CN113949488B - High-order frequency domain computation diversity method based on multi-component expansion - Google Patents
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- H04L1/00—Arrangements for detecting or preventing errors in the information received
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- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
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- H04L1/0045—Arrangements at the receiver end
- H04L1/0047—Decoding adapted to other signal detection operation
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- H04L1/04—Arrangements for detecting or preventing errors in the information received by diversity reception using frequency diversity
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Abstract
A high-order frequency domain computation diversity method based on multi-component expansion belongs to the technical field of wireless communication. The invention solves the problem of low diversity gain of the existing frequency domain calculation diversity method. The invention spreads the data in multiple components, and makes the energy distribution of the signal tend to average by using the weighted transformation, so that the computation diversity transmitting signal is evenly dispersed in a plurality of independent fading channels, thereby improving the diversity gain of the frequency domain computation diversity method. The invention can be applied to the technical field of wireless communication.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a high-order frequency domain computation diversity method based on multi-component expansion.
Background
In the field of wireless communication, the bit error rate performance of a computation diversity algorithm can be effectively improved by prolonging the length of a data block and utilizing the residual available spectrum resources to carry out frequency domain two-component computation diversity. With the increase of the extension length, the ratio of the resource length occupied by each data stream to the total resource length is further reduced, but when the extension conversion length of the frequency domain two-component computation diversity is further prolonged from the aspect of energy averaging distribution anti-fading, a single data block is taken as a research object, and signals of the single data block are still concentrated in the two data blocks, so when the extension conversion length of the frequency domain two-component computation diversity is prolonged, the problem that the diversity gain of the frequency domain computation diversity is lower exists, and the deep fading resistance of the single data block is weakened.
Disclosure of Invention
The invention aims to solve the problem of low diversity gain of the existing frequency domain computation diversity method, and provides a high-order frequency domain computation diversity method based on multi-component expansion.
The technical scheme adopted for solving the technical problems is as follows: a high-order frequency domain computation diversity method based on multi-component expansion specifically comprises the following steps:
generating original data D with the length of kL at a transmitting end, wherein L is the length of a code block, and k is a positive integer;
inputting a transformation order N, performing post-zero filling operation on the original Data D according to the transformation order N to obtain Data after zero filling, recording the Data after zero filling as data_Z (1), wherein the total length of the Data after zero filling is 2 N *L；
Step two, performing multi-component expansion on the zero-padded data to obtain a multi-component expansion result;
the specific process of the second step is as follows:
step two, initializing the iteration times n=1 of a transmitting end;
step two, starting from the first bit of the Data data_Z (n), dividing the Data after zero padding into 2 N-n Each primary data block has a length of 2 n *L；
After each primary Data block is processed, the processing result corresponding to each primary Data block is expressed as one path of serial Data and recorded as Data Data_Z (n+1);
thirdly, enabling n to be increased by 1, and repeating the process of the second step;
stopping iteration until n=n+1, and taking the Data data_z (n+1) obtained in the last iteration as a multi-component expansion result;
performing IFFT transformation on the multi-component expansion result to obtain an IFFT transformation result, and transmitting the IFFT transformation result through an antenna;
step four, a receiving end receives signals, and after sequentially carrying out equalization and FFT conversion on the received signals, FFT conversion results are obtained; processing the FFT conversion result, and marking the processing result as data_R (1);
step five, obtaining an output signal by processing the data_R (1);
the specific process of the fifth step is as follows:
step five, initializing the iteration times r=1 of a receiving end;
step five, starting from the first bit of data_R (R), divide data_R (R) into 2 r Group data, each group data having a length of 2 N-r *L；
Processing each group of Data respectively, and representing the processing result corresponding to each group of Data as one path of serial Data and recording the serial Data as Data data_R (r+1);
step five, enabling r to be increased by 1, and repeating the process of the step five;
stopping iteration until r=n, obtaining Data data_r (N) obtained in the last iteration, extracting the former kL bit Data of the Data data_r (N), and taking the extracted Data as an output signal.
Further, the transformation order N is determined according to the length of the total expansion resource, and 2 N * L is the length of the total extended resource.
