A 127g-pm-qpsk signal analysis algorithm

Abstract

The application discloses a 127G-PM-QPSK signal analysis algorithm, which extracts OPU4 from the original signal frame of OTU4, analyzes the overhead of OPUk based on the PSI characteristics, obtains the customer signal group N of the signal, calculates the Cm value according to the customer signal group, extracts the payload data in OPU4 according to the Cm value, extracts all data in each group, obtains N ODUk, extracts the payload data in ODUk, and obtains the customer signal according to different mapping modes. The algorithm can be applied to ODUflex complex signal grouping and has high accuracy, and can provide effective guarantee for front-end device signal access.

Description

Technical Field

[0001] The present invention relates to the field of optical transmission network, in particular to 127G-PM-QPSK signal analysis Background Art

[0002] With the rapid development of Internet technology and the continuous expansion of business scope, the continuous increase in the number of users, and the increasing complexity of the requirements for transmission networks from technologies such as the Internet of Things, cloud computing, big data, and mobile Internet, the disadvantages of traditional OTN technology, such as fixed bandwidth pipes and fixed rate interfaces, have become increasingly significant and can no longer meet the needs of network development. The introduction of ODUflex makes the pipe bandwidth of OTN technology flexible and variable, ensuring efficient bandwidth utilization and reducing transmission costs. Currently, the new optical transport network (OTN) defines two types of rate-variable ODUflex containers:

[0003] One is ODUflex, based on constant bit rate (CBR) services, which adapts to CBR services through synchronous mapping of BMPs. The rate range is generally divided into three segments: between ODU1 and ODU2, between ODU2 and ODU3, and between ODU3 and ODU4. The other is GFP, which ranges from 1.38 GHz to 104.134 GHz. Theoretically, the bit rate of this method is arbitrarily variable. The ITU-T recommends using an integer number of tributary timeslots of the minimum HO ODUk channel, i.e., (N*1.25 GHz, N∈[1,80]), where N represents the number of tributary timeslots occupied by GFP.

[0004] The practicality of the second container type has been highly recognized by major technology manufacturers as network technology continues to evolve. This mapping method appears in a large number of transmission signals. However, it also brings some challenges. The application of ODUflex has made the previous method of using the OPU payload structure identifier (PSI) to distinguish client signal groups no longer fully applicable. In many transmission signals, there are client signals with the same and continuous PSI values ​​but not the same signal group, which brings considerable difficulties to the service output of front-end equipment. Summary of the Invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present invention provides an ODUflex complex signal grouping analysis algorithm.

[0006] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0007] The present invention extracts OPU4 by analyzing the original OTU4 signal frame structure, then analyzes the overhead of the OPU4 signal frame, and combines the correlation characteristics of PSI and JC1 to obtain N packets. Next, the first Cm value of each packet is obtained through GMP mapping. The offset of the Cm value between adjacent adjustment cycles can be obtained by XORing the JC values ​​of adjacent adjustment cycles, thereby obtaining the Cm value of each adjustment cycle of the packet. All packet data in OPU4 is extracted according to the sigma / delta algorithm to obtain N ODUk. The payload data in the ODUk is then extracted to obtain the client signal.

[0008] The beneficial effects of the present invention are:

[0009] Traditionally, the OPU payload structure identifier (PSI) was used to analyze client signal groups. This analysis exploited the fact that client signals within the same group had identical and continuous PSI values, enabling partial signal analysis. However, with the introduction and widespread adoption of ODUflex, this traditional analysis method no longer meets practical needs, and most signals cannot be fully analyzed. This present invention, based on the PSI characteristics, analyzes the OPUk overhead. Through overhead analysis, the PSI of client signals in the OPU4 is fully grouped. Currently, in on-site user testing, approximately thousands of signals have been accessed, and no grouping errors have been found, ensuring normal service output. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 OTUk frame structure

[0011] Figure 2 OPUk frame structure

[0012] Figure 3 For PSI and OMFI distribution

[0013] Figure 4 Cm value offset indicator table

[0014] Figure 5 OPUk payload data distribution diagram

[0015] Figure 6 Sigma-Delta mapping formula

[0016] Figure 7 Parameter table DETAILED DESCRIPTION

[0017] In order to make the contents of the present invention more clearly understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the present invention.

