Polar code decoder and polar code decoding method based on probability calculation

A technology of probability calculation and polar code, which is applied in the field of channel coding, can solve the problem of unoptimistic decoder throughput and achieve the effect of improving the overall throughput, good versatility, and good practical prospects

Active Publication Date: 2014-10-01
BEIJING UNIV OF POSTS & TELECOMM
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The disadvantage of the existing technology is that the iterative calculation of the bit likelihood ratio during the hardware implementation of the polar code decoding algorithm produces a huge delay, which leads to the unoptimistic throughput rate of the decoder

Method used

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  • Polar code decoder and polar code decoding method based on probability calculation
  • Polar code decoder and polar code decoding method based on probability calculation
  • Polar code decoder and polar code decoding method based on probability calculation

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Experimental program
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Effect test

Embodiment approach 1

[0041] Embodiment 1: bipolar probability calculation (BSC-SC) decoder, see Figure 9 , introducing the specific steps of the process:

[0042] Step 1, converting fixed-point numbers into probability sequences: After receiving the soft information output by the demodulator, these soft information need to be converted into probability sequences and sent to the decoder for iterative calculation. The probability sequence in this method is the simplest Bernoulli sequence, that is, a randomly generated 01 bit sequence. The code length of the polar code used is N, the set of information subchannels required by the polar code is A, and each soft information value is transformed into a probability sequence of length M. Wherein, N is the nth power of 2, n is a positive integer, and M is the length of the initial probability sequence set by the decoding system. Parameters A, N and M are preset. This step 1 specifically includes:

[0043] (11) Store the received soft information value...

Embodiment approach 2

[0053] Embodiment 2: low bit probability calculation (LBSC-SC) decoder, the basic purpose of each step in the method is the same as the corresponding steps in method 1, and the algorithm used in each step in the method is the essential difference between this method and method 1 . see Figure 11 , introducing the specific steps of the process:

[0054] Step 1: This step converts the values ​​received by the channel into a sequence of probabilities. The code length of the polar code used is N, the set of information channels required by the polar code is A, and each soft information value is transformed into a probability sequence of length M. Wherein, N is the nth power of 2, n is a positive integer, and M is the length of the initial probability sequence set by the decoding system. Parameters A, N and M are preset. Step 1 specifically includes:

[0055] (11) Store the received soft information value, and scale it according to the signal-to-noise ratio, so that all soft i...

Embodiment approach 3

[0066] Embodiment 3: multi-stage probability calculation decoder, see Figure 14 , taking a simple special case of a multi-stage probability calculation decoder (in the special case, the decoding algorithm is divided into two stages, but in fact it can be divided into more stages) as an example to introduce the specific steps of the method:

[0067] Step 1: This step converts the values ​​received by the channel into a sequence of probabilities. The code length of the polar code used is N, the set of information channels required by the polar code is A, and each soft information value is transformed into a probability sequence of length M. In the first n of the decoder 0 level, all soft information values ​​are represented by probability sequences of length M, and in the remaining (n-n 0 ) level, all soft information lengths are represented by probability sequences with a length of M / 2 to improve system throughput. where n is a positive integer, n 0 The value is N is the...

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Abstract

The invention provides a polar code decoder and a polar code decoding method based on probability calculation. The polar code decoder comprises a probability sequence transformation module, a successive interference cancellation decoding module and a decision device, wherein the probability sequence transformation module is used for transforming received channel information into a first probability sequence; the successive interference cancellation decoding module is used for performing iteration processing on the first probability sequence based on a decision result of the decision device so as to obtain a second probability sequence and transforming the second probability sequence into a soft information value; and the decision device is used for performing hard decision on the soft information value and returning the decision result to the decoding module. According to the polar code decoder and the polar code decoding method based on probability calculation, the idea of the probability calculation is applied to the design of the polar code decoder, so that the processing delay of the polar code decoder can be reduced, and the total throughput of the polar code decoder can be increased greatly; and meanwhile, the polar code decoder and the polar code decoding method are simple in operation and good in universality and have better practical prospect.

Description

technical field [0001] The invention belongs to the technical field of channel coding, in particular to a polar code decoder and a polar code decoding method based on probability calculation. Background technique [0002] Polar Codes (Polar Codes) is a constructive channel coding method proposed by E.Arikan in 2009 that has been strictly proven to achieve channel capacity. figure 1 is the basic structural block diagram of decoding using polar codes; figure 2 It is a schematic diagram of the basic structure of channel polarization. Before polar encoding, first of all N=2 n independent binary input channels (or repeatedly use the same channel N times successively, that is, N available time slots of a channel), and then use the basic unit of channel polarization to repeatedly polarize the binary input discrete channels. In the above formula, n is a natural number. The most basic channel polarization operation is to perform single-step polarization on two identical unpolari...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L1/00
Inventor 牛凯许郑磊
Owner BEIJING UNIV OF POSTS & TELECOMM
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