Optimization method for iterative equalization of wireless wideband communication channel

Abstract

The invention discloses an optimization method for iterative equalization of a wireless wideband communication channel. The method comprises the following steps of setting a pilot training sequence and a received pilot training sequence, carrying out initial channel estimation and respectively carrying out fast Fourier transform on an initial channel estimation value and the pilot training sequence obtained at a receiving end in order to obtain a frequency domain estimation value and a frequency domain response respectively; utilizing a zero-forcing algorithm to obtain an equalization pilot training sequence X'(N+i) after ith iteration and then computing to obtain a signal-to-noise ratio SNRi after ith iteration; utilizing an MMSE (Minimum Mean Square Error) algorithm to obtain an equalization filter coefficient W(N+i) after ith iteration and then computing to obtain an error function E(N+i) after ith iteration, and obtaining an equalization filter updating coefficient W'(N+i) after ith iteration accordingly; and utilizing the equalization filter updating coefficient W'(N+i) after ith iteration to replace the equalization filter coefficient W(N+i), repeating the process until an error function value meets design requirements, stopping iteration, and computing to obtain the equalization filter updating coefficient W'(N+i) after ith iteration as an optimal equalization filter coefficient.

Description

technical field [0001] The invention belongs to the technical field of wireless broadband communication, and in particular relates to an optimization method for iterative equalization of a wireless broadband communication channel. Background technique [0002] In recent years, with the rapid growth of wireless multimedia services and Internet services, wireless communication technology has been rapidly developed and widely used. High requirements, which in turn require wireless communication equipment to support high mobility and transmission quality, as well as provide high spectrum utilization and user data rates. Wireless communication technology has experienced the evolution from narrow band to broadband, from low speed to high speed, resulting in wireless broadband mobile communication system. However, in the mobile application environment, the transmission of broadband data in the wireless broadband mobile communication system is very sensitive to the time variation o...

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Problems solved by technology

[0005] In engineering implementation, equalization usually adopts Zero-Forcing (ZF) algorithm and minimum mean square error (Minimum Mean Square-Error, MMSE) algorithm; ZF algorithm is simple and easy to implement, but in frequency selective channels, especially when the When the frequency selective channel distortion is serious, its noise will be strengthened, which will reduce the performance of the receiving threshold; the MMSE algorithm is better than the ZF algorithm when the channel has a deep frequency fading pole, but there will be residual intersymbol interference

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