Abstract:
An optical signal-to-noise ratio (OSNR) measuring device includes a processor, wherein the processor executes a process. The process includes: converting an optical signal to an electrical signal; first acquiring a signal intensity from the electrical signal; second acquiring a noise intensity of a predetermined frequency band from the electrical signal; performing a digital conversion on the noise intensity; and computing an OSNR of the optical signal based on the signal intensity and the converted noise intensity. The predetermined frequency band is a frequency band including a folding noise that occurs when the digital conversion is performed.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
       [0001]    This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2016-020118, filed on Feb. 4, 2016, the entire contents of which are incorporated herein by reference. 
       FIELD 
       [0002]    The embodiments discussed herein are related to an Optical Signal-to-Noise Ratio measuring device (OSNR measuring device) and an OSNR measuring method, which measure an OSNR on an optical network. 
       BACKGROUND 
       [0003]    The next-generation optical network desires an OSNR measuring device that monitors an OSNR of an optical signal in operation without giving any effect to a main signal, for fault detection, early recovery from the fault, and realization of a network control technology for increasing the transmission capacity. 
         [0004]    The OSNR measuring device receives an optical signal by using, for example, a photodiode, and measures an OSNR of the optical signal on the basis of the signal intensity of a Direct-Current component (DC component) in the received optical signal and the noise intensity of an Alternating-Current component (AC component) having passed through an optical filter. The OSNR measuring device can measure an OSNR of the optical signal in a simple configuration and at low cost.
   Patent Literature 1: US Patent Application Publication No. 2015-0155935   Patent Literature 2: Japanese Laid-open Patent Publication No. 2015-106905   
 
         [0007]    Recently, a super channel transmission technology for 400 G/1 T transmission uses an optical filter whose bandwidth is approximately 0.1 nm in consideration of influence of crosstalk from adjacent subcarriers because a signal band of subcarrier signals that constitute a super channel is 32 GHz and a bandwidth thereof is approximately 0.26 nm. In a super channel transmission technology, a frequency bandwidth of an optical filter is narrowed. 
         [0008]    However, in the OSNR measuring device, deterioration in OSNR monitoring accuracy is more significant as a frequency bandwidth of an optical filter becomes narrower. For example, the amount of amplifier noise included in the noise intensity decreases relatively to an optical signal. As a result, in such a case that the bandwidth is 0.2 nm or less, the monitoring accuracy of an OSNR deteriorates as illustrated in  FIG. 10 . 
         [0009]    Therefore, in order to increase the monitoring accuracy of an OSNR, it is considered to execute an averaging process and increase the monitoring accuracy of an OSNR by increasing the averaging count in the averaging process. However, because a time until the monitoring accuracy is improved is longer as the averaging count increases, measuring time of an OSNR increases. 
       SUMMARY 
       [0010]    According to an aspect of an embodiment, an optical signal-to-noise ratio (OSNR) measuring device includes a processor, wherein the processor executes a process. The process includes: converting an optical signal to an electrical signal; first acquiring a signal intensity from the electrical signal; second acquiring a noise intensity of a predetermined frequency band from the electrical signal; performing a digital conversion on the noise intensity; and computing an OSNR of the optical signal based on the signal intensity and the converted noise intensity, wherein the predetermined frequency band is a frequency band including a folding noise that occurs when the digital conversion is performed. 
         [0011]    The object and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the claims. 
         [0012]    It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention, as claimed. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0013]      FIG. 1  is a block diagram illustrating one example of an OSNR measuring device according to a first embodiment; 
           [0014]      FIG. 2  is a block diagram illustrating a configuration example of a monitor controller in the OSNR measuring device according to the first embodiment; 
           [0015]      FIG. 3  is a diagram illustrating a relation example between frequency bandwidths extracted by a first Band Pass Filter (BPF) and a second BPF in a relation between a signal power and a signal frequency; 
           [0016]      FIG. 4  is a flowchart illustrating one example of processing operations, of the monitor controller in the OSNR measuring device, which are associated with a first OSNR computing process; 
           [0017]      FIG. 5  is a flowchart illustrating one example of processing operations, of the monitor controller in the OSNR measuring device, which are associated with a second OSNR computing process; 
           [0018]      FIG. 6A  is a diagram illustrating one example of a frequency bandwidth of the first BPF in a filter design without including a folding noise in a relation between a signal power and a signal frequency; 
           [0019]      FIG. 6B  is a diagram illustrating one example of a frequency bandwidth of the first BPF in a filter design including a folding noise in a relation between a signal power and a signal frequency; 
           [0020]      FIG. 7  is a diagram illustrating one example of OSNR errors in pass frequency bands including a folding noise and without including a folding noise; 
           [0021]      FIG. 8  is a block diagram illustrating a configuration example of a monitor controller in an OSNR measuring device according to a second embodiment; 
           [0022]      FIG. 9  is a block diagram illustrating a configuration example of a monitor controller in an OSNR measuring device according to a third embodiment; and 
           [0023]      FIG. 10  is a diagram illustrating one example of an error between an OSNR computed by a conventional OSNR measuring device and a reference OSNR for each filter bandwidth. 
       
