CN101834618B - Turbo decoding method and turbo decoder - Google Patents

Abstract

A method and a turbo decoder for turbo decoding a coded signal having the same initial state and final state are disclosed. The method includes: performing a cyclic iterative operation of Turbo decoding on the encoded signal until the iteration termination condition is met to generate a decoded signal, wherein, in each iterative operation process, the forward initial state measurement (initial FSM) and the backward initial state The metric (initial BSM) performs forward recursive operation and backward recursive operation, thereby obtaining the final FSM and final BSM, and based on the final FSM and final BSM obtained in the previous iteration operation, the initial FSM and initial BSM of the current iteration are set. BSM, wherein the initial FSM and initial BSM are set as predetermined state metrics in the first iteration operation. According to the present invention, the initial FSM and the initial BSM in each iterative operation can be relatively simply determined without introducing additional calculation load, thereby facilitating the execution of Turbo decoding.

Description

Turbo decoding method and Turbo decoder

technical field

The present invention generally relates to methods and turbo decoders for turbo decoding encoded signals. More particularly, the present invention relates to a method of turbo decoding a coded signal having the same initial state and final state, and a turbo decoder.

Background technique

So far, wireless communication systems have developed rapidly. The original second-generation mobile communication system, that is, the Global Mobile Communications (GSM) system has continuously evolved to General Packet Radio Service (GPRS), Enhanced Data Rates for GSM Evolution (EDGE) and other technologies, which greatly improved the data transmission of the system. ability. The third-generation mobile communication systems with higher transmission rates, such as wideband code division multiple access (WCDMA), CDMA2000 and other technologies, have also been deployed in many countries and regions around the world, and have begun to be put into commercial use. While the cellular communication technology is developing, other wireless access technologies, such as Wireless Local Area Network (WLAN) and Worldwide Interoperability for Microwave Access (WiMAX) technology have also developed rapidly. In addition, projects such as IEEE 802.16m technology for the fourth-generation mobile communication system, the third-generation partnership project evolution technology (3GPP LTE), and the third-generation partnership project evolution technology enhancement (3GPP LTE+) have also begun to enter the research and development stage .

The Turbo decoder is an important device of the physical layer of the above-mentioned various communication systems. In data communication business, Turbo coding/decoding is the most important channel coding/decoding method. The principle and implementation method of the Turbo encoder are relatively fixed, while the performance of the Turbo decoder will directly affect the performance of the receiver. Turbo codes were first proposed in 1993 by C.Berrou et al. Among them, the code with a large constraint length is realized by the pseudo-random interleaving of the component codes, which is close to the characteristics of random codes, and by using iterative decoding, it can obtain medium decoding complexity, and the bit error rate is maintained on the order of 1e-5, thus approaching the Shannon limit. Various studies and simulation results show that Turbo codes not only have superior performance in resisting additive Gaussian noise, but also have strong anti-fading and anti-interference capabilities, and their error correction performance is close to Shannon's limit, which makes Turbo codes in actual communication There are a wide range of applications in the system, among which the third-generation mobile communication systems, such as International Mobile Telecommunications-2000 (IMT-2000) and IEEE 802.16e systems, use Turbo codes as one of their channel standards for high-speed data transmission.

For a long time, in the process of Turbo encoding, the initial state and the final state of the encoder are preset to a certain known value, for example, the initial state or the final state is set to 0 state, so as to facilitate Turbo decoding. A disadvantage of this approach is that tail bits must be appended to the information bits to control the final state. The addition of tail bits reduces the spectral efficiency of the system. For the specific process of Turbo encoding/decoding, see, for example, "Turbo Coding, Turbo Equalization and Space-Time Coding for Transmission over Fading Channels" written by Lajos Ha and B.L.Yeap (Wiley-IEEE Press published in September 2002, ISBN No. : 978-0-470-84726-8), which will not be described in detail here.

