CN113194054A - Non-orthogonal multi-carrier modulation method based on compressed coding code stream characteristics - Google Patents
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Abstract
The invention discloses a non-orthogonal multi-carrier modulation method based on the characteristics of a compression coding code stream, which comprises the following steps: in the frequency spectrum of the compressed bit stream image, the frequency characteristic ratio is equal to the ratio of the total amplitude of the high-frequency component to the total amplitude of the low-frequency component; expanding the subcarriers with different frequencies to different degrees according to the frequency characteristics of the bit stream image, performing corresponding shift on a time domain, and performing zero filling on other positions to generate a multicarrier modulation matrix with non-uniform non-orthogonal characteristics; regarding the compressed bit stream of 0-1 as a new image type, designing a modulation matrix according to the frequency characteristics of the compressed bit stream image, carrying out constellation mapping modulation on the compressed bit stream, modulating by a non-uniform non-orthogonal multi-carrier modulation matrix, and finally sending to a channel; at the receiving end, the received signal is sequentially subjected to analog-to-digital conversion and serial-to-parallel conversion, a demodulation process is implemented, and demodulated symbols are restored into compressed bit streams through constellation demapping.
Description
Technical Field
The invention relates to the field of non-orthogonal multi-carriers, in particular to a non-orthogonal multi-carrier modulation method (F-NNMC) based on the characteristics of compressed code streams, based on the frequency characteristics of image compressed data code streams.
Background
In wireless image transmission, the requirements on data transmission efficiency and received image quality are higher and higher, and the huge data volume of images and precious bandwidth resources are in conflict, so that higher spectral efficiency needs to be achieved on the premise of ensuring the image quality of a receiving end.
The main difficulties of wireless image transmission are that the image data volume is large, the channel is complex, the bandwidth is limited and the interference is serious, so that the effective image compression algorithm and the bandwidth efficient modulation are key technologies for meeting the sonar image transmission requirements. The essence of image compression is to remove redundant information in an image, reducing the size of the transmitted data, while maintaining an acceptable visual quality of the image. To cope with the limitation of bandwidth, multicarrier modulation is generally adopted. Multicarrier modulation may be classified into orthogonal modulation and non-orthogonal modulation.
For Orthogonal multi-carrier modulation, Orthogonal Frequency Division Multiplexing (OFDM) is the most widely used multi-carrier modulation scheme due to its strong anti-multipath interference capability. However, it requires strict synchronization and there is a high Peak-to-Average Power Ratio (PAPR). Orthogonal Wavelength Division Multiplexing (OWDM) was developed as an alternative to OFDM, and although OWDM reduces the peak-to-average power ratio compared to OFDM, its spectral efficiency is not sufficient to transmit images of large data volumes. In recent years, Filter Bank Multicarrier (FBMC) and Generalized Frequency Division Multiplexing (GFDM) have been proposed, and the use of an additional Filter improves the spectral efficiency, but results in high hardware complexity.
For non-orthogonal multi-carrier modulation, Spectrum Efficient Frequency Division Multiplexing (SEFDM) introduces non-orthogonal overlapping sub-carriers within a given bandwidth to improve Spectral efficiency. The Sparse Non-orthogonal Frequency Division Multiplexing (SN-OFDM) and the Sparse Non-orthogonal Wavelet Division Multiplexing (SN-OWDM) apply the Sparse representation principle to the Non-orthogonal modulation process, and improve the spectrum efficiency.
However, the above studies only focus on the transmission efficiency in terms of data size and transmission bandwidth, and the source compression and modulation are studied separately.
