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Difference value toplimit acquiring method, point fixing method and apparatus

A difference and upper limit technology, which is applied in the field of difference upper limit acquisition and fixed-point technology, and can solve problems such as inability to fix-point, inability to obtain the upper limit of cumulative metric difference, and unreliable fixed-point performance of LVA decoders.

Active Publication Date: 2008-12-10
SHANGHAI HUAWEI TECH CO LTD
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0006] The method in the prior art cannot obtain the upper limit of the difference value of the cumulative metric including the suboptimal path, and furthermore, it cannot fix the cumulative metric value of each optimal path of the LVA , making the fixed-point performance of the LVA decoder unreliable

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  • Difference value toplimit acquiring method, point fixing method and apparatus
  • Difference value toplimit acquiring method, point fixing method and apparatus
  • Difference value toplimit acquiring method, point fixing method and apparatus

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Embodiment 1

[0031] see figure 2 , the method for obtaining the upper limit of the difference provided by the embodiment of the present invention may include:

[0032] Step 201: Obtain the difference between the maximum value and the minimum value of the branch metric;

[0033] If a certain state forks when going back, the metric from the forked state to a certain state is the branch metric. lambda max is the difference between the minimum branch metric and the maximum branch metric of the radix-2 algorithm. For the decoding of fixed-point soft information, λ max has a definite value. Assuming that the coding rate is 1 / R, for N-bit quantized soft information input, λ max =R*(2 N -1)

[0034] Step 202: Determine the number of optimal paths and the constraint length of the convolutional encoder;

[0035] Wherein, the number L of optimal paths can be preset, and the size of the set value is related to the complexity of the LVA decoder. Because it is in the LVA algorithm, it must incl...

Embodiment 2

[0081] see image 3 , the fixed-point method provided by the embodiment of the present invention may include:

[0082] Step 301: Obtain the upper limit of the difference of cumulative metrics of each optimal path;

[0083] According to the number of optimal paths, the constraint length of the convolutional encoder and the difference between the maximum value and the minimum value of the branch metric, the upper limit of the cumulative metric difference of each optimal path of LVA is obtained.

[0084] For the method of obtaining the upper limit of the difference, please refer to the attached figure 2 Relevant descriptions of the illustrated embodiments will not be repeated here.

[0085] Step 302: according to the selected normalization value, perform normalization processing on the cumulative metric value of each optimal path;

[0086] According to the acquisition method of the difference upper limit of the cumulative metric of each optimal path, after obtaining the upper...

Embodiment 3

[0097] In this embodiment, first obtain the upper limit of the difference value upper limit of the cumulative metric of each optimal path in any state, and then arbitrarily select the cumulative metric value of any optimal path in a certain state as the normalized value, and optimize each LVA according to the normalized value The cumulative metric value of the path is normalized, and the bit width of the cumulative metric value of each optimal path is determined according to the value range of the normalized cumulative metric value of each optimal path of the LVA.

[0098] see Figure 4 , the fixed-point method provided in this embodiment may include:

[0099] Step 401: Obtain the upper limit of the cumulative metric difference of each optimal path in any state of the LVA;

[0100] Among them, the method and appended figure 2 The descriptions in the embodiments are basically the same and will not be repeated here.

[0101] Step 402: arbitrarily select a preferred path cumu...

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Abstract

The embodiment of the invention discloses a difference upper limit obtaining method, a fixed point method and a device thereof, wherein the difference upper limit obtaining method comprises: obtaining the difference of the maximum and the minimum of the branch measurement; determining the number of the preferred path and the constraint length of the convolutional coder; obtaining the difference upper limit of the cumulated measurement of the preferred path. The fixed point method includes: obtaining the difference upper limit of the cumulated measurement of the preferred path; performing the normalization process on the cumulated measurement of the preferred path according to the selected normalization value; determining the bit wide of the cumulated measurement of the preferred path according to the selected normalization value and the difference upper limit of each cumulated measurement of the preferred path. The difference upper limit obtaining method can effectively guide the acquisition of the difference upper limit of the cumulated measurement of the preferred path, furthermore, the fixed point bit width can be reasonably arranged through performing the fixed point on the cumulated measurement of the preferred path after being normalized, which ensures the performance of the fixed point of the encoder and reasonably controls the complexity and the cost of the encoder.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a difference upper limit acquisition and fixed-point technology. Background technique [0002] The codes used in various error control in the communication system can be divided into two categories: block codes and convolutional codes according to the different processing methods for information elements. The check element of each code group of the block code is only related to the information element of this group; the check element of each code group of the convolutional code is not only related to the information element of this group, but also related to the information element of the m segment before it. Among them, m is code storage. Since the correlation between each code segment is fully utilized in the coding process of the convolutional code, the performance of the convolutional code is better than that of the block code under the premise of the same coding effi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L1/00
Inventor 茅宇晨阙程晟
Owner SHANGHAI HUAWEI TECH CO LTD
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