In order to avoid adding tail bits at the end of information bits, in the IEEE 802.16e standard, a turbo decoding scheme of double-binary circular recursive systematic convolutional (DBCRSC) coding is adopted. In this scheme, the initial state and final state of the encoded signal are equal, but not predetermined values. Therefore, the receiver needs to first determine the initial state and the final state during the decoding operation. For example, in the Turbo decoder and the Turbo decoding method proposed in US Patent Application Publication US2008/0273631A1, during each iterative operation of Turbo decoding, the total code blocks (including effective load block and padding block) to perform forward recursion and backward recursion to calculate the estimated forward state metric (FSM) and estimated backward state metric (BSM), and then use the estimated FSM and The BSM performs forward recursion and backward recursion on the remainder of the total code block. That is to say, in each iterative operation of Turbo decoding, a part of the received data needs to be processed in advance, and initial state metrics and final state metrics of forward recursion and backward recursion are calculated. However, such a method is neither an optimal solution, but also brings additional computation load.

Therefore, in each iterative operation of Turbo decoding, how to make better use of the characteristic that the initial state and final state of the encoded signal are equal to determine the initial state metric and final state of each iterative operation with a smaller amount of calculation Metrics, so as to facilitate the execution of Turbo decoding, are still one of the urgent problems to be solved.

Contents of the invention

A brief overview of the invention is given below in order to provide a basic understanding of some aspects of the invention. It should be understood that this summary is not an exhaustive overview of the invention. It is not intended to identify key or critical parts of the invention nor to delineate the scope of the invention. Its purpose is merely to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later.

In order to solve the above-mentioned problems of the prior art, an object of the present invention is to provide a method and a Turbo decoder for turbo decoding a coded signal having the same initial state and final state, which fully utilizes the initial state of the coded signal The state and the final state are equal, and it can make the decoding algorithm achieve better performance as the iterative operation proceeds without introducing additional computation.

In order to achieve the above object, according to one aspect of the present invention, a method for turbo decoding an encoded signal having the same initial state and final state is provided, which includes the following steps: performing turbo decoding on the encoded signal Loop iterative operation until the iteration termination condition is met to generate the decoded signal, wherein, in each iterative operation of Turbo decoding, the forward recursive operation and the backward recursive operation are respectively performed from the forward initial state metric and the backward initial state metric , thus obtaining the forward final state metric and the backward final state metric, in the first iteration of Turbo decoding, the forward initial state metric and the backward initial state metric are set as predetermined state metrics, and in the Turbo decoding In the n+1th iterative operation, the forward initial state metric and the backward initial state metric are set based on the forward final state metric and the backward final state metric obtained in the nth iterative operation, where n is a natural number .

According to another aspect of the present invention, there is also provided a Turbo decoder for performing Turbo decoding on encoded signals having the same initial state and final state, which includes: at least one decoding module, configured to perform Turbo decoding on the encoded signal At least one component code of is subjected to a cyclic iterative operation of Turbo decoding until the iteration termination condition is met to generate a decoded signal, wherein during each iteration of Turbo decoding, the forward initial state measurement of the at least one component code is respectively performing forward recursive operation and backward recursive operation with the backward initial state metric, thereby obtaining the forward final state metric and the backward final state metric of the at least one component code, wherein the Turbo decoder further includes: at least A forward and backward initial state setting device, used to set the forward initial state metric and the backward initial state metric of the at least one component code, and provide it to the at least one decoding module, wherein, in Turbo decoding In the first iterative operation, the forward initial state metric and the backward initial state metric of the at least one component code are set as predetermined state metrics, and in the n+1th iterative operation of Turbo decoding, the at least one The forward initial state metric and the backward initial state metric of the component codes are set based on the forward final state metric and the backward final state metric of the at least one component code obtained in the n-th iterative operation, where n is Natural number.

Wherein, the forward initial state metric includes the probability or log probability likelihood ratio of each possible initial state of the encoded signal, and the backward initial state metric includes the probability or log probability of each possible final state of the encoded signal. Log probability likelihood ratio.