Disclosure of Invention
The invention provides a non-orthogonal multi-carrier modulation method based on the characteristics of a compression coding code stream, which improves the data transmission rate and simultaneously reduces the transmission error rate, solves the problems of large data volume, low frequency spectrum efficiency and poor received image quality in wireless image transmission to a certain extent, and ensures the high efficiency and reliability of transmission, as detailed in the following description:
a non-orthogonal multi-carrier modulation method based on compressed coding code stream characteristics combines multi-carrier modulation with characteristics of compressed image data, and comprises the following steps:
in the frequency spectrum of the compressed bit stream image, the frequency characteristic ratio is equal to the ratio of the total amplitude of the high-frequency component to the total amplitude of the low-frequency component;
expanding the subcarriers with different frequencies to different degrees according to the frequency characteristics of the bit stream image, performing corresponding shift on a time domain, and performing zero filling on other positions to generate a multicarrier modulation matrix with non-uniform non-orthogonal characteristics;
regarding the compressed bit stream of 0-1 as a new image type, designing a modulation matrix according to the frequency characteristics of the compressed bit stream image, carrying out constellation mapping modulation on the compressed bit stream, modulating by a non-uniform non-orthogonal multi-carrier modulation matrix, and finally sending to a channel;
at the receiving end, the received signals are sequentially subjected to analog-to-digital conversion and serial-to-parallel conversion, the demodulation process is implemented, demodulated symbols are restored into compressed bit streams through constellation demapping, and finally the original images are restored through decompression of a decoder.
The expanded sub-carriers are part of the original orthogonal base, and the orthogonal sub-carriers of the same frequency are subjected to multiplexing translation for multiple times to generate non-orthogonal sub-carriers.
Further, the method generates a new multi-carrier modulation matrix through multiplexing translation, and the new multi-carrier modulation matrix has the characteristic of non-uniform non-orthogonality.
The technical scheme provided by the invention has the beneficial effects that:
1. the method is applied to wireless image transmission, so that the efficiency and the reliability of image transmission are improved; the non-orthogonality among the sub-carriers improves the frequency spectrum efficiency, and the non-uniform sub-carrier structure can bear more effective information of transmission data, thereby improving the reliability;
2. the invention firstly proposes the idea of combining the multi-carrier modulation scheme with the transmission data characteristic, regards the compressed bit stream of the image as a novel image, and generates a new subcarrier structure on the basis of carrying out spectrum analysis on the compressed bit stream; because compressed bit stream images of different image compression modes have similar frequency characteristics, the proposed F-NNMC modulation scheme can adapt to different image compression algorithms;
3. the novel subcarrier designed by the invention is a part of the original orthogonal base, and the data transmission is carried out on the non-orthogonal subcarrier generated by multiplexing and translating the same orthogonal subcarrier for multiple times, so that the frequency resource is saved, and the high spectrum efficiency of wireless image transmission is ensured;
4. the invention uses the multi-carrier modulation method, improves the peak signal-to-noise ratio (PSNR) and the Structural Similarity (SSIM) of the image at the receiving end, and ensures the high quality of the received image;
5. compared with the existing modulation scheme, the proposed F-NNMC scheme realizes lower Bit Error Rate (BER) with less spectrum resources, and the received image has higher peak signal-to-noise ratio (PSNR) and Structural Similarity (SSIM).
Drawings
FIG. 1 is a test image and a corresponding compressed bitstream image;
wherein, (a) is a side scan sonar chart; (b) the side-scan sonar image is obtained through JPEG compression; (c) for side-scan sonar images, SPIHT compresses.
FIG. 2 is a graph of a filtered spectrum of a compressed bitstream image;
wherein, (a) is a side scan sonar image, JPEG compressed, r 2.74; (b) for a side scan sonar image, SPIHT compresses, r 2.72.
FIG. 3 is a diagram illustrating generation of non-uniform non-orthogonal multi-carriers based on orthogonal bases;
wherein (a) is an orthogonal group; (b) non-uniform non-orthogonal multi-carriers.
FIG. 4 is a block diagram of an F-NNMC multi-carrier modulation system;
FIG. 5 is a schematic diagram of F-NNMC performance under different orthogonal bases;
wherein, (a) is a PSNR performance diagram; (b) is a SSIM performance diagram; (c) a BER performance diagram is shown.
FIG. 6 is a graphical illustration of a comparison of the performance of F-NNMC with existing modulation schemes;
wherein, (a) is a PSNR performance comparison diagram; (b) the SSIM performance is compared with a schematic diagram; (c) a comparison of BER performance is shown.