    
    
     DESCRIPTION OF EMBODIMENTS 
       [0024]    Preferred embodiments of the present invention will be explained with reference to accompanying drawings. In addition, the disclosed technology is not limited to the embodiments described below. Moreover, these embodiments may be appropriately combined within a consistent range. 
       [a] First Embodiment 
       [0025]      FIG. 1  is a block diagram illustrating one example of an OSNR measuring device according to a first embodiment. The OSNR measuring device  1  illustrated in  FIG. 1  includes an optical filter  11 , a photodetector  12 , a light intensity monitor  13 , a first Band Pass Filter (first BPF)  14 , an Analog Digital Converter (ADC)  15 , a monitor controller  16 , and an optical filter controller  17 . The optical filter  11  is, for example, a wavelength filter that extracts a desired optical signal from, for example, a Wavelength Division Multiplex signal (WDM signal). The photodetector  12  is, for example, a photodiode that electrically converts the extracted optical signal to an electrical signal. The photodetector  12  outputs the electrically converted electrical signal to the light intensity monitor  13  and the first BPF  14 . 
         [0026]    The light intensity monitor  13  extracts a signal intensity P total , which is a DC component of the output signal of the photodetector  12 , and inputs the extracted signal intensity P total  to the monitor controller  16 . The signal intensity P total  is, for example, a signal power of an optical signal. The signal intensity P total  may be expressed by a formula (1). 
         [0000]    
       
         
           
             
               
                 
                   
                     P 
                     total 
                   
                   = 
                   
                     
                       
                         P 
                         sig 
                       
                       + 
                       
                         P 
                         ase 
                       
                     
                     = 
                     
                       
                         P 
                         sig 
                       
                        
                       
                         ( 
                         
                           1 
                           + 
                           
                             
                               1 
                               OSNR 
                             
                              
                             
                               
                                 B 
                                 o 
                               
                               R 
                             
                           
                         
                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   1 
                   ) 
                 
               
             
           
         
       
     
         [0027]    “P sig ” corresponds to a signal light power, “P ase ” corresponds to an Amplified Spontaneous Emission noise power (ASE noise power), “B o ” corresponds to an optical bandwidth, and “R” corresponds to an ASE noise bandwidth. 
         [0028]    The first BPF  14  extracts a noise intensity N total  that is an AC component of a predetermined frequency band and is a result of removing a DC component from an electrical signal of the photodetector  12 . The noise intensity N total  is, for example, a noise component of an optical signal including a folding noise. The noise intensity N total  may be expressed by a formula (2) 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       
                         
                           N 
                           total 
                         
                         = 
                           
                          
                         
                           
                             N 
                             beat 
                           
                           + 
                           
                             N 
                             shot 
                           
                           + 
                           
                             N 
                             thermal 
                           
                           + 
                           
                             N 
                             circuit 
                           
                           + 
                           
                             N 
                             signal 
                           
                         
                       
                     
                   
                   
                     
                       
                         = 
                           
                          
                         
                           
                             N 
                             beat 
                           
                           + 
                           
                             N 
                             nonbeat 
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   2 
                   ) 
                 