The advantage of the present invention is that, in the Turbo decoding method and the Turbo decoder according to the present invention, fully consider and utilize the characteristic that the initial state and the final state of the coded signal are equal, based on the last iterative operation obtained in Turbo decoding The forward final state metric (also referred to as the final FSM for short) and the backward final state metric (also referred to as the final BSM for short) are used to set the forward initial state metric in the current iterative operation of Turbo decoding (also referred to as Initial FSM) and backward initial state metric (also referred to as initial BSM for short), so no additional operations are required to obtain the forward initial state metric and the backward initial state metric, and as the iterative operation of Turbo decoding proceeds, The calculation of the initial state metric and the final state metric of forward recursion and backward recursion becomes more and more accurate, so that the decoding algorithm can achieve better performance.

These and other advantages of the present invention will be more apparent through the following detailed description of the preferred embodiments of the present invention with reference to the accompanying drawings.

Description of drawings

The present invention can be better understood by referring to the following description given in conjunction with the accompanying drawings, wherein the same or similar reference numerals are used throughout to designate the same or similar parts. The accompanying drawings, together with the following detailed description, are incorporated in and form a part of this specification, and serve to further illustrate preferred embodiments of the invention and explain the principles and advantages of the invention. In the attached picture:

FIG. 1 shows a schematic flowchart of a method for turbo decoding coded signals having the same initial state and final state according to an embodiment of the present invention;

Fig. 2 shows a schematic block diagram of a Turbo decoder for performing Turbo decoding on coded signals having the same initial state and final state according to an embodiment of the present invention; and

Fig. 3 shows the performance curve of performing Turbo decoding on a DBCRSC coded signal by using the Turbo decoding method shown in Fig. 1 and/or the Turbo decoder shown in Fig. 2 according to the IEEE 802.16e specification.

It will be appreciated by those skilled in the art that elements in the figures are illustrated for simplicity and clarity only and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of the embodiments of the present invention.

Detailed ways

Exemplary embodiments of the present invention will be described below with reference to the accompanying drawings. In the interest of clarity and conciseness, not all features of an actual implementation are described in this specification. It should be understood, however, that in developing any such practical embodiment, many implementation-specific decisions must be made in order to achieve the developer's specific goals, such as meeting those constraints related to the system and business, and those Restrictions may vary from implementation to implementation. Moreover, it should also be understood that development work, while potentially complex and time-consuming, would at least be a routine undertaking for those skilled in the art having the benefit of this disclosure.

Here, it should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only the device structure and/or processing steps closely related to the solution according to the present invention are shown in the drawings, and the Other details not relevant to the present invention are described.

Fig. 1 shows a schematic flowchart of a method 100 for turbo decoding a coded signal (for example, a DBCRSC coded signal) having the same initial state and final state according to an embodiment of the present invention.

As shown in FIG. 1 , the turbo decoding method 100 starts by initializing the number of iterations i of turbo decoding to 1 in step S110 , and then judges in step S120 whether the iterative operation of turbo decoding to be performed is the first iterative operation.

If it is determined in step S120 that the first iteration of Turbo decoding is to be performed, then the processing of method 100 proceeds to step S130, where the forward initial state metric (i.e., initial FSM) and the backward initial state metric (i.e., Initial BSM) are respectively set as predetermined state metrics.

In one example of the turbo decoding method 100, the initial FSM includes probability or log probability likelihood ratios for each possible initial state of the encoded signal, and the initial BSM includes the probability for each possible final state of the encoded signal probability or log probability likelihood ratio; and in the first iteration of Turbo decoding, the initial FSM and initial BSM are respectively set as follows: the probability or log probability likelihood of each possible initial state of the encoded signal The ratios are set equal, and the probability or log probability likelihood ratios of the respective possible final states of the encoded signal are set equal and equal to a certain predetermined value (for example, 0). Wherein, the probability and the logarithmic probability likelihood ratio are in one-to-one correspondence, and can be calculated mutually. However, it should be understood that the principles of the present invention are not limited thereto. For example, in the first iteration of turbo decoding, the probability or logarithmic probability likelihood ratio of each possible initial state and each possible final state of the encoded signal may be set to any other non-zero value.

