# Communication Fault Maintenance Decision of Information System Based on Inverse Symmetry Algorithm
## 1 Introduction  
With the improvement of the automatic operation level of information systems and the development of communication technology, information systems have the ability to transmit and obtain fault information online in the form of data communication. Many institutions have already completed or are building communication protection fault information systems, and many companies have developed corresponding products [1]. As an immature product, the communication fault maintenance system has many problems such as inconsistent traffic regulations, inconