Double filtering smooth decoding method and device suitable for OvXDM system and OvXDM system

Abstract

The invention discloses a double filtering smooth decoding method and device suitable for an OvXDM system and the OvXDM system. The importance weight of each particle in a particle set corresponding to the symbol is calculated through forward filtering and backward information filtering, and then screening is performed through combination of the particle importance weight of forward filtering andparticle importance weight of backward information filtering so as to output the final decoding sequence. Mutual information between the particles is fully utilized in the process to realize decodingof the OvXDM system so that the obtained decoding sequence is closer to the real value, the decoding complexity can be reduced in comparison with the conventional decoding method along with increasingof the number of times of overlapping and the decoding efficiency and the system performance can be enhanced.

Description

technical field [0001] The present application relates to the field of decoding, and in particular to a double-filter smoothing decoding method and device suitable for an OvXDM system and the OvXDM system. Background technique [0002] For the overlapping multiplexing system OvXDM system, in its traditional decoding, it is necessary to continuously visit the nodes in the trellis graph (Trellis), and set up two memories for each node, one for storing the relative best path to the node , a metric used to store the relative best path to the node. [0003] Let’s take the OvTDM system as an example. Since each node in the trellis diagram needs to be expanded during the decoding process, the number of nodes determines the complexity of decoding. For a system with an overlapping number of K and a modulation dimension of M ( M is an integer greater than or equal to 2), and the number of nodes in the stable state in the corresponding trellis graph is M K-1 , so the decoding complex...

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Problems solved by technology

Therefore, on the one hand, the larger the number of overlapping times K is better for the requirement of improving spectral efficiency; on the other hand, the smaller the number of times of overlapping K is better for the requirement of reducing decoding complexity. For example, when K is greater than 8, the decoding complexity increases sharply, and the existing decoding methods are difficult to meet the requirements of real-time decoding. Spectral efficiency, decoding complexity, and decoding efficiency form a pair of contradictory requirements.

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