Next, as shown in Figure 1, in step S140, the forward recursive operation and the backward recursive operation are respectively performed from the forward initial state metric and the backward initial state metric, thereby obtaining the forward final state metric of the current iterative operation (ie, final FSM) and backward final state metrics (ie, final BSM). Here, the process of forward recursive operation and backward recursive operation is exactly the same as the process in the existing Turbo decoding, for example, you can refer to "Turbo Coding, Turbo Equalization and Space-Time Coding for Transmission over FadingChannels" mentioned above etc. Therefore, for the sake of brevity in the description, the specific process of the forward recursive operation and the backward recursive operation will not be described in detail here.

Then, in step S150, the forward final state metric and the backward final state metric obtained in step S140 of the current iterative operation are stored for use in the next iterative operation.

Next, the processing flow of the method 100 proceeds to step S160, and it is judged whether a predetermined iteration termination condition is satisfied. Here, the predetermined iteration termination condition may be, for example, reaching a predetermined number of iterations. However, the principle of the present invention is not limited thereto, and those skilled in the art can completely set iteration termination conditions according to actual needs. For example, in some specific occasions, the iteration termination condition can also be set as follows: the cyclic redundancy check (that is, CRC check) is performed on the result of each iteration operation, and if the check is passed, the iteration operation is stopped process, and if the verification fails, continue to the next iteration until the predetermined number of iterations is reached.

If it is determined in step S160 that the iteration termination condition is not satisfied, then in step S170, the number of iterations i is increased by 1, that is, i=i+1, then the processing flow returns to step S120, and it is judged whether the current iteration to be performed is The first iteration operation of turbo decoding.

When it is determined in step S120 that the current iterative operation to be performed is not the first iterative operation of Turbo decoding, the processing flow proceeds to step S180, based on the stored forward final state metrics obtained in the last iterative operation and the backward To the final state metric, to set the forward initial state metric and backward initial state metric of the current iteration.

For example, in an example of the method 100, the backward final state metric and the forward final state metric obtained in the last iterative operation can be respectively set as the forward initial state metric and the backward initial state metric of the current iterative operation ; Alternatively, the forward final state metric and the backward final state metric obtained in the last iterative operation can also be respectively set as the forward initial state metric and the backward initial state metric of the current iterative operation. In this example, the forward initial state metric may include the probability or log probability likelihood ratio of each possible initial state of the encoded signal, and the backward initial state metric may include each possible initial state of the encoded signal. The probability or log probability likelihood ratio of the final state, wherein the probability and the log probability likelihood ratio are in one-to-one correspondence and can be calculated from each other.

In another example of the method 100, the state metric obtained by performing weighted summation of the backward final state metric and the forward final state metric obtained in the last iterative operation may be set as the forward initial state metric of the current iterative operation State metrics and backward initial state metrics.

For example, assuming that the encoded signal is preset with four possible initial states and four corresponding final states when it is encoded by the encoder, wherein the logarithmic probability likelihood ratio of the four possible initial states is are denoted as α ₁ , α ₂ , α ₃ , α ₄ , and the log-likelihood ratios of the four possible final states are denoted as β ₁ , β ₂ , β ₃ , and β ₄ respectively. The forward final state metrics and backward final state metrics obtained in are expressed as: {β ₁ , β ₂ , β ₃ , β ₄ }, and {α ₁ , α ₂ , α ₃ , α ₄ }, then we can According to the equation γ _i = a _i α _i + b _i β _i (where a _i and b _i are weights, i=1, 2, 3, 4), the forward final state metric and the backward final state metric are calculated Weighted summation, and set the obtained state metrics {γ ₁ , γ ₂ , γ ₃ , γ ₄ } as the forward initial state metric and backward initial state metric of the current iterative operation. Wherein, those skilled in the art can set different weights a _i and b _i according to needs. For example, under additive white Gaussian noise (AWGN) channel conditions, it can be considered that the confidence of the forward final state metric and the backward final state metric obtained through recursive operations are equal, so that both a _i and b _i can be set to 0.5 . Of course, they can also be set to other values as needed.

