Optical signal receiver and optical signal receiving method

Abstract

Provided are an optical signal receiver and an optical signal receiving method for simplifying a configuration necessary for signal detection. An optical signal receiver is provided with: a sampling signal generation unit (11) that generates a sampling signal comprising optical signals having a plurality of wavelengths in a prescribed pattern; a sampling processing unit (13) that generates a plurality of optical signals by sampling the sampling signal; and a signal aggregation unit (14) that generates a plurality of aggregated optical signals by aggregating, for the plurality of optical signals, the optical signals having the plurality of wavelengths in accordance with the prescribed pattern of the plurality of wavelengths included in the sampling signal.

Description

Optical signal receiver and optical signal receiving method

[0001] The present invention relates to an optical signal receiver and an optical signal receiving method.

[0002] With increasing communication speeds, optical signals are being used instead of electrical signals for transmitting and receiving signals. In optical signal transmission and reception, the transmitter generates an optical signal by sampling an optical sampling signal according to the transmitted signal, and the receiver detects the transmitted signal by digitally converting the received optical signal according to the sampling period.

[0003] As communication speeds have increased in recent years, sampling frequencies have also risen. This makes it difficult for a single A / D converter in the receiver to perform digital conversion processing. Therefore, signal parallelization technology, which processes optical signals of multiple wavelengths in parallel, is being used. In signal parallelization technology, the receiver performs digital conversion processing according to the optical signals of each wavelength acquired by spectral analysis. This requires multiple A / D converters in the receiver, which tends to make the configuration complex.

[0004] In recent years, in order to suppress the increase in the number of AD converters in receivers, the use of linear multivariate analysis methods such as sparse principal component analysis has been considered (Patent Document 1). In the technology disclosed in Patent Document 1, multiple first spectral data and third spectral data are generated by performing nonlinear transformation and spectroscopy on a plurality of predetermined first optical signals used in the analysis phase and a third optical signal detected in the detection phase. In the analysis phase, multiple second spectral data are generated by selecting the spectrum of the principal component in each of the first spectral data by performing sparse principal component analysis on the plurality of first spectral data. In the detection phase, the intensity of the spectrum of the principal component among the third spectral data is measured (compressed sensing), and the third optical signal is detected by comparing the pattern between the principal component spectrum of the third spectral data and the plurality of second spectral data. According to the technology of Patent Document 1, the characteristics of the optical signal containing a nonlinear structure are mapped to spectral space (i.e., a higher-dimensional space) by nonlinear transformation, and the efficiency of sparse principal component analysis is improved by utilizing the mapped nonlinear structure. As a result, in compressed sensing, it is sufficient to measure only the principal component spectrum instead of the entire spectrum, allowing for the detection of the transmitted signal with a relatively simple configuration without the need for an ultrafast time gate or reference light source.

[0005] International Publication No. 2021 / 261476

[0006] The technology disclosed in Patent Document 1 allows for the detection of signals by sparse principal component analysis and compressed sensing by using a nonlinear converter in the receiver to map the characteristics of the nonlinear structure contained in the optical signal onto the spectral space. With sparse principal component analysis and compressed sensing, the receiver only needs to detect the spectral intensity corresponding to the selected principal component, thus enabling the detection of the transmitted signal with a relatively simple configuration. Thus, since sparse principal component analysis and compressed sensing are useful technologies for simplifying the configuration of optical signal receivers, research is also being conducted on technologies that improve the utilization efficiency of sparse principal component analysis and compressed sensing using methods different from nonlinear conversion, thereby simplifying the receiver configuration.

[0007] This invention has been made in view of these problems, and aims to provide an optical signal receiver and an optical signal receiving method that simplify the configuration necessary for signal detection.

[0008] The optical signal receiver of the present invention comprises: a sampling signal generation unit that generates a sampling signal including multiple optical signals of a predetermined pattern; a sampling processing unit that generates multiple optical signals by sampling the sampling signal; and a signal aggregation unit that generates multiple aggregated optical signals by aggregating multiple optical signals in each of the multiple optical signals according to a predetermined pattern of multiple wavelengths of the sampling signal.

[0009] The optical signal receiving method of the present invention includes generating a sampling signal that includes optical signals of multiple wavelengths in a predetermined pattern; generating multiple optical signals by sampling the sampling signal; and generating multiple aggregated optical signals in each of the multiple optical signals by aggregating light of multiple wavelengths according to a predetermined pattern of multiple wavelengths of the sampling signal.