               
             
           
         
       
     
         [0029]    “N beat ” is a beat noise, “N shot ” is a shot noise, “N thermal ” is a thermal noise, “N circuit ” is a circuit noise, “N signal ” is a main signal component, and “N nonbeat ” is a nonbeat noise. For the convenience of explanation, the nonbeat noise N nonbeat  will be explained to be zero. 
         [0030]    The ADC  15  samples the noise intensity of a predetermined frequency band, which is extracted by the first BPF  14 , to execute digital conversion, and inputs a digitally converted noise intensity N total  to the monitor controller  16 . The monitor controller  16  computes an Optical Signal-to-Noise Ratio (OSNR) on the basis of the signal intensity extracted in the light intensity monitor  13  and the noise intensity digitally converted in the ADC  15 . The optical filter controller  17  controls the optical filter  11  to select an optical wavelength that is to be extracted in the optical filter  11 . 
         [0031]      FIG. 2  is a block diagram illustrating a configuration example of the monitor controller  16  in the OSNR measuring device  1  according to the first embodiment. The monitor controller  16  illustrated in  FIG. 2  includes a second BPF  21 , a computing unit  22 , a correcting coefficient storage  23 , a first controller  24 , and a first setting unit  25 . The second BPF  21 , the computing unit  22 , the correcting coefficient storage  23 , the first controller  24 , and the first setting unit  25  may be realized by using, for example, processors and memories (not illustrated). The second BPF  21  extracts the noise intensity N beat  that is an AC component of a monitor target from the noise intensity N total . The noise intensity N beat  of the monitor target may be expressed by a formula (3). 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       
                         
                           N 
                           beat 
                         
                         = 
                           
                          
                         
                           A 
                            
                           
                             ( 
                             
                               
                                 2 
                                  
                                 
                                   P 
                                   sig 
                                 
                                  
                                 
                                   P 
                                   ase 
                                 
                                  
                                 
                                   1 
                                   
                                     B 
                                     o 
                                   
                                 
                               
                               + 
                               
                                 
                                   P 
                                   ase 
                                   2 
                                 
                                  
                                 
                                   1 
                                   
                                     B 
                                     o 
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                     
                   
                   
                     
                       
                         = 
                           
                          
                         
                           2 
                            
                           
                             A 
                             R 
                           
                            
                           
                             
                               P 
                               sig 
                               2 
                             
                              
                             
                               ( 
                               
                                 
                                   1 
                                   OSNR 
                                 
                                 + 
                                 
                                   
                                     B 
                                     o 
                                   
                                   
                                     2 
                                      
                                     
                                       R 
                                       · 
                                       
                                         OSNR 
                                         2 
                                       
                                     
                                   
                                 
                               
                               ) 
                             