In yet another example of the method 100, the backward final state metric and the forward final state metric obtained in the previous iteration can be weighted and multiplied, and the product is normalized, and then the resulting state metric Set to the forward initial state metric and backward initial state metric of the current iteration.

For example, assuming that the encoded signal is preset with four possible initial states and four corresponding final states when it is encoded by the encoder, wherein the probabilities of the four possible initial states are represented as α ₁ , α ₂ , α ₃ , α ₄ , the probabilities of the four possible final states are denoted as β ₁ , β ₂ , β ₃ , β ₄ , the forward final state metrics and the backward The final state metrics are expressed as: {β ₁ , β ₂ , β ₃ , β ₄ }, and {α ₁ , α ₂ , α ₃ , α ₄ }, then the state metric {γ ₁ can be calculated according to the following equation , γ ₂ , γ ₃ , γ ₄ }:

${\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; /</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 4</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; ,</span>$

And set the calculated state metrics {γ ₁ , γ ₂ , γ ₃ , γ ₄ } as the forward initial state metric and backward initial state metric of the current iterative operation. Wherein, those skilled in the art can set different weights a _i and b _i according to needs, and i=1, 2, 3, 4, j=1, 2, 3, 4.

Referring to Fig. 1 again, after setting the forward initial state metric and the backward initial state metric of the current iterative operation in step S180, perform forward recursion and backward recursion in step S140, and repeat the steps described above In this way, the cyclic iterative operation of Turbo decoding is performed on the coded signal until it is determined in step S160 that the iteration termination condition is met, and the processing flow of the method 100 ends in step S190, so that the decoded signal can finally be obtained.

FIG. 2 shows a schematic block diagram of a turbo decoder 200 for turbo decoding a coded signal having the same initial state and final state according to an embodiment of the present invention. In the turbo decoder 200 shown in FIG. 2, the turbo decoding method described with reference to FIG. 1 can be performed.

As shown in Figure 2, the Turbo decoder 200 includes at least one decoding module (two decoding modules 210A and 210B are shown in the figure, but the principle of the present invention is not limited thereto), for at least one of the encoded signals The component codes are subjected to a cyclic iterative operation of Turbo decoding until an iteration termination condition is satisfied, so as to generate decoded signals of the component codes. Wherein, during each iterative operation of Turbo decoding, the forward recursive operation and the backward recursive operation are respectively performed from the forward initial state metric and the backward initial state metric of the at least one component code, thereby obtaining the at least A forward final state metric and a backward final state metric for a component code. Wherein, the at least one decoding module is a soft decoding module with soft-in and soft-out.

In the Turbo decoder 200 shown in Figure 2, the functions and specific operation processes of the decoding modules 210A and 210B, the summation units 220A and 220B, the interleaver 230, the deinterleaver 240, the hard decision unit 250 and the deinterleaver 260 are the same as The function and operation process of the corresponding components in the existing Turbo decoder are the same (for details, see for example "Turbo Coding, TurboEqualisation and Space-Time Coding for Transmission over FadingChannels" and US Patent Application Publication US2008/0273631A1, etc.), and these components It is not the focus of the present invention, therefore, for the sake of brevity in the description, these components will not be described in detail here.

As shown in Figure 2, different from the existing Turbo decoder, the Turbo decoder 200 also includes at least one forward and backward initial state setting device (two forward and backward initial state setting devices 270A and 270B, but the principle of the present invention is not limited thereto), for setting the forward initial state metric and the backward initial state metric of the at least one component code in each iterative operation of Turbo decoding, and providing them to the at least one decoding module. In the first iterative operation of Turbo decoding, the at least one forward and backward initial state setting device may set the forward initial state metric and the backward initial state metric of the at least one component code as a predetermined state metric, and In the n+1th (where n is a natural number) iterative operation of Turbo decoding, the at least one forward and backward initial state setting device may be based on the previous step of the at least one component code obtained in the nth iterative operation The forward final state metric and the backward final state metric are used to set the forward initial state metric and the backward initial state metric of the at least one component code. In view of the fact that how to set the forward initial state metric and the backward initial state metric in each iterative operation has been described above with reference to the flow chart shown in Figure 1, therefore, in order to avoid unnecessary repetition, no more The function of the at least one forward and backward initial state setting device is described in detail.

Fig. 3 shows the performance curve of performing Turbo decoding on a DBCRSC coded signal by using the Turbo decoding method shown in Fig. 1 and/or the Turbo decoder shown in Fig. 2 according to the IEEE 802.16e specification.

A total of 11 clusters of curves are shown in Fig. 3, wherein each cluster of curves represents the decoding performance corresponding to a modulation and encoding method, and each cluster of curves includes 8 curves, which respectively represent the Decoding performance in the first to eighth iterations of turbo decoding. In Figure 3, the corresponding modulation and coding methods represented by the 11 clusters of curves from left to right are:

(1) QPSK (Quadrature Phase Shift Keying) modulation, 1/2 code rate, repeated encoding 6 times;

(2) QPSK modulation, 1/2 code rate, repeated encoding 4 times;

(3) QPSK modulation, 1/2 code rate, repeated encoding twice;

(4) QPSK modulation, 1/2 code rate, no repeated coding;

(5) QPSK modulation, 3/4 code rate, no repeated coding;

(6) 16QAM (hexadecimal quadrature amplitude modulation) modulation, 1/2 code rate, no repeated coding;

(7) 16QAM modulation, 3/4 code rate, no repeated coding;

(8) 64QAM modulation (sixty-four quadrature amplitude modulation), 1/2 code rate, no repeated coding;

(9) 64QAM modulation, 2/3 code rate, no repeated coding;

(10) 64QAM modulation, 3/4 code rate, no repeated coding;

(11) 64QAM modulation, 5/6 code rate, no repeated coding.

It is not difficult to see from the decoding performance curve shown in Figure 3 that as the number of iterative operations of Turbo decoding increases, the BLER (Block Error Rate) decreases day by day under the same SINR (Signal-to-Interference-Noise Ratio), or when the BLER In the same situation, the SINR decreases day by day, that is to say, with the iterative operation of Turbo decoding, the Turbo decoding algorithm can achieve better performance.

From the above description of the Turbo decoding method and the Turbo decoder according to the embodiment of the present invention, it can be seen that the characteristic that the initial state and the final state of the encoded signal are equal is fully considered in the iterative operation of Turbo decoding. The forward final state metric (final FSM) and backward final state metric (final BSM) obtained in the operation are used to set the forward initial state metric (initial FSM) and backward initial state metric (initial BSM) of the current iterative operation, There is no need to introduce additional calculations to estimate the initial FSM and initial BSM as in the prior art, and as the iterative operation proceeds, the calculation of the initial state metric and the final state metric becomes more and more accurate, so that the decoding algorithm can obtain better performance.

In addition, obviously, each operation process of the above method according to the present invention can also be implemented in the form of computer executable programs stored in various machine-readable storage media.

Moreover, the purpose of the present invention can also be achieved in the following manner: the storage medium storing the above-mentioned executable program code is directly or indirectly provided to a system or device, and the computer or central processing unit (CPU) in the system or device Read and execute the above program code. At this time, as long as the system or device has the function of executing the program, the embodiment of the present invention is not limited to the program, and the program can also be in any form, for example, an object program, a program executed by an interpreter, or a program provided to an operating system. script programs, etc.