[0010] According to the optical signal receiver and optical signal receiving method of the present invention, upon receiving a transmission signal, multiple optical signals are obtained by sampling a sampling signal containing multiple wavelengths of optical signals in a predetermined pattern according to the transmission signal. Then, a combined optical signal is generated by aggregating light of multiple wavelengths according to a predetermined pattern of multiple wavelengths present in the sampling signal, and the transmission signal is detected from the combined optical signal. Although the transmission signal is distributed at the period of the sampling signal by sampling, the combined optical signal, which aggregates light of multiple wavelengths, has a lower sampling frequency than the optical signal before aggregation. Therefore, the sampling frequency at the time of detection of the transmission signal can be lowered, which reduces the number of AD converters required for analysis of the combined optical signal for signal detection and simplifies the configuration.

[0011] Furthermore, because optical signals possess coherence, aggregating optical signals of multiple wavelengths results in the emergence of characteristics different from those of the original optical signals (for example, changes in intensity at specific wavelengths), thus achieving a higher dimensionality in the signal space of the optical signal. As a result, by utilizing sparse principal component analysis, a statistical analysis method, specific principal components can be selected from the higher-dimensional optical signal, and the signal space is dimensionally compressed by sparse compression, which reduces the number of dimensions of the data. Then, based on the measured values ​​of the principal components obtained by compressed sensing, it becomes possible to detect the transmitted signal. In this way, even when optical signals of multiple wavelengths are aggregated, the characteristics that emerge after the aggregation of the optical signals due to coherence allow for the detection of the transmitted signal from the aggregated optical signal using sparse principal component analysis and compressed sensing.

[0012] This is a block diagram showing the functional configuration of an optical signal receiver according to the first embodiment. This diagram illustrates sparse principal component analysis. This is a block diagram showing the functional configuration of an optical signal aggregater. This diagram illustrates the function of an optical signal aggregater. This diagram shows the case where multiple optical signals are aggregated using the coherence of optical signals. This is a flowchart showing the processing of the analysis phase. This is a flowchart showing the processing of the detection phase. This is a block diagram showing the functional configuration of an optical signal receiver according to the second embodiment. This is a flowchart showing the processing of the analysis phase. This is a flowchart showing the processing of the detection phase.

[0013] Embodiments of the present invention will be described in detail below with reference to the drawings. In the following description, the same reference numerals are used for identical components, and redundant descriptions are omitted.

[0014] (First Embodiment) Figure 1 is a block diagram showing the functional configuration of an optical signal receiver 100 according to the first embodiment. The optical signal receiver 100 is configured to detect the input transmission signal by sparse principal component analysis using an analysis signal of a predetermined pattern. The signal received by the optical signal receiver 100 may be a high-frequency analog signal other than an optical signal.

[0015] The optical signal receiver 100 includes an optical signal aggregater 10 and an optical signal detector 20. The optical signal receiver 100 performs different processes in an analysis phase utilizing sparse principal component analysis and a detection phase in which it detects a transmitted signal using the analysis results.

[0016] In the analysis phase, the optical signal aggregater 10 generates multiple first aggregated optical signals corresponding to multiple analytical signals used in sparse principal component analysis. In the detection phase following the analysis phase, the optical signal aggregater 10 generates a second aggregated optical signal corresponding to the input transmission signal. The first aggregated optical signal and the second aggregated optical signal are signals in which optical signals from multiple time slots are aggregated into a single time slot.

[0017] The optical signal detector 20 includes a spectrometer 21 and a calculator 22. The spectrometer 21 generates a plurality of first spectral data and a plurality of second spectral data from a plurality of input first aggregated optical signals and second aggregated optical signals during the analysis phase and the detection phase. The calculator 22 includes an analysis unit 221 that performs sparse principal component analysis during the analysis phase and a detection unit 222 that detects the transmission signal using the analysis results of the sparse principal component analysis during the detection phase.

[0018] In the analysis phase, the analysis unit 221 performs sparse principal component analysis on multiple first spectral data to select the principal component spectra from the entire spectrum as an analysis result, and obtains multiple analysis spectral data corresponding to the selected principal component spectra. Based on the analysis spectral data from the analysis unit 221, the detection unit 222 performs compressed sensing by measuring only the principal component spectra selected by sparse principal component analysis from the second spectral data, and detects the transmission signal by comparing the measured values ​​of the compressed sensing with the multiple analysis spectral data to output the detection result. The detection performed by the arithmetic unit 22 means detecting the optical characteristics of the second optical signal before aggregation (e.g., time waveform, intensity, amplitude and phase, or any combination thereof), and / or detecting the transmission signal corresponding to the characteristics.

[0019] As the arithmetic unit 22, for example, a computer having a processor and memory can be used. In this case, the computer can function as the arithmetic unit 22 when the instructions or software program stored in memory is executed by the processor. Alternatively, a dedicated electronic circuit or the like may be used as the arithmetic unit 22.

[0020] Here, sparse principal component analysis (SPC) is a statistical analysis technique that reduces the dimensionality of data by introducing a sparse structure into the input variables. In SPC, linear combinations containing only a few input variables can be used as principal components. This type of sparse principal component analysis will be explained using Figure 2.