[0018] like Figure 1As shown, extract OPU4 from the original OTU4 signal frame structure, remove the overhead part, and then remove the FEC part of OTUk to obtain the following: Figure 2 OPU frame structure. Taking the frame with MFAS=0 (multiframe alignment signal) as the starting point, take the PSI of 80 frames of data after PSI[2] (payload structure identifier), and then take the JC1 value of 80 frames of data with OMFI=0 (multiframe indication) as the starting point. The reason for taking 80 frames of data here is that the value of OMFI is 0 to 79 as a cycle. Therefore, 80 frames can be regarded as an adjustment cycle, such as Figure 3 As shown. Through the analysis of the original data frame OPU4, the data in the same adjustment cycle is divided into two adjustment situations. One is that each frame of data in the same group has code rate adjustment and the adjustment value is the same. The other situation is that each frame of data in the same group is adjusted only in the last frame. In the first situation, sometimes there are situations where the PSI value and the code rate adjustment value are the same in different grouped data frames. For this special situation, a separation algorithm is made. According to the relationship between PSI and JC values, the adjustment cycle of the data is increased, and the data of each adjustment cycle is grouped. The one with the largest number of groups is taken as the grouping result, and group K is obtained at this time. The next step is to calculate the Cm value of each group. First, the K Cm values ​​of the first adjustment cycle are obtained through GMP mapping; the Cm values ​​in subsequent adjustment cycles are obtained according to the difference in JC values ​​of adjacent adjustment cycles to obtain the offset of Cm of the next cycle and thus the Cm value of the next cycle, and the XOR C1-C14 comparison is performed. Figure 4 The offset can be obtained from the table, and the Cm value of the current cycle plus the offset is used as the Cm value of the next cycle, and so on for each subsequent cycle. Next, the Cm value is obtained according to each cycle, and the data of each adjustment cycle is obtained according to the Sigma / Delta algorithm. The payload filling of OPU4 is as follows Figure 5 As shown, press Figure 2 As shown in the figure, the payload part is numbered, and then the number is multiplied by the Cm value, and the remainder is 15200. The number is compared with the Cm value. If it is less than the Cm value, it is data, and if it is greater than the cm value, it is padding. In this way, the Cm values ​​of K packets can be used to obtain K ODUk. The calculation formula is as follows: Figure 6 As shown, the parameters in the formula can be Figure 7 Search in the table.

[0019] Next, the PT in the ODUk overhead is used to determine the multiplexing mapping method. Currently, two common mapping methods are AMP mapping and BMP mapping. By extracting the client signal from the OPUk based on the mapping method, correctly grouped services can be obtained. Common services include 10GE, GFP, and SDH.

[0020] The next step is to send the business data to the corresponding parsing module. The following describes the processing flow of the parsing module:

[0021] 10GE signal analysis: Since 10GE data uses 64B / 66B encoding, the synchronization header must be found first. The synchronization header consists of '0' and '1' and conforms to the binomial distribution. When the data cardinality is large, it can be regarded as a normal distribution. By calculating the mathematical expectation of the normal distribution, the column where the synchronization header is located is obtained, and the GE payload data is further extracted. After the data is extracted, it is arranged into an N*66 row and column matrix. According to the polynomial G(x) = 1 + X 39 +X 58 Descramble the data part; after descrambling, compare the N*66 row and column matrix with the 64B / 66B encoding table to extract the packet data. Next, extract the IP message according to the first-arrival field and frame start character of the Ethernet frame and store it in the form of a pcap file to restore the session information.

[0022] To parse the GFP signal, first find the core header in the GFP frame and XOR the core header with the GFP idle frame (0xB6AB31E0) to get the packet length. However, the GFP data frames are not necessarily continuous. After extracting each frame, you need to find the core header of the next frame again and XOR it with the idle frame to extract all the data packets in sequence. Next, you need to extract the extracted data packets according to the polynomial G(x)=X 43 +1 for descrambling. After data descrambling, the payload mapping method is determined based on the GFP UPI. Currently, there are two common mapping methods: GFP-F (frame mapping), which directly maps Ethernet packets into GFP; and GFP-T (transparent transmission). GFP-F is simpler to process, directly extracting IP packets and storing them in pcap files. However, descrambled GFP-T data cannot be directly extracted and must be further arranged according to 536 bits (8*65B+16B). This creates an N*536 row and column matrix. A single row of data is then taken and re-divided into a small matrix with 8 rows and 65 columns. The data portion of each small matrix is ​​extracted according to the 64B / 65B encoding table. The resulting data is then decoded according to 8B / 10B to obtain the IP packet, which is then stored in a pcap file.

[0023] To analyze the SDH signal, first find the synchronization header (F6F6F6282828) in the SDH frame and use the synchronization header to determine the SDH type. Common types include STM-1, STM-4, STM-16, and STM-64. Since the synchronization header of the SDH signal does not participate in the descrambling, directly take the data part according to the polynomial G(x) = 1+x 6 +x 7 The data is descrambled. After descrambling, the data obtained needs to be extracted from the VC-4 according to the AU-4 pointer indication, and the payload in the high-order particles is extracted.

[0024] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A 127G-PM-QPSK signal analysis algorithm, characterized in that: The following steps are involved: (1) Extract OPU4 from the original signal frame of OTU4; (2) Analyze the overhead JC value of OPUk based on the PSI packet characteristics; (3) N packets are obtained by analyzing the correlation characteristics of PSI and JC1, where the correlation analysis of PSI and JC1 is based on 80-frame data cycle processing; (4) The Cm value of each packet is calculated based on the JC value; (5) The payload data in OPU4 is extracted based on the Cm value; (6) All data of each packet are extracted to obtain N ODUks; (7) The payload data is extracted from the ODUk; (8) The valid data is extracted according to the mapping method to obtain the client signal.

2. The 127G-PM-QPSK signal analysis algorithm according to claim 1, characterized in that: The offset of the Cm value is obtained by XORing the JC values ​​of adjacent adjustment cycles, and the Cm value of the current cycle plus the offset is used as the Cm value of the next cycle.

3. The 127G-PM-QPSK signal analysis algorithm according to claim 1, characterized in that: The algorithm is applicable to ODUflex complex signal grouping and can extract the payload in the grouped signal and restore the session information.

Images