The above-mentioned machine-readable storage media include, but are not limited to: various memories and storage units, semiconductor devices, magnetic disk units such as optical, magnetic and magneto-optical disks, and other media suitable for storing information, and the like.

In addition, the present invention can also be realized by connecting a computer to a corresponding website on the Internet, downloading and installing the computer program code according to the present invention into the computer, and then executing the program.

Finally, it should also be noted that in this text, relational terms such as left and right, first and second, etc. are only used to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between such entities or operations. Furthermore, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus comprising a set of elements includes not only those elements, but also includes elements not expressly listed. other elements of or also include elements inherent in such a process, method, article, or device. Without further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising said element.

Although the embodiments of the present invention have been described in detail above with reference to the accompanying drawings, it should be understood that the above-described embodiments are only used to illustrate the present invention, rather than to limit the present invention. Various modifications and changes can be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the present invention. Accordingly, the scope of the present invention is limited only by the appended claims and their equivalents.

Claims (19)

1. one kind is used for the code signal with identical initial condition and end-state is carried out the method that Turbo decodes, may further comprise the steps: described code signal is carried out the loop iteration computing of Turbo decoding, until satisfy stopping criterion for iteration, with the generating solution coded signal, wherein

In the each time interative computation process of Turbo decoding, carry out forward recursive computing and backward recursive computing from forward direction initial condition tolerance and backward initial condition tolerance respectively, obtain thus forward direction end-state tolerance and backward end-state tolerance,

In the first time of Turbo decoding interative computation, forward direction initial condition tolerance and backward initial condition tolerance are set to predetermined state and measure, and

In the n+1 time interative computation of Turbo decoding, forward direction initial condition tolerance and backward initial condition tolerance are based on that the forward direction end-state that obtains in the n time interative computation is measured and backward end-state is measured and setting, and wherein n is natural number.

2. method according to claim 1, wherein, described forward direction initial condition tolerance comprises probability or the logarithm probability likelihood ratio of each possibility initial condition of described code signal, and described backward initial condition tolerance comprises probability or the logarithm probability likelihood ratio of each possibility end-state of described code signal.

3. method according to claim 2, wherein, forward direction initial condition tolerance and rear being set to initial condition tolerance in the process that predetermined state measures, probability or the logarithm probability likelihood ratio of each possibility initial condition of described code signal are set to predetermined value, and probability or the logarithm probability likelihood ratio of each possibility end-state of described code signal are set to described predetermined value.

4. any one described method in 3 according to claim 1, wherein, the tolerance of the forward direction initial condition in the n+1 time interative computation of Turbo decoding and rear tolerance to initial condition are respectively obtain in the n time interative computation rear to end-state tolerance and forward direction end-state tolerance.

5. any one described method in 3 according to claim 1, wherein, the tolerance of the forward direction initial condition in the n+1 time interative computation of Turbo decoding and rear tolerance to initial condition are respectively that the forward direction end-state that obtains in the n time interative computation is measured and measured to end-state afterwards.

6. any one described method in 3 according to claim 1, wherein, the tolerance of the forward direction initial condition in the n+1 time interative computation of Turbo decoding and rear tolerance to initial condition are by forward direction end-state tolerance and rear the tolerance to end-state that obtains in the n time interative computation is weighted the state measurement that summation obtains.

7. any one described method in 3 according to claim 1, wherein, the tolerance of the forward direction initial condition in the n+1 time interative computation of Turbo decoding and rear to initial condition tolerance be by the forward direction end-state that obtains in the n time interative computation is measured and rear measure to be weighted to end-state multiply each other and product carried out the state measurement that normalization obtains.

8. any one described method in 3 according to claim 1, wherein, described code signal is duobinary system circular recursion system convolutional coded signal.

9. method according to claim 4, wherein, described code signal is duobinary system circular recursion system convolutional coded signal.

10. method according to claim 5, wherein, described code signal is duobinary system circular recursion system convolutional coded signal.