[0021] Figure 2 illustrates sparse principal component analysis using frequency components. In Figure 2, each line graph represents a single spectral data obtained by spectroscopy from a single optical signal. In each line graph, the horizontal axis represents wavelength, and the vertical axis represents power value.

[0022] Figure 2(a) shows multiple first spectral data corresponding to multiple analytical signals. Each of the multiple first spectral data represents the spectrum of a multiple first optical signal corresponding to a multiple analytical signal. Here, each of the multiple first spectral data has 1024 frequency components. That is, each of the multiple first spectral data contains 1024 data points, each consisting of a combination of power value and frequency. In this case, the frequencies of the 1024 data points are common to all of the multiple first spectral data.

[0023] Figure 2(b) shows multiple analytical spectral data generated during the detection phase. These multiple analytical spectral data are generated by selecting specific principal component spectra from all spectra of multiple first spectral data using sparse principal component analysis. Since the multiple analytical spectral data can represent the differences between the spectra of multiple first optical signals with fewer frequency components than the multiple first spectral data, it is possible to distinguish between multiple first optical signals. Here, it is assumed that each of the multiple analytical spectral data has nine frequency components as principal component spectra. That is, each of the multiple analytical spectral data contains nine data points, each consisting of a combination of power value and frequency. In this case, the frequencies of the nine data points are common to all of the multiple analytical spectral data.

[0024] Therefore, in the analysis phase, compressed sensing is performed to measure the intensity of the principal component spectrum selected in the detection phase for the second spectral data corresponding to the transmitted signal, and the principal component spectrum of the second spectral data is obtained. Then, the pattern is compared between the principal component spectrum of the second spectral data and the multiple analytical spectral data, and the transmitted signal is detected based on the comparison result. In other words, in the detection phase, the similarity or dissimilarity between the second spectral data and the multiple analytical spectral data is evaluated, and the transmitted signal is detected based on the evaluation result.

[0025] In detail, the analysis unit 221 performs sparse principal component analysis on multiple first spectral data to select principal component spectra from all spectra and generates multiple analytical spectral data having fewer frequency components than the multiple first spectral data. The number of frequency components in each of the multiple analytical spectral data is less than the number of frequency components in each of the multiple first spectral data. For example, the analysis unit 221 performs sparse principal component analysis on multiple first spectral data, each consisting of N (where N is a natural number greater than or equal to 2) frequency components, to generate multiple analytical spectral data, each consisting of M (a natural number less than N) frequency components. Each of the generated multiple analytical spectral data is stored in memory in association with the characteristics of the corresponding first optical signal (e.g., time waveform, intensity, amplitude, and phase, or any combination thereof).

[0026] The detection unit 222 compares the patterns between the second spectral data and the multiple analyzed spectral data, and detects the transmission signal based on the comparison result. In other words, the detection unit 222 evaluates the similarity or dissimilarity between the second spectral data and the multiple analyzed spectral data, and detects the transmission signal based on the evaluation result.

[0027] For example, the detection unit 222 performs compressed sensing to measure the intensity of the principal component spectrum selected in the detection phase for the second spectral data, and searches for analytical spectral data similar to the second spectral data by comparing the patterns of the principal component spectrum of the second spectral data with multiple analytical spectral data. Then, the detection unit 222 detects the transmission signal based on the analytical signal corresponding to the searched analytical spectral data.

[0028] Alternatively, for example, the detection unit 222 may determine whether or not there is an analysis spectrum data similar to the second spectrum data among the multiple analysis spectrum data by comparing the pattern between the principal component spectrum of the second spectrum data obtained by compressed sensing and the multiple analysis spectrum data. The detection unit 222 may then detect the transmission signal based on the determination result.

[0029] For comparing the principal component spectrum of such second spectral data with the analytical spectral data, for example, the sum of absolute differences (SAD) of frequency components between the principal component spectrum of the second spectral data and the analytical spectral data can be used. In this case, the detection unit 222 can search for the analytical spectral data with the smallest SAD among the multiple analytical spectral data as the analytical spectral data most similar to the principal component spectrum of the second spectral data. Furthermore, if the multiple analytical spectral data do not contain any analytical spectral data with an SAD smaller than a predetermined threshold, the detection unit 222 can determine that there is no analytical spectral data similar to the principal component spectrum of the second spectral data.

[0030] The method for comparing analytical spectral data is not limited to this. For example, instead of SAD, the reciprocal of SAD (multiplicative inverse), the sum of squared differences (SSD), or the reciprocal of SSD may be used.