Further, the received signals are sequentially subjected to equalization and FFT, and the specific equalization process is as follows:
wherein Y is a signal received by a receiving end, G is an equalization matrix,and X is a signal transmitted by a transmitting end through an antenna, H is a channel state information matrix, and Z is zero-mean additive Gaussian white noise.
Further, the processing is performed on each primary data block respectively, which specifically includes:
for any one primary data block:
wherein f (t) represents the data of the data block, and x is the processing node of the data blockIf F (-t) represents the result of F (t) through data inversion, F (t) represents the result of F (t) through fourier transform of the data block data, F (-t) represents the result of F (t) through data inversion,is a transform coefficient;
the processing mode of other primary data blocks is the same.
Further, the transform coefficientsThe method comprises the following steps:
wherein e is the base of natural logarithm, i is the imaginary unit, θ l For eigenvalues, l=0, 1,2,3.
Further, in the fifth step, each group of data is processed respectively, and the specific process of the processing is as follows:
for any set of data:
wherein x is 1 F for processing the set of data 1 (t) represents the set of data, f 1 (-t) represents f 1 (t) results obtained by data inversion, F 1 (t) represents the result of Fourier transform of the group of data, F 1 (-t) represents F 1 (t) as a result of data inversion,is a transform coefficient;
the processing manner is the same for other sets of data.
Further, the transform coefficientsThe method comprises the following steps:
further, the characteristic value θ l The relation of (2) is:
wherein θ l ∈(0,2π]，l＝0,1,2,3。
The beneficial effects of the invention are as follows: the invention provides a high-order frequency domain computation diversity method based on multi-component expansion.
Drawings
FIG. 1 is a flow chart of a high-order frequency domain computation diversity method based on multi-component expansion of the present invention;
in the drawing the view of the figure,power for Z;
FIG. 2a is a graph showing energy distribution after two-fold length data is subjected to first-order frequency domain two-component computation diversity and second-order frequency domain two-component computation diversity;
FIG. 2b is a graph showing energy distribution after three-fold length data is subjected to first-order frequency domain two-component computation diversity and second-order frequency domain two-component computation diversity;
FIG. 2c is a graph showing the energy distribution of four times of length data after the first-order frequency domain two-component computation diversity and the second-order frequency domain two-component computation diversity;
fig. 3 is a bit error rate comparison diagram of first-order frequency domain two-component computation diversity and second-order frequency domain two-component computation diversity.
Detailed Description
The first embodiment is as follows: as shown in fig. 1. The high-order frequency domain computation diversity method based on multi-component expansion, which is described in the embodiment, specifically comprises the following steps:
generating original data D with the length of kL at a transmitting end, wherein L is the length of a code block, and k is a positive integer;
inputting a transformation order N, performing post-zero filling operation on the original Data D according to the transformation order N to obtain Data after zero filling, recording the Data after zero filling as data_Z (1), wherein the total length of the Data after zero filling is 2 N *L，2 N ＞k；
Step two, performing multi-component expansion on the zero-padded data to obtain a multi-component expansion result;
the specific process of the second step is as follows:
step two, initializing the iteration times n=1 of a transmitting end;
step two, starting from the first bit of the Data data_Z (n), dividing the Data after zero padding into 2 N-n Each primary data block has a length of 2 n *L；
After each primary Data block is processed, the processing result corresponding to each primary Data block is expressed as one path of serial Data (the position of the processing result corresponding to each primary Data block in the serial Data corresponds to the position of the original primary Data block in the zero-filling Data), and the serial Data is recorded as Data data_Z (n+1);
thirdly, enabling n to be increased by 1, and repeating the process of the second step;
stopping iteration until n=n+1, and taking the Data data_z (n+1) obtained in the last iteration as a multi-component expansion result;
performing IFFT transformation on the multi-component expansion result to obtain an IFFT transformation result, and transmitting the IFFT transformation result through an antenna;
step four, a receiving end receives signals, and after sequentially carrying out equalization and FFT conversion on the received signals, FFT conversion results are obtained; processing the FFT conversion result, and marking the processing result as data_R (1);
step five, obtaining an output signal by processing the data_R (1);
the specific process of the fifth step is as follows:
step five, initializing the iteration times r=1 of a receiving end;
step five, starting from the first bit of data_R (R), divide data_R (R) into 2 r Group data, each group data having a length of 2 N-r *L；
Processing each group of Data respectively, and representing the processing result corresponding to each group of Data as one path of serial Data and recording the serial Data as Data data_R (r+1);
step five, enabling r to be increased by 1, and repeating the process of the step five;
stopping iteration until r=n, obtaining Data data_r (N) obtained in the last iteration, extracting the former kL bit Data of the Data data_r (N), and taking the extracted Data as an output signal.
The second embodiment is as follows: the first difference between this embodiment and the specific embodiment is that: the transformation order N is determined according to the length of the total expansion resource, and 2 N * L is the length of the total extended resource.
Other steps and parameters are the same as in the first embodiment.
And a third specific embodiment: this embodiment differs from the first or second embodiment in that: the received signals are sequentially subjected to equalization and FFT conversion, and the specific equalization process is as follows:
wherein Y is a signal received by a receiving end, G is an equalization matrix,and X is a signal transmitted by a transmitting end through an antenna, H is a channel state information matrix, and Z is zero-mean additive Gaussian white noise.
Other steps and parameters are the same as in the first or second embodiment.
The specific embodiment IV is as follows: this embodiment differs from one of the first to third embodiments in that: each primary data block is processed respectively, and the method specifically comprises the following steps:
for any one primary data block:
wherein F (t) represents the data of the data block, x is the processing result of the data block, F (-t) represents the result of F (t) obtained by data inversion, F (t) represents the result of F (t) obtained by fourier transformation, F (-t) represents the result of F (t) obtained by data inversion,is a transform coefficient;
the processing mode of other primary data blocks is the same.
Other steps and parameters are the same as in one to three embodiments.
Fifth embodiment: this embodiment differs from one to four embodiments in that: the transform coefficientsThe method comprises the following steps:
wherein e is the base of natural logarithm, i is the imaginary unit, θ l For eigenvalues, l=0, 1,2,3.
Other steps and parameters are the same as in one to four embodiments.
Specific embodiment six: this embodiment differs from one of the first to fifth embodiments in that: in the fifth step, each group of data is processed respectively, and the specific process of the processing is as follows:
for any set of data:
wherein x is 1 F for processing the set of data 1 (t) represents the set of data, f 1 (-t) represents f 1 (t) results obtained by data inversion, F 1 (t) represents the result of Fourier transform of the group of data, F 1 (-t) represents F 1 (t) as a result of data inversion,is a transform coefficient;
the processing manner is the same for other sets of data.
In the fourth step, the method of the present embodiment is also used for processing the FFT conversion result.
Other steps and parameters are the same as in one of the first to fifth embodiments.
Seventh embodiment: this embodiment differs from one of the first to sixth embodiments in that: the transform coefficientsThe method comprises the following steps:
other steps and parameters are the same as in one of the first to sixth embodiments.
Eighth embodiment: this embodiment differs from one of the first to seventh embodiments in that: the characteristic value theta l The relation of (2) is:
wherein θ l ∈(0,2π]，l＝0,1,2,3。
Other steps and parameters are the same as those of one of the first to seventh embodiments.
As shown in fig. 2a, 2b and 2c, the data with lengths twice, three times and four times respectively pass through the first-order and second-order frequency domain two-component computation diversity (FDC-CD) respectively to obtain an energy distribution diagram. And no matter how much the proportion of the original data quantity to the total resource block is, after the two-component computation diversity transformation of the second-order frequency domain, each group of data can be uniformly distributed on the whole resource block, and the effect superior to the first-order diversity is realized. Thus, for a total extension length of 2, the original data code block length N The optimal energy distribution can be completed by only expanding FDC-CD in N order at most.
As shown in fig. 3, on the premise that the total extended resource length is 4 times of the original data code block length, the bit error rate performance of the second-order FDC-CD is improved compared with that of the first-order FDC-CD under the condition that the original data occupies 2/4, 3/4 or 4/4 of the ratio, and the smaller the proportion of the original data is, the larger the gain is.