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
     
         [0032]    “A” is a correcting coefficient. 
         [0033]    The computing unit  22  computes an OSNR by using the formulae (1) to (3) on the basis of the signal intensity P total  of the light intensity monitor  13 , the noise intensity N beat  of a monitor target of the second BPF  21 , and the correcting coefficient “A”. The correcting coefficient “A” is a coefficient for computing so that an OSNR computed on the basis of the signal intensity P total  and the noise intensity N beat  in the computing unit  22  becomes an actual OSNR. The actual OSNR is, for example, an OSNR of an optical signal in which a known Amplified Spontaneous Emission noise (ASE noise) is added to the optical signal and an optical spectrum analyzer is used. The correcting coefficient storage  23  is a region in which the correcting coefficient “A” is stored. The first controller  24  controls whole of the monitor controller  16 . The first setting unit  25  sets various setting contents of the optical filter  11 , the first BPF  14 , the ADC  15 , and the second BPF  21 . The first setting unit  25  sets the optical filter controller  17  to set an optical wavelength that is an extraction target of the optical filter  11 . The first setting unit  25  sets a pass frequency band of the first BPF  14 . The first setting unit  25  sets a pass frequency band of the second BPF  21 . The first setting unit  25  sets a sampling frequency of the ADC  15 . 
         [0034]      FIG. 3  is a diagram illustrating a relation example between frequency bandwidths extracted by the first BPF  14  and the second BPF  21  in a relation between a signal power and a signal frequency. Herein, “fs” illustrated in  FIG. 3  is a sampling frequency of the ADC  15 , “fs/2” is the Nyquist frequency that is defined as a half of the sampling frequency fs, “fc” is a canter frequency of the second BPF  21 , and “Δf” is a pass frequency bandwidth of the second BPF  21 . “BPF low ” is a lower limit frequency of a pass frequency band of the first BPF  14 , and “BPF high ” is an upper limit frequency of a pass frequency band of the first BPF  14 . The pass frequency bandwidth of the first BPF  14  is assumed to satisfy the following conditions: 0≦BPF low &lt;fc−Δf/2, fs/2+fc+Δf/2≦BPF high . The upper limit frequency BPF high  is assumed to be a frequency that is in a higher band than that of the Nyquist frequency and is further assumed not to receive influence of wavelength dispersion, polarization mode dispersion, and waveform deterioration by non-linearity of a fiber. The first BPF  14  is to extract an AC component that includes a folding noise associated with digital conversion of an AC component of the ADC  15 . 
         [0035]    The second BPF  21  reversely brings in a folding noise in a higher frequency band than that of the Nyquist frequency to reduce variation when the noise intensity N beat  of a monitor target is extracted from the noise intensity N total  including a folding noise. 
         [0036]    Next, the operation of the OSNR measuring device  1  according to the first embodiment will be explained.  FIG. 4  is a flowchart illustrating one example of processing operations, of the monitor controller  16  in the OSNR measuring device  1 , which are associated with a first OSNR computing process. The first OSNR computing process illustrated in  FIG. 4  is a process in which an OSNR is computed on the basis of the signal intensity P total  of a photoelectrically converted electrical signal, the noise intensity N beat  including a folding noise, and the correcting coefficient “A”. 
         [0037]    In  FIG. 4 , the first controller  24  in the monitor controller  16  sets, via the first setting unit  25 , a sampling frequency of the ADC  15 , a pass frequency bandwidth of the first BPF  14 , and a pass frequency bandwidth of the second BPF  21  (Step S 11 ). The first controller  24  sets, via the first setting unit  25 , a center wavelength of the optical filter  11  to an optical wavelength of a monitor target (Step S 12 ). 
         [0038]    The computing unit  22  in the monitor controller  16  determines whether or not the signal intensity P total  from the light intensity monitor  13  and the noise intensity N beat  including a folding noise that is from the second BPF  21  are detected (Step S 13 ). When detecting the signal intensity P total  and the folding noise including the noise intensity N beat  (Step S 13 : Yes), the computing unit  22  computes an OSNR, citing formulae (1) to (3), on the basis of the detected signal intensity P total , the noise intensity N beat  including a folding noise, and the correcting coefficient “A” (Step S 14 ), and terminates a processing operation illustrated in  FIG. 4 . When not detecting the signal intensity P total  or the noise intensity N beat  including a folding noise (Step S 13 : No), the computing unit  22  shifts the processing to Step S 13  to monitor whether or not the signal intensity P total  and the noise intensity N beat  are detected. 