[0031] Next, the configuration and processing of the optical signal aggregater 10 will be explained using Figures 3 and 4. Figure 3 is a block diagram showing the functional configuration of the optical signal aggregater 10. Figure 4 is a diagram illustrating the processing within the optical signal aggregater 10.

[0032] As shown in Figure 3, the optical signal aggregater 10 comprises a sampling signal generation unit 11, an analysis signal generation unit 12, a sampling processing unit 13, and a signal aggregation unit 14. The sampling processing unit 13 also receives a transmission signal from outside the optical signal aggregater 10 (optical signal receiver 100). The input transmission signal is an optical signal, which is an analog signal of harmonics.

[0033] In both the analysis and detection phases, the sampling signal generation unit 11 generates a sampling signal in which pulsed light of multiple wavelengths (four in this embodiment) (for example, red, yellow, green, and violet pulsed light) are repeated in a time series. The generated sampling signal is output to the sampling processing unit 13. As shown in Figure 4(a), the sampling signal is composed of repeated pulsed light of four different wavelengths, indicated by different hatching.

[0034] In the analysis phase, the analytical signal generation unit 12 generates an analytical signal (first signal) that corresponds to the first spectral data used in the analysis phase in which sparse principal component analysis is performed.

[0035] In the analysis phase, the sampling processing unit 13 performs sampling on the sampling signal generated by the sampling signal generation unit 11 in accordance with the analysis signal (first signal) generated by the analysis signal generation unit 12, thereby generating a first optical signal. In the detection phase, the sampling processing unit 13 performs sampling on the sampling signal in accordance with the transmission signal (second signal) received by the optical signal aggregater 10, thereby generating a second optical signal.

[0036] The right side of Figure 4 shows the analysis signal and transmission signal used for the sampling process. As shown in Figure 4(b), the sampling processing unit 13 generates a first optical signal whose intensity changes according to the analysis signal during the analysis phase. During the detection phase, the sampling processing unit 13 generates a second optical signal whose intensity changes according to the transmission signal. In the illustrated example, the intensity of each pulse of the sampling signal is modulated, but this is not the only example. The sampling processing unit 13 may perform sampling according to any characteristic of the optical signal (e.g., time waveform, amplitude, phase, or any combination thereof), not just intensity.

[0037] The signal aggregation unit 14 generates a first aggregated optical signal and a second aggregated optical signal by aggregating multiple pulsed light signals of different wavelengths that exist across multiple time slots into a single time slot, based on the first optical signal and the second optical signal generated by the sampling processing unit 13.

[0038] As shown in (c) of FIG. 4, an aggregation process is performed in which four pulsed lights of different wavelengths are aggregated into one time slot at the head of those pulsed lights. In the analysis phase, an aggregation process is performed on a plurality of first optical signals to generate a plurality of first aggregated optical signals. In the detection phase, an aggregation process is performed on the second optical signal to generate a second aggregated optical signal. When pulsed lights of different wavelengths are repeated in different patterns in the sampling signal, the aggregation process is executed so that the signals of the pulsed lights of each wavelength are included one by one according to the repeating pattern. Hereinafter, using FIG. 5, the reason why signal detection by sparse principal component analysis and compressive sensing becomes possible by such an aggregation process will be described.

[0039] FIG. 5 is a diagram for explaining the outline of the aggregation process. Common to (a) to (c) of FIG. 5, the horizontal axis indicates the wavelength and the vertical axis indicates the intensity. As shown in (a) of FIG. 5, the pulsed lights of four types of wavelengths have the waveform of a sinc function that peaks at a specific wavelength λ Ａ ~λ Ｄ . Then, as shown in (b) of FIG. 5, when the pulsed lights of the sinc functions with different peak wavelengths λ Ａ ~λ Ｄ overlap, due to the coherence (interferability) of the pulsed lights, that is, the property of interfering with each other, peaks appear at wavelengths different from the peak wavelengths of the four types of pulsed lights. In the illustrated example, peaks appear at three wavelengths of λ １ ~λ ３ in the aggregated optical signal.

[0040] (c) of FIG. 5 is a diagram showing the waveform of the aggregated optical pulse when the intensities of the four types of optical pulses to be aggregated are different. When pulsed lights having various intensities are aggregated at each wavelength, optical signals having various wavelength patterns are generated. Therefore, in the analysis phase, sparse principal component analysis is executed, that is, λ Ａ ~λ Ｄ which are different from the peak wavelengths of the pulsed lights before aggregation, and λ １ ~λ ３Three wavelengths are selected as the main components, the characteristics of their intensities are captured, and the analysis results are generated in association with the combinations of the intensities of the four types of pulsed light before aggregation. Then, in the detection phase, compressive sensing is performed to measure the intensities of the main components selected by sparse principal component analysis for the signal to be measured, and the transmission signal can be detected by comparing the pattern between the measured values of the intensities of the main components obtained by compressive sensing and the analysis results.

[0041] In this embodiment, the optical signal aggregator 10 includes the signal aggregation unit 14 to realize the high-dimensional conversion of the signal space. As a result, the optical signal detector 20 performs dimensional compression of the signal space by sparse compression, and the transmission signal can be detected by sparse principal component analysis and compressive sensing. When four types of pulsed light are aggregated, signal amplification is possible in 16 patterns due to mutual interference. When N types of pulsed light are aggregated, signal amplification is possible in N squared patterns.

[0042] Thus, the optical signal aggregator 10 generates a plurality of first aggregated optical signals corresponding to a plurality of detection signals and a second aggregated optical signal corresponding to the transmission signal. The plurality of first aggregated optical signals and the second aggregated optical signal are optical signals having different optical characteristics from each other. The plurality of first aggregated optical signals correspond to the analysis signals, and the second aggregated optical signal corresponds to the transmission signal.

[0043] Examples of the optical characteristics can include at least one of a time waveform, intensity, amplitude, and phase. In this case, at least one of the time waveform, intensity, amplitude, and phase of each of the plurality of first aggregated optical signals is different from the time waveform, intensity, amplitude, and phase of other first aggregated optical signals. The second aggregated optical signal is an aggregated optical signal corresponding to the transmission signal to be detected. That is, the characteristics of the second aggregated optical signal (for example, time waveform, intensity, amplitude, and phase, or any combination thereof) are unknown and are detected by the optical signal detector 20.

[0044] Next, the processing of the optical signal receiver 100 will be described with reference to FIGS. 6 and 7. FIG. 6 shows the processing of the optical signal receiver 100 performed in the analysis phase. FIG. 7 shows the processing of the optical signal receiver 100 performed in the detection phase.

[0045] First, the analysis phase will be explained with reference to Figure 6. Figure 6 is a flowchart showing the processing of the analysis phase in the first embodiment. The analysis phase is performed before the detection phase. However, the analysis phase does not need to be performed after each detection phase.

[0046] First, in step S11, the sampling signal generation unit 11 generates a sampling signal consisting of pulsed light of different wavelengths. When the analysis signal generation unit 12 generates multiple analysis signals, the sampling processing unit 13 samples the sampling signal based on the multiple analysis signals and generates multiple first optical signals. Then, the signal aggregation unit 14 generates multiple first aggregated optical signals by performing an aggregation process on each first optical signal to aggregate the pulsed light of multiple time slots into one time slot of the same time. The generated multiple first aggregated optical signals are transmitted to the optical signal detector 20.

[0047] In step S12, the spectrometer 21 spectrally analyzes multiple first aggregated optical signals, thereby acquiring multiple first spectral data. Here, each of the multiple first spectral data contains a relatively large number of frequency components. In other words, the spectrometer 21 is required to measure power values ​​at a relatively large number of frequencies. The acquired multiple first spectral data are transmitted to the arithmetic unit 22.

[0048] In step S13, the analysis unit 221 of the arithmetic unit 22 performs sparse principal component analysis on the multiple first spectral data. As a result, principal component spectra are selected from the entire spectrum, and multiple analytical spectral data are generated, each showing fewer principal component frequency components than the multiple first spectral data.

[0049] In step S14, the detection unit 222 stores the analytical spectral data obtained by sparse principal component analysis.

[0050] Next, the detection phase, which takes place after the analysis phase, will be explained with reference to Figure 7. Figure 7 is a flowchart showing the processing of the detection phase in the first embodiment.

[0051] First, in step S21, the sampling signal generation unit 11 generates a sampling signal in which pulsed light of different wavelengths is repeated in a predetermined pattern. The sampling processing unit 13 samples the sampling signal based on a transmission signal input from an external source and generates a second optical signal. Then, the signal aggregation unit 14 generates a second aggregated optical signal by performing an aggregation process on the second optical signal, which aggregates pulsed light from multiple time slots according to a predetermined pattern into one time slot of the same time. The generated second aggregated optical signal is transmitted to the optical signal detector 20.

[0052] In step S22, the spectrometer 21 spectrally analyzes the second concentrated optical signal, thereby acquiring second spectral data. Here, the second spectral data contains at least the same frequency components as those contained in each of the multiple analytical spectral data. In other words, the spectrometer 21 only needs to measure power values ​​at relatively low frequencies. The acquired second spectral data is transmitted to the arithmetic unit 22.

[0053] In step S23, the detection unit 222 of the arithmetic unit 22 selects and measures the principal component spectra selected in the sparse principal component analysis in step S13 for the entire spectrum of the second spectral data. The detection unit 222 then compares the measured values ​​of the principal component spectra of the second spectral data with the patterns of the multiple analytical spectral data stored in the analysis phase.

[0054] In step S24, the detection unit 222 detects the transmission signal based on the comparison result.

[0055] In step S25, the detection unit 222 outputs the detection result to, for example, a storage device, display, or information terminal. In this way, the analysis spectrum, which is the analysis result obtained in the analysis phase, is used to detect the transmission signal from the second spectral data and obtain the detection result.

[0056] As described above, in the optical signal aggregater 10 of the first embodiment, the signal aggregation unit 14 aggregates pulsed light of multiple wavelengths according to a predetermined pattern of multiple wavelengths of the sampled signal obtained by sampling by the sampling processing unit 13 to generate an aggregated optical signal. Due to this aggregation, the sampling frequency of the aggregated optical signal is lower than that of the optical signal before aggregation. As a result, the sampling frequency required when detecting the transmission signal from the aggregated optical signal can be lowered, and the number of AD converters required for analysis of the aggregated optical signal for signal detection in the receiver can be reduced.

[0057] In detail, the multiple first and second optical signals corresponding to the multiple analysis signals / transmission signals output from the sampling processing unit 13 are distributed to each pulse of the sampling signal. The signal aggregation unit 14 then aggregates each of the multiple first and second optical signals in a predetermined pattern to generate multiple burst-like first aggregated optical signals / second aggregated optical signals. The multiple first aggregated optical signals / second aggregated optical signals generated in this way have a lower sampling frequency than the multiple first and second optical signals. For example, by aggregating four pulses of different wavelengths for each of the sampled first and second optical signals, the sampling frequency can be reduced to one-quarter (the sampling period can be quadrupled). As a result, the number of AD converters required to detect the multiple first aggregated optical signals / second aggregated optical signals in the optical signal detector 20 located downstream of the optical signal aggregater 10 can be reduced.

[0058] As shown in Figure 4, pulsed light possesses coherence, so when the signal aggregator 14 aggregates pulsed light of multiple wavelengths, a peak at a different wavelength than the peak of the pulsed light before aggregation appears after aggregation, thereby achieving a higher dimensionality in the signal space of the optical signal. As a result, sparse principal component analysis and compressed sensing become available in the optical signal detector 20, and detection of the transmitted signal becomes possible through dimensionality reduction of the signal space by sparse compression, which reduces the number of dimensions of the data for the higher dimensional optical signal. In addition, by aggregating the optical signal, the intensity increases and the signal-to-noise ratio improves, resulting in a signal that is more resistant to noise.

[0059] The optical signal aggregater 10 of the first embodiment has a signal aggregation unit 14. The signal aggregation unit 14 aggregates pulsed light of multiple wavelengths in the sampling signal so that each of the multiple wavelengths is included once. By aggregating pulsed light of different wavelengths in this way, wavelengths that can distinguish the analytical signal due to coherence appear. As a result, in the analysis phase, the optical signal detector 20 generates multiple analytical spectral data by selecting spectra corresponding to wavelengths that can be distinguished by sparse principal component analysis in each of the multiple first spectral data. In the detection phase, the optical signal detector 20 obtains measured values ​​of the spectral intensity corresponding to the selected wavelength in the second spectral data by compressed sensing, and enables the detection of the transmitted signal by comparing patterns between these measured values ​​and the multiple analytical spectral data.

[0060] Generally, detecting a transmitted signal in a receiver requires a sampling frequency twice the signal bandwidth of the transmitted signal. In contrast, in the optical signal receiver 100 of the first embodiment, signal aggregation is performed by an optical signal aggregater 10. For example, by aggregating four wavelengths of optical signals, the number of optical signals sampled when detecting the transmitted signal is reduced to one-quarter, and as a result, the sampling frequency required for detection can be reduced to one-quarter. Thus, in the optical signal receiver 100 of the first embodiment, detection of the transmitted signal is possible at a sampling frequency below the signal bandwidth of the transmitted signal, which reduces the number of AD converters and simplifies the configuration.

[0061] In the first embodiment, an example of aggregating light of four different wavelengths was described, but the number of optical signals to be aggregated is not limited to four and may be increased depending on the capabilities of the computer. For example, when aggregating 10 optical signals of different wavelengths, the sampling frequency required for the AD conversion processing in the detection phase by the optical signal detector 20 can be reduced to one-tenth, thus reducing it step by step. In this way, the number of AD converters required in the optical signal detector 20 can be reduced step by step, reducing the manufacturing cost and power consumption of the optical signal receiver 100, and enabling the use of AD converters with high accuracy (resolution).

[0062] The sampling processing unit 13 of the first embodiment generates a first optical signal and a second optical signal by changing the intensity of the sampling signal in accordance with a plurality of analysis signals and a transmission signal. By performing sampling that changes the intensity, it becomes possible to obtain discriminable wavelength characteristics that appear in the aggregation process by intensity. As a result, multiple first spectral data and second spectral data obtained by the spectrometer 21 can be used, and in the detection phase, it is only necessary to compare the analysis spectral data and the second spectral data, thereby speeding up the detection processing of the transmission signal.

