHANGZHOU
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