Turbo parallel decoding method and decoder

Abstract

The invention relates to a turbo parallel decoding method and a decoder. The method comprises the following steps:1. The decoder divides an input decoding sequence into w windows with the same length and adds bits in front and back of the windows in sequence; 2. The decoder starts the forward state metric calculation of the first iteration and stores the forward state metric of the original end position of the window to serve as the initial value of the forward state metric of next window in the second iteration; 3. The decoder starts the backward state metric calculation of the first iteration and stores the backward state metric of the original end position of the window to serve as the initial value of the backward state metric of the next window in the second iteration; and 4. The decoder removes the added bit section of each window and carries out subsequent iteration according to a parallel window arithmetic, the iteration is ended when the iteration time reaches the preset maximum iteration time.

Description

technical field [0001] The invention relates to the communication field, in particular to a turbo parallel decoding method and a decoder. Background technique [0002] Turbo codes, also known as parallel concatenated convolutional codes (PCCC), were proposed by C. Berrou et al. at the ICC'93 conference. It cleverly combines convolutional codes and random interleavers to achieve random coding. Decoding adopts soft input and soft output iterative decoding to approximate maximum likelihood decoding. Simulation results show that the decoding performance of turbo codes is close to the Shannon limit. The good error correction performance of the Turbo code makes it one of the error correction codes adopted by many communication protocols (WiMAX, LTE). [0003] LTE (Long Term Evolution, Long Term Evolution), as a new wireless access technology, uses Frequency Division Multiple Access (OFDM / FDMA) in the air interface to replace the long-term use of 3GPP Code Division Multiple Acce...

AI Technical Summary

Problems solved by technology

[0018] From the processing process of the parallel window algorithm described above, we can see that the initial values ​​of α and β cannot be obtained in the first iteration, so you need to set them yourself, and the inaccurate initial values ​​of α and β set by yourself will cause the first iteration The extrinsic information of one iteration is inaccurate, and the inaccurate extrinsic information generated by the first iteration is used as the prior information of the second iteration to affect the second iteration. This cumulative error will cause performance loss and correspondingly increase the iterations

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