         [0039]      FIG. 5  is a flowchart illustrating one example of processing operations, of the monitor controller  16  in the OSNR measuring device  1 , which are associated with a second OSNR computing process. The second OSNR computing process illustrated in  FIG. 5  is a process in which the correcting coefficient “A” is adjusted while computing an OSNR, and the adjusted correcting coefficient “A” is updated. 
         [0040]    In  FIG. 5 , the monitor controller  16  acquires an actual OSNR measured by using an optical spectrum analyzer (not illustrated) (Step S 21 ). The first controller  24  in the monitor controller  16  sets, via the first setting unit  25 , a sampling frequency of the ADC  15 , a pass frequency bandwidth of the first BPF  14 , and a pass frequency bandwidth of the second BPF  21  (Step S 22 ). The first controller  24  sets, via the first setting unit  25 , a center wavelength of the optical filter  11  to an optical wavelength of a monitor target (Step S 23 ). 
         [0041]    The computing unit  22  determines whether or not the signal intensity P total  that is from the light intensity monitor  13  and the noise intensity N beat  including a folding noise that is from the second BPF  21  are detected (Step S 24 ). When detecting the signal intensity P total  and the noise intensity N beat  (Step S 24 : Yes), the computing unit  22  acquires the correcting coefficient “A” from the correcting coefficient storage  23  (Step S 25 ). The computing unit  22  computes, citing formulae (1) to (3), an OSNR on the basis of the detected signal intensity P total , the noise intensity N beat  including a folding noise, and the correcting coefficient “A” (Step S 26 ). The first controller  24  computes the difference between the computed OSNR and an actual OSNR (Step S 27 ), and determines whether or not the difference is equal to or less than a predetermined threshold (Step S 28 ). In such a case that the difference is equal to or less than the predetermined threshold (Step S 28 : Yes), the first controller  24  terminates the processing operation illustrated in  FIG. 5  while maintaining the present correcting coefficient “A”. 
         [0042]    In such a case that the difference is not equal to or less than the predetermined threshold (Step S 28 : No), the first controller  24  adjusts the correcting coefficient “A” so that the difference is minimum, updates the adjusted correcting coefficient “A” in the correcting coefficient storage  23  (Step S 29 ), and terminates the processing operation illustrated in  FIG. 5 . In such a case that the signal intensity P total  or the noise intensity N beat  is not detected (Step S 24 : No), the computing unit  22  shifts the process to Step S 24  to monitor whether or not the signal intensity P total  and the noise intensity N beat  are detected. 
         [0043]      FIG. 6A  is a diagram illustrating one example of a frequency bandwidth of the first BPF  14  in a filter design without including a folding noise in a relation between a signal power and a signal frequency. As illustrated in  FIG. 6A , an upper limit frequency of a pass frequency band of the first BPF  14  is set so that it does not exceed the Nyquist frequency in order to remove the folding noise. For example, in such a case that the sampling frequency of the ADC  15  is 1 MHz and the Nyquist frequency is 500 kHz, a lower limit frequency of a pass frequency band of the first BPF  14  is set to 10 Hz and the upper limit frequency thereof is set to 300 kHz. As a result, the first BPF  14  extracts the noise intensity N total  from an electrical signal in a pass frequency band that does not include a folding noise. 
         [0044]    On the other hand,  FIG. 6B  is a diagram illustrating one example of a frequency bandwidth of the first BPF in a filter design including a folding noise in a relation between a signal power and a signal frequency. As illustrated in  FIG. 6B , an upper limit frequency of a pass frequency band of the first BPF  14  is set in a higher band than the Nyquist frequency in order to include a folding noise. For example, in such a case that a sampling frequency of the ADC  15  is 1 MHz and the Nyquist frequency is 500 kHz, the lower limit frequency of the pass frequency band of the first BPF  14  is set to 10 Hz and the upper limit frequency thereof is set to 1 MHz. As a result, the first BPF  14  extracts the noise intensity N total  including a folding noise from an electrical signal in a pass frequency band including a folding noise. 
         [0045]      FIG. 7  is a diagram illustrating one example of OSNR errors in pass frequency bands including a folding noise and without including a folding noise. As illustrated in  FIG. 7 , an OSNR computed by using the noise intensity N beat  of a pass frequency band including a folding noise is proved to have higher accuracy compared with an OSNR computed by using that not including a folding noise. 