Fig. 7 is a comparison diagram of transmission effects of compressed images with different modulation schemes.
Wherein, (a) is an original image; (b) for the OFDM transmission effect diagram, PSNR is 15.5173, SSIM is 0.0462; (c) the OWDM transmission effect graph is formed by the steps of (1) carrying out transmission effect mapping, wherein PSNR is 17.9306, and SSIM is 0.1414; (d) the SN-OWDM transmission effect graph is formed, wherein PSNR is 21.6519, SSIM is 0.3501; (e) the F-NNMC transmission effect diagram is shown, PSNR is 36.7511, and SSIM is 0.9176.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention are described in further detail below.
The embodiment of the invention firstly proposes the combination of the Modulation and the Characteristic of transmitting Compressed Data, the Compressed Data of the Image is regarded as a novel Image with unique Frequency Characteristic, and Based on the spectrum analysis result of the Compressed Image Data, a Non-uniform Non-orthogonal Multicarrier Modulation technology (Non-uniform Non-orthogonal Multicarrier Modulation Based on radio Frequency communication of Compressed Image Data) is proposed for solving the problem that the high efficiency and the reliability can not be considered at the same time when the wireless Image is transmitted, and the Image transmission performance is improved. In the multi-carrier modulation method, new subcarriers are only a part of the original orthogonal base, and the orthogonal subcarriers with the same frequency are subjected to multiplexing translation for multiple times to generate non-orthogonal subcarriers so as to reduce the used subcarrier frequency and transmit more data in the same bandwidth; the non-uniform subcarrier structure enables modulation to carry more useful information for transmitting data.
In the past studies in which image compression and modulation were separately studied, the embodiment of the present invention for the first time combines a modulation technique with the characteristics of compressed image data to improve transmission performance. In order to meet the requirements of image transmission on high efficiency and reliability, the embodiment of the invention provides a non-uniform non-orthogonal multi-carrier modulation scheme (F-NNMC) based on the frequency characteristics of compressed image data. The compressed data of the image is considered as a novel image with unique frequency characteristics, and a spectrum analysis of the image is used for performing certain multiplexing translation on a traditional orthogonal transformation base such as Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Discrete Wavelet Transform (DWT) to generate a new modulation transformation matrix with non-uniform and non-orthogonal characteristics. Compared with the prior art, the non-uniform subcarrier structure can better bear the effective information of compressed image data and reduce the transmission Bit Error Rate (BER), thereby effectively reducing the distortion of decompressed images and improving the PSNR and SSIM of received images; the non-orthogonal characteristic can repeatedly utilize the same subcarrier frequency to carry out data transmission, thereby saving frequency resources and obviously improving the utilization rate of frequency spectrum.
Frequency characteristics of image compressed data
(1) Compressing bitstream images
Image compression is a necessary step for transmitting large data volumes of sonar images within a limited bandwidth by reducing redundancy and the degree of correlation of the image data. Since the compressed bit stream of sonar images is a new image type, the unique frequency characteristics of this type of image are studied under different compression algorithms.
The embodiment of the invention selects two popular compression algorithms JPEG and SPIHT for explanation. Fig. 1 is a test image and its corresponding compressed bitstream image. The size of the test image is 128 × 128.
(2) Spectral analysis
Fourier transform is an important image processing tool and is widely used for image spectrum analysis. The output represents the frequency spectrum of the frequency domain, while the input is an image of the spatial domain. For an image of size m × n, the two-dimensional DFT is given by the following equation.
Wherein f (x, y) represents a spatial domain image, and the index term is a basis function corresponding to each point in the frequency domain. The equation can be understood as that the values of the points F (u, v) in the frequency domain can be obtained by multiplying the spatial image by the corresponding basis functions and then adding the results. Power spectrum F2The larger the amplitude of (u, v) is, the more corresponding frequencies u, v are contained in the image. u, v are sine and cosine frequency components in the frequency domain; and m and n are dimension parameters of the image.
