An Iterative Equalization Method Based on Survivor-by-Survivor Path Processing in Direct Sequence Spread Spectrum Communication

Abstract

The invention relates to an iterative equalization method based on survivor-by-survival path processing in direct sequence spread spectrum communication, which is a joint equalization and decoding method suitable for fast time-varying channel conditions. The method can effectively track time-varying channels without insert additional training data. Compared with the traditional direct sequence spread spectrum communication signal processing method, this method can flexibly adjust the spreading ratio, and can adaptively track channel changes without additional training data overhead. The method is as follows: in the receiver, the direct sequence spread spectrum symbol is used as the processing unit, and the "surviving path channel estimation method" is adopted in the iterative equalization detector, and the channel is adaptively updated according to the size of the "channel estimation matching index" Estimation; the detector adopts the detection algorithm of soft-in and soft-out, and the subsequent decoder adopts the iterative decoding algorithm of soft-in and soft-out, and the soft information is exchanged between the detector and the decoder, and iteratively approaches the optimal solution.

Description

technical field [0001] The invention relates to a joint equalization and decoding method applied to a wireless communication system under fast time-varying channel conditions, and belongs to the technical field of equalization in mobile communication. Background technique [0002] In order to adapt to the future development, the mobile communication system must be able to support high-speed data transmission. As the rate increases, the frequency-selective fading of the channel will significantly affect the performance of the communication system. The usual method is to use equalization technology or spread spectrum technology to counteract the frequency selective fading of the channel. The iterative equalization technology combines equalization and decoding. Using a method similar to Turbo iterative processing can well approach the optimal receiver for joint equalization and decoding, greatly improving the performance of the receiver, that is, maintaining the same frequency...

AI Technical Summary

Problems solved by technology

[0003] However, in the current signal processing method combining direct sequence spread spectrum technology and iterative equalization technology, the detection algorithm of its iterative equalization algorithm, such as the linear MMSE algorithm or MAP algorithm using soft-in soft-out (SISO), needs to be assumed to be The channel is time invariant and the channel response is known

In order to meet the above assumptions, two methods are usually used: one is to continuously update the channel estimate by inserting training pilot data into the data stream, but this will reduce the channel utilization; the other is to use a decision-oriented channel estimation method, that is, using Channel estimation is performed on data judgment results, and the decision-oriented algorithm has unreliable judgment in the direct sequence spread spectrum communication system, which leads to error propagation, which seriously restricts the improvement of system performance

Images