         [0046]    In the OSNR measuring device  1  according to the first embodiment, an electrical signal, which is a result of electrical conversion of an optical signal, is branched and output to the light intensity monitor  13  and the ADC  15 , the signal intensity P total  is detected from the electrical signal by the light intensity monitor  13 , and the noise intensity N total  of a frequency band including a folding noise of the ADC  15  is extracted from the electrical signal by the first BPF  14 . The OSNR measuring device  1  extracts the converted noise intensity N beat  by using the second BPF  21 . The OSNR measuring device  1  computes an OSNR to the optical signal on the basis of the signal intensity P total , the noise intensity N beat  of a frequency band including a folding noise, and the correcting coefficient “A”. As a result, the OSNR measuring device  1  uses the noise intensity N total  of a frequency band including a folding noise, and thus, the amount of an amplifier noise included in the noise intensity N beat  relatively increases to the optical signal. Therefore, even in a case where a bandwidth is 0.2 nm or less, the deterioration in the monitoring accuracy of an OSNR can be reduced. In other words, by employing the OSNR measuring device  1 , the deterioration in monitoring accuracy of an OSNR by constriction of a conventional frequency band can be reduced even in a super channel transmission system in which a frequency bandwidth of the optical filter  11  is constricted. 
         [0047]    The computing unit  22  in the OSNR measuring device  1  acquires the noise intensity N beat  of a monitor target from the converted noise intensity N total , and further computes an OSNR on the basis of the signal intensity P total , the noise intensity N beat  of the monitor target, and the correcting coefficient “A”. As a result, by employing the OSNR measuring device  1 , deterioration in the monitoring accuracy of an OSNR can be reduced even in a super channel transmission system in which a bandwidth of the optical filter  11  is constricted. 
         [0048]    The first setting unit  25  of the OSNR measuring device  1  automatically sets a pass frequency band of the first BPF  14 , a pass frequency band of the second BPF  21 , and a sampling frequency of the ADC  15  in accordance with a specified wavelength. As a result, the OSNR measuring device  1  can automatically set setting contents of the first BPF  14 , the second BPF  21 , and the ADC  15  in accordance with a specified wavelength of the optical filter  11 . 
         [0049]    The upper limit frequency of the pass frequency band, which is set by using the first BPF  14  in the OSNR measuring device  1 , is in a higher band than the Nyquist frequency that is a half of a sampling frequency of the ADC  15 . As a result, the first BPF  14  can extract the noise intensity N total  including a folding noise from an electrical signal. 
         [0050]    The computing unit  22  in the OSNR measuring device  1  stores the correcting coefficient “A” in the correcting coefficient storage  23  so that an actual OSNR can be computed by using the computed OSNR on the basis of the signal intensity P total  and the noise intensity N beat . The computing unit  22  computes an OSNR on the basis of the signal intensity P total , the noise intensity N beat , and the correcting coefficient “A”. As a result, the computing unit  22  can compute an OSNR with the high monitoring accuracy, which approximates to an actual OSNR. 
         [0051]    The aforementioned computing unit  22  according to the first embodiment computes an OSNR on the basis of the signal intensity P total , the noise intensity N beat , and the correcting coefficient “A”. However, an OSNR may be computed on the basis of the signal intensity P total  and the noise intensity N beat  instead of using the correcting coefficient. 
         [0052]    The monitor controller  16  in the aforementioned OSNR measuring device  1  according to the first embodiment extracts the noise intensity N beat  of a monitor target from the noise intensity N total  including a folding noise in the first BPF  14 , and further computes an OSNR on the basis of the signal intensity P total  and the noise intensity N beat  of a monitor target. However, not limited to the monitor controller  16  illustrated in  FIG. 2 , it may be appropriately modified, and thus, will be explained hereinafter as a second embodiment with regard to the modified embodiment. 
       [b] Second Embodiment 
       [0053]      FIG. 8  is a block diagram illustrating a configuration example of a monitor controller  16 A in an OSNR measuring device  1  according to a second embodiment. The configuration same as that of the monitor controller  16  illustrated in  FIG. 2  will be followed by the same reference symbols as those illustrated in  FIG. 2 , and thus, explanation about the duplicate configuration and operation will be omitted. 
         [0054]    The monitor controller  16 A illustrated in  FIG. 8  includes an averaging processing unit  26 , a second controller  24 A, and a second setting unit  25 A other than the second BPF  21 , the computing unit  22 , and the correcting coefficient storage  23 . The averaging processing unit  26  is a processing unit that is arranged between the second BPF  21  and the computing unit  22 , and averages, at a predetermined averaging count, the noise intensity N beat  of a monitor target extracted in the second BPF  21 . The second controller  24 A controls whole of the monitor controller  16 A. The second setting unit  25 A sets a sampling frequency of the ADC  15 , a pass frequency band of the first BPF  14 , a pass frequency band of the second BPF  21 , and averaging count of the averaging processing unit  26 . 