The low frequency components in the spectrum correspond to the contours of the image and the high frequency components correspond to the details of the image. The compressed bit stream image has a sharp pixel value change and a distinct high frequency characteristic, and the frequency characteristic thereof can be analyzed by fourier transform. The butterworth low pass filter is selected to separate the high and low frequency components to obtain a ratio of the high and low frequency components of the image. The filter function of a second order butterworth low pass filter can be expressed as follows:
wherein, F0Representing the filter radius, σ is the pixel variance of the compressed bitstream image, with an image size of m × n, and the filter spectrum of the compressed bitstream image is obtained using a butterworth filter, as shown in fig. 2.
According to the principle of Fourier transform of an image, in the power spectrum of a compressed bit stream image, a frequency characteristic ratio r is approximately equal to the total amplitude A of high-frequency componentsHWith the total amplitude A of the low frequency componentLThe ratio of. It is defined as follows:
the values of (a) and (b) in fig. 2 are 2.74 and 2.72, respectively, which shows that bitstream images generated by different compression algorithms have similar frequency characteristics.
Generation of two, non-uniform non-orthogonal subcarriers
Fig. 3 is a process for generating non-uniform non-orthogonal multi-carriers, which is based on orthogonal basis DFT, DCT or DWT, and spreads subcarriers of different frequencies in a bitstream image to different extents according to a result of spectrum analysis of the bitstream image, and performs corresponding shifts in a time domain, and performs zero padding at other positions to generate a transform basis with non-uniform non-orthogonal characteristics.
Three, F-NNMC multi-carrier modulation system
(1) Transmission procedure
In the F-NNMC system, the pixel values of the transmission image range from 0 to 255, and are encoded by a compression algorithm. The obtained 0-1 compressed bit stream can be regarded as a new image type, and the modulation matrix is designed according to the frequency characteristics of the compressed bit stream image. Then, constellation mapping modulation is carried out on the compressed bit stream, QAM signals are output, parallel signals X are obtained after serial-parallel conversion, modulation is carried out by the proposed non-uniform non-orthogonal multi-carrier matrix, cyclic prefix is added to the modulation signals S, and the output data are subjected to digital-to-analog conversion after parallel-serial conversion and are finally sent to a channel.
(2) Receiving process
At the receiving end, firstly, the received signal is sequentially subjected to analog-to-digital conversion and serial-to-parallel conversion, then the demodulation process is carried out, and the symbol after F-NNMC demodulation is carried out
And the compressed bit stream is restored through constellation demapping. And finally, decompressing through a corresponding decoder, converting the received compressed bit stream into pixel values in the range of 0-255, and restoring the original image.
Fourth, image quality evaluation index
Both peak signal-to-noise ratio and structural similarity are objective criteria for evaluating image quality.
(1) Peak signal-to-noise ratio (PSNR)
The peak signal-to-noise ratio only concerns the pixel value difference of the image and cannot represent the sensory quality, and the larger the value, the better.
(2) Structural Similarity (SSIM)
The structural similarity is based on three relatively independent subjective measures of brightness, contrast and structure, the structural similarity between images is measured, the value is 0-1, and the larger the value is, the better the value is. SSIM is more consistent with the judgment of human eye on image quality than PSNR.
FIG. 5 is a graph of F-NNMC performance for different orthogonal bases. (a) And (b) and (c) respectively show graphs of signal-to-noise ratio and peak signal-to-noise ratio, structural similarity and transmission error rate. Wherein r represents a frequency characteristic ratio, and the value of r influences the number distribution of high-frequency and low-frequency subcarriers in the modulation system.
FIG. 6 shows the performance of F-NNMC versus existing modulation schemes, with compression algorithms selecting JPEG and SPIHT for wide application. Fig. 7 shows a comparison of the transmission effect of different modulation schemes on compressed images. As can be seen from the above illustration, the F-NNMC modulation scheme provided by the present invention has excellent transmission performance, can meet the requirements of wireless image transmission on high efficiency and reliability, and has a wider application prospect compared with the existing modulation scheme.
The result shows that compared with the existing scheme, the F-NNMC modulation method can improve the Peak Signal-to-Noise Ratio (PSNR) and the Structural Similarity (SSIM) of the image at the receiving end, and effectively reduce the transmission Error Rate (Bit Error Rate, BER), thereby improving the spectral efficiency on the premise of ensuring the image quality.
In the embodiment of the present invention, except for the specific description of the model of each device, the model of other devices is not limited, as long as the device can perform the above functions.
Those skilled in the art will appreciate that the drawings are only schematic illustrations of preferred embodiments, and the above-described embodiments of the present invention are merely provided for description and do not represent the merits of the embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (3)
1. A non-orthogonal multi-carrier modulation method based on compressed coding code stream characteristics is characterized in that the method combines multi-carrier modulation with characteristics of compressed image data, and comprises the following steps:
in the frequency spectrum of the compressed bit stream image, the frequency characteristic ratio is equal to the ratio of the total amplitude of the high-frequency component to the total amplitude of the low-frequency component;
expanding the subcarriers with different frequencies to different degrees according to the frequency characteristics of the bit stream image, performing corresponding shift on a time domain, and performing zero filling on other positions to generate a multicarrier modulation matrix with non-uniform non-orthogonal characteristics;
regarding the compressed bit stream of 0-1 as a new image type, designing a modulation matrix according to the frequency characteristics of the compressed bit stream image, carrying out constellation mapping modulation on the compressed bit stream, modulating by a non-uniform non-orthogonal multi-carrier modulation matrix, and finally sending to a channel;
at the receiving end, the received signals are sequentially subjected to analog-to-digital conversion and serial-to-parallel conversion, the demodulation process is implemented, demodulated symbols are restored into compressed bit streams through constellation demapping, and finally the original images are restored through decompression of a decoder.
2. The method according to claim 1, wherein the expanded sub-carriers are part of an original orthogonal basis, and the non-orthogonal sub-carriers are generated by performing multiplexing translation on orthogonal sub-carriers of the same frequency for multiple times.
3. The method according to claim 1, wherein the method generates a new multi-carrier modulation matrix by multiplexing shift, and the new multi-carrier modulation matrix has non-uniform non-orthogonal characteristics.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130039397A1 (en) * | 2010-03-08 | 2013-02-14 | Sony Corporation | Communications system using adaptive orthogonal frequency division multiplexing |
| CN103647740A (en) * | 2013-11-25 | 2014-03-19 | 北京航空航天大学 | Multi-carrier modulation and demodulation method of orthogonal non-uniform multi-carrier spacing based on Ramanujan summation |
| CN106789809A (en) * | 2016-12-02 | 2017-05-31 | 天津大学 | A kind of non-orthogonal multi-carrier transmission method |
| CN108768913A (en) * | 2018-06-07 | 2018-11-06 | 天津大学 | A kind of non-orthogonal multi-carrier modulator approach improving image transmitting performance |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130039397A1 (en) * | 2010-03-08 | 2013-02-14 | Sony Corporation | Communications system using adaptive orthogonal frequency division multiplexing |
| CN103647740A (en) * | 2013-11-25 | 2014-03-19 | 北京航空航天大学 | Multi-carrier modulation and demodulation method of orthogonal non-uniform multi-carrier spacing based on Ramanujan summation |
| CN106789809A (en) * | 2016-12-02 | 2017-05-31 | 天津大学 | A kind of non-orthogonal multi-carrier transmission method |
| CN108768913A (en) * | 2018-06-07 | 2018-11-06 | 天津大学 | A kind of non-orthogonal multi-carrier modulator approach improving image transmitting performance |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113691480A (en) * | 2021-08-25 | 2021-11-23 | 哈尔滨工业大学 | Multi-carrier sending method and receiving method based on multi-layer orthogonal modulation |
| CN113691480B (en) * | 2021-08-25 | 2024-03-19 | 哈尔滨工业大学 | Multi-carrier transmitting method and receiving method based on multi-layer orthogonal modulation |
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