11. method according to claim 6, wherein, described code signal is duobinary system circular recursion system convolutional coded signal.

12. method according to claim 7, wherein, described code signal is duobinary system circular recursion system convolutional coded signal.

13. Turbo decoder that is used for the code signal with identical initial condition and end-state is carried out the Turbo decoding, comprise: at least one decoder module, be used at least one component code of described code signal is carried out the loop iteration computing of Turbo decoding, until satisfy stopping criterion for iteration, with the generating solution coded signal, wherein in the each time interative computation process of Turbo decoding, carry out forward recursive computing and backward recursive computing from forward direction initial condition tolerance and the backward initial condition tolerance of described at least one component code respectively, obtain thus forward direction end-state tolerance and the backward end-state tolerance of described at least one component code, wherein, described Turbo decoder further comprises:

At least one forward-backward algorithm initial condition setting device for forward direction initial condition tolerance and the backward initial condition tolerance of each time at least one component code described in the interative computation that is arranged on the Turbo decoding, and provides it to described at least one decoder module,

Wherein, in the first time of Turbo decoding interative computation, forward direction initial condition tolerance and the backward initial condition tolerance of described at least one component code are set to predetermined state tolerance, and in the n+1 time interative computation of Turbo decoding, forward direction end-state that the forward direction initial condition of described at least one component code tolerance and backward initial condition tolerance are based on described at least one component code that obtains in the n time interative computation is measured and backward end-state measures to arrange, and wherein n is natural number.

14. Turbo decoder according to claim 13, wherein, described forward direction initial condition tolerance comprises probability or the logarithm probability likelihood ratio of each possibility initial condition of described code signal, and described backward initial condition tolerance comprises probability or the logarithm probability likelihood ratio of each possibility end-state of described code signal.

15. Turbo decoder according to claim 14, wherein, in the first time of Turbo decoding interative computation, probability or the logarithm probability likelihood ratio of each possibility initial condition of the described code signal of described at least one forward-backward algorithm initial condition setting device are set to equal predetermined value, and probability or the logarithm probability likelihood ratio of each possibility end-state of described code signal are set to equal described predetermined value.

16. any one described Turbo decoder in 15 according to claim 13, wherein, in the n+1 time interative computation of Turbo decoding, the rear of described at least one component code that described at least one forward-backward algorithm initial condition setting device will obtain in the n time interative computation is set to respectively the forward direction initial condition tolerance of described at least one component code and measures to initial condition afterwards to end-state tolerance and forward direction end-state tolerance, and provides it to described at least one decoder module.

17. any one described Turbo decoder in 15 according to claim 13, wherein, in the n+1 time interative computation of Turbo decoding, the forward direction end-state of described at least one component code that described at least one forward-backward algorithm initial condition setting device will obtain in the n time interative computation tolerance and be set to respectively the forward direction initial condition tolerance of described at least one component code and measure to initial condition afterwards to end-state tolerance afterwards, and provide it to described at least one decoder module.

18. any one described Turbo decoder in 15 according to claim 13, wherein, in the n+1 time interative computation of Turbo decoding, described at least one forward-backward algorithm initial condition setting device is by to the forward direction end-state tolerance of described at least one component code of obtaining in the n time interative computation with being weighted state measurement that summation obtains to end-state tolerance and being set to the forward direction initial condition tolerance of described at least one component code and measuring to initial condition afterwards afterwards, and provides it to described at least one decoder module.

19. any one described Turbo decoder in 15 according to claim 13, wherein, in the n+1 time interative computation of Turbo decoding, described forward-backward algorithm initial condition setting device by to the forward direction end-state tolerance of described at least one component code of in the n time interative computation, obtaining and rear be weighted to multiply each other and product is carried out state measurement that normalization obtains to end-state tolerance be set to the forward direction initial condition tolerance of described at least one component code and measure to initial condition afterwards, and provide it to described at least one decoder module.

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