[0063] The optical signal receiver 100 of the first embodiment includes an optical signal aggregater 10 and an optical signal detector 20. The optical signal aggregater 10 outputs a plurality of first aggregated optical signals and a plurality of second aggregated optical signals. Due to the coherence of light, peaks at wavelengths different from the peaks of the pulsed light before aggregation appear in the plurality of first aggregated optical signals and second aggregated optical signals. The optical signal detector 20 utilizes the wavelengths at which peaks appear due to aggregation to perform sparse principal component analysis on the plurality of first aggregated optical signals, compressed sensing on the second aggregated optical signal, and detection of the transmitted signal by comparing patterns between the results of the sparse principal component analysis and the measurement results of the compressed sensing. In this way, signal aggregation by the optical signal detector 20 enables compressed sensing in the optical signal detector 20, and as a result, the optical signal receiver 100 can detect the transmitted signal at a sampling frequency below the signal bandwidth of the transmitted signal.

[0064] The optical signal detector 20 of the first embodiment includes a spectrometer 21 and a calculator 22. By providing the spectrometer 21, first spectral data and second spectral data can be acquired from the first aggregated optical signal and the second aggregated optical signal, so that sparse principal component analysis and compressed sensing can be performed in these spectral data according to the wavelengths at which the analytical signal can be identified.

[0065] (Second Embodiment) In the first embodiment, the first aggregated optical signal and the second aggregated optical signal generated by the optical signal aggregater 10 were spectrally analyzed in the optical signal detector 20 to generate first spectral data and second spectral data. In the second embodiment, an example will be described in which the first aggregated optical signal and the second aggregated optical signal are nonlinearly transformed in the optical signal detector 20 and then spectrally analyzed.

[0066] Figure 8 shows an optical signal receiver 100A of the second embodiment. In this figure, a nonlinear converter 31 is provided in front of the spectrometer 21 in the optical signal detector 20. When the nonlinear converter 31 receives a plurality of first aggregated optical signals and a second aggregated optical signal, it generates a plurality of first nonlinear optical signals and a second nonlinear optical signal by performing a nonlinear conversion. The plurality of first nonlinear optical signals and a second nonlinear optical signal generated by the nonlinear converter 31 are converted into first spectral data and second spectral data via the spectrometer 21.

[0067] Here, the nonlinear converter 31 can convert the optical signal into a nonlinear optical signal through nonlinear optical effects, so that the characteristics of the optical signal (e.g., time waveform, intensity, amplitude, phase, or any combination thereof) can be nonlinearly mapped into spectral space. As a result, in sparse principal component analysis, it is possible to generate multiple first spectral data that can represent the differences between multiple first optical signals with fewer frequency components.

[0068] As shown in the first embodiment, the multiple first and second aggregated optical signals have the characteristic of appearing due to coherence when pulsed light of multiple wavelengths is aggregated, making multivariate analysis methods (e.g., sparse principal component analysis) possible.

[0069] In the second embodiment, the added nonlinear converter 31 corresponds to a physical realization method for data transformation to a higher-dimensional space using a nonlinear function. That is, the nonlinear converter 31 can map the characteristics of an optical signal containing a nonlinear structure to spectral space (i.e., a higher-dimensional space), and therefore can transform the nonlinear structure contained in the first and second aggregated optical signals into a spectrum containing multiple frequency components to which sparse principal component analysis can be applied.

[0070] For example, a nonlinear optical medium can be used as the nonlinear converter 31. More specifically, a nonlinear optical fiber or a nonlinear optical waveguide (e.g., a silicon waveguide) can be used as the nonlinear converter 31, but is not limited to these.

[0071] Next, the processing of the optical signal receiver 100A will be explained using Figures 9 and 10. Figure 9 shows the processing of the optical signal receiver 100A performed in the analysis phase. Figure 10 shows the processing of the optical signal receiver 100A performed in the detection phase.

[0072] First, the analysis phase will be explained with reference to Figure 9. Figure 9 is a flowchart showing the analysis phase process in the second embodiment. Compared to the analysis phase process of the first embodiment shown in Figure 6, the process of step S31 is added between steps S11 and S12.

[0073] In step S31, the nonlinear converter 31 generates a first nonlinear optical signal by performing a nonlinear transformation on the first aggregated optical signal. Then, in step S12, the spectrometer 21 obtains first spectral data by spectrally analyzing the first nonlinear optical signal. The subsequent processing is the same as in the first embodiment, and analytical spectral data is obtained.