The above examples of the present invention are only for describing the calculation model and calculation flow of the present invention in detail, and are not limiting of the embodiments of the present invention. Other variations and modifications of the above description will be apparent to those of ordinary skill in the art, and it is not intended to be exhaustive of all embodiments, all of which are within the scope of the invention.
Claims (4)
1. The high-order frequency domain computation diversity method based on multi-component expansion is characterized by comprising the following steps of:
generating original data D with the length of kL at a transmitting end, wherein L is the length of a code block, and k is a positive integer;
inputting a transformation order N, performing post-zero filling operation on the original Data D according to the transformation order N to obtain Data after zero filling, recording the Data after zero filling as data_Z (1), wherein the total length of the Data after zero filling is 2 N *L；
Step two, performing multi-component expansion on the zero-padded data to obtain a multi-component expansion result;
the specific process of the second step is as follows:
step two, initializing the iteration times n=1 of a transmitting end;
step two, starting from the first bit of the Data data_Z (n), dividing the Data after zero padding into 2 N-n Each primary data block has a length of 2 n *L；
After each primary Data block is processed, the processing result corresponding to each primary Data block is expressed as one path of serial Data and recorded as Data Data_Z (n+1);
each primary data block is processed respectively, and the method specifically comprises the following steps:
for any one primary data block:
wherein F (t) represents the data of the data block, x is the processing result of the data block, F (-t) represents the result of F (t) obtained by data inversion, F (t) represents the result of F (t) obtained by fourier transformation, F (-t) represents the result of F (t) obtained by data inversion,is a transform coefficient;
the processing mode of other primary data blocks is the same;
the transform coefficientsThe method comprises the following steps:
wherein e is the base of natural logarithm, i is the imaginary oneNumber units, θ l For eigenvalues, l=0, 1,2,3;
thirdly, enabling n to be increased by 1, and repeating the process of the second step;
stopping iteration until n=n+1, and taking the Data data_z (n+1) obtained in the last iteration as a multi-component expansion result;
performing IFFT transformation on the multi-component expansion result to obtain an IFFT transformation result, and transmitting the IFFT transformation result through an antenna;
step four, a receiving end receives signals, and after sequentially carrying out equalization and FFT conversion on the received signals, FFT conversion results are obtained; processing the FFT conversion result, and marking the processing result as data_R (1);
step five, obtaining an output signal by processing the data_R (1);
the specific process of the fifth step is as follows:
step five, initializing the iteration times r=1 of a receiving end;
step five, starting from the first bit of data_R (R), divide data_R (R) into 2 r Group data, each group data having a length of 2 N-r *L；
Processing each group of Data respectively, and representing the processing result corresponding to each group of Data as one path of serial Data and recording the serial Data as Data data_R (r+1);
in the fifth step, each group of data is processed respectively, and the specific process of the processing is as follows:
for any set of data:
wherein x is 1 F for processing the set of data 1 (t) represents the set of data, f 1 (-t) represents f 1 (t) results obtained by data inversion, F 1 (t) represents the result of Fourier transform of the group of data, F 1 (-t) represents F 1 (t) as a result of data inversion,is a transform coefficient;
the processing mode of other groups of data is the same;
the transform coefficientsThe method comprises the following steps:
step five, enabling r to be increased by 1, and repeating the process of the step five;
stopping iteration until r=n, obtaining Data data_r (N) obtained in the last iteration, extracting the former kL bit Data of the Data data_r (N), and taking the extracted Data as an output signal.
2. The multi-component spreading-based high-order frequency domain computation diversity method of claim 1, wherein said transform order N is determined according to a length of a total spreading resource, 2 N * L is the length of the total extended resource.
3. The high-order frequency domain computation diversity method based on multi-component extension according to claim 2, wherein the specific process of sequentially performing equalization and FFT transformation on the received signal is:
wherein Y is a signal received by a receiving end, G is an equalization matrix,for the equalized signal, X is the signal transmitted by the transmitting end through the antenna, H is the channel state information matrix, Z is zero-mean additiveWhite gaussian noise.
4. A multi-component spread based high order frequency domain computation diversity method according to claim 3, wherein the eigenvalue θ l The relation of (2) is:
wherein θ l ∈(0,2π]，l＝0,1,2,3。
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