         [0055]    The computing unit  22  computes an OSNR by using formulae (1) to (3) on the basis of the signal intensity P total  of the light intensity monitor  13 , the noise intensity N beat  of a monitor target that is averaged in the averaging processing unit  26 , and the correcting coefficient “A”. 
         [0056]    The monitor controller  16 A according to the second embodiment computes an OSNR on the basis of the signal intensity P total  of the light intensity monitor  13 , the averaged noise intensity N beat  of a monitor target, and the correcting coefficient “A”. As a result, the averaging the noise intensity N beat  of a monitor target leads to usage of a noise component with high accuracy, and thus, an OSNR with high accuracy can be acquired. 
       [c] Third Embodiment 
       [0057]      FIG. 9  is a block diagram illustrating a configuration example of a monitor controller  16 B in an OSNR measuring device  1  according to a third embodiment. The configuration same as that of the monitor controller  16  illustrated in  FIG. 2  will be followed by the same reference symbols as those illustrated in  FIG. 2 , and thus, explanation about the duplicate configuration and operation will be omitted. 
         [0058]    The monitor controller  16 B illustrated in  FIG. 9  includes a Fourier Fast Transformer processing unit (FFT processing unit)  27 , an averaging processing unit  28 , a third controller  24 B, and a third setting unit  25 B other than the computing unit  22  and the correcting coefficient storage  23 . 
         [0059]    The FFT processing unit  27  converts the noise intensity N total  extracted in the first BPF  14  to a frequency domain signal that is corresponding to the noise intensity N beat  of a monitor target. The averaging processing unit  28  is a processing unit that is arranged between the FFT processing unit  27  and the computing unit  22 , and averages the noise intensity N beat  of a monitor target, which is the frequency domain signal converted in the FFT processing unit  27 , at a predetermined averaging count. The third controller  24 B controls whole of the monitor controller  16 B. The third setting unit  25 B sets a sampling frequency of the ADC  15 , a pass frequency band of the first BPF  14 , a frequency domain signal of a monitor target of the FFT processing unit  27 , and averaging count of the averaging processing unit  28 . 
         [0060]    The computing unit  22  computes an OSNR by using formulae (1) to (3) on the basis of the signal intensity P total  of the light intensity monitor  13 , the noise intensity N beat  of the monitor target that is averaged in the averaging processing unit  28 , and the correcting coefficient “A”. 
         [0061]    The monitor controller  16 B according to the third embodiment computes an OSNR on the basis of the signal intensity P total  of the light intensity monitor  13 , the averaged noise intensity N beat  of a monitor target, and the correcting coefficient “A”. As a result, the averaging the noise intensity N beat  of a monitor target leads to usage of a noise component with high accuracy, and thus, an OSNR with high accuracy can be measured. 
         [0062]    Moreover, a Discrete Fourier Transformer processing unit (DFT processing unit) may be used instead of the FFT processing unit  27  according to the third embodiment. 
         [0063]    In addition, each component of each apparatus illustrated in the drawings is functionally conceptual, and thus, does not always physically configured as illustrated in the drawings. Namely, a specific mode of separation or integration of each apparatus is not limited to that illustrated in the drawings. That is, all or some of the components can be configured by separating or integrating them functionally or physically in any unit, according to various types of loads, the status of use, etc. 
         [0064]    Furthermore, all or arbitrary ones of processing functions may be executed by a Central Processing Unit (CPU) (or a microcomputer such as a Micro Processing Unit (MPU) or a Micro Controller Unit (MCU)), and further may be executed by a program, which is analyzed and executed by the CPU (or microcomputer such as MPU or MCU), or hardware by the wired logic. 
         [0065]    According to an aspect of the embodiments, an OSNR can be measured with high accuracy. 
         [0066]    All examples and conditional language recited herein are intended for pedagogical purposes of aiding the reader in understanding the invention and the concepts contributed by the inventor to further the art, and are not to be construed as limitations to such specifically recited examples and conditions, nor does the organization of such examples in the specification relate to a showing of the superiority and inferiority of the invention. Although the embodiments of the present invention have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.