[0074] Next, the detection phase will be explained with reference to Figure 10. Figure 10 is a flowchart showing the processing of the detection phase in the second embodiment. Compared with the processing of the detection phase in the first embodiment shown in Figure 7, the processing of step S32 is added between steps S21 and S22.

[0075] In step S32, the nonlinear converter 31 generates a second nonlinear optical signal by performing a nonlinear transformation on the second aggregated optical signal. Then, in step S22, the spectrometer 21 generates second spectral data by spectrally analyzing the second nonlinear optical signal. The subsequent processing is the same as in the first embodiment, and the transmission signal is detected by comparison with the analyzed spectral data, and the analysis result is output.

[0076] According to the optical signal detector 20 of the second embodiment, by adding a nonlinear converter 31, the nonlinear structure contained in the first aggregated optical signal and the second aggregated optical signal can be converted into a spectrum containing multiple frequency components to which the analysis method can be applied. As a result, in sparse principal component analysis and compressed sensing, it becomes possible to utilize features that appear due to nonlinear conversion in addition to features that appear due to coherence when multiple pulsed light is aggregated, thereby improving the speed and accuracy of the detection processing of the transmitted signal.

[0077] This invention allows for various embodiments and modifications without departing from the broad spirit and scope of the invention. Furthermore, the embodiments described above are for illustrative purposes only and do not limit the scope of the invention. In other words, the scope of the invention is indicated not by the embodiments, but by the claims. Various modifications made within the scope of the claims and the equivalent scope of the invention are considered to be within the scope of the invention.

[0078] 10 Optical signal aggregater 11 Sampling signal generation unit 12 Analysis signal generation unit 13 Sampling processing unit 14 Signal aggregation unit 20 Optical signal detector 21 Spectrometer 22 Calculator 221 Analysis unit 222 Detection unit 31 Nonlinear converter 100, 100A Optical signal receiver

Claims

1. An optical signal receiver comprising: a sampling signal generation unit that generates a sampling signal including multiple optical signals of a predetermined pattern; a sampling processing unit that generates multiple optical signals by sampling the sampling signal; and a signal aggregation unit that generates multiple aggregated optical signals by aggregating the multiple optical signals in each of the multiple optical signals according to the predetermined pattern of the multiple wavelengths of the sampling signal.

2. The optical signal receiver according to claim 1, wherein the sampling signal generation unit generates the sampling signal in which the multiple pulsed light of multiple wavelengths changes and repeats in a predetermined pattern, and the signal aggregation unit aggregates the multiple pulsed light of multiple wavelengths in each of the multiple optical signals so that each of the multiple pulsed light of multiple wavelengths is included.

3. The optical signal receiver according to claim 1, wherein the sampling processing unit generates the plurality of optical signals by changing the intensity of the sampling signal according to a predetermined signal.

4. The optical signal receiver further comprises an optical signal detector for detecting a transmission signal, the sampling processing unit generates a plurality of first optical signals by sampling the sampling signal in accordance with a plurality of analytical signals used for sparse principal component analysis, generates a second optical signal by sampling the sampling signal in accordance with the transmission signal detected using the analysis results of the sparse principal component analysis, the signal aggregation unit generates a plurality of first aggregated optical signals and a second aggregated optical signal by aggregating the plurality of first optical signals and the second optical signals, the optical signal detector performs sparse principal component analysis using the plurality of first aggregated optical signals and the second aggregated optical signal generated by the signal aggregation unit, and detects the transmission signal from the second aggregated optical signal generated by the signal aggregation unit using the analysis results of the sparse principal component analysis, according to claim 1.

5. The optical signal receiver according to claim 4, comprising: a spectrometer that generates a plurality of first spectral data from a plurality of first aggregated optical signals and generates a second spectral data from a second aggregated optical signal; an analysis unit that generates a plurality of analytical spectral data having fewer frequency components than the plurality of first spectral data by performing sparse principal component analysis on the plurality of first spectral data; and a detection unit that compares the second spectral data with the plurality of analytical spectral data and detects the transmission signal based on the result of the comparison.

6. The optical signal receiver according to claim 5, wherein the optical signal detector further comprises a nonlinear converter that nonlinearly converts the plurality of first aggregated optical signals into a plurality of first nonlinear optical signals and nonlinearly converts the second aggregated optical signal into a second nonlinear optical signal, and the spectrometer generates the plurality of first spectral data from the plurality of first nonlinear optical signals and generates the second spectral data from the second nonlinear optical signal.

7. An optical signal receiving method comprising: generating a sampling signal containing optical signals of multiple wavelengths in a predetermined pattern; generating multiple optical signals by sampling the sampling signal; and generating multiple aggregated optical signals by aggregating the light of the multiple wavelengths in each of the multiple optical signals according to the predetermined pattern of the multiple wavelengths of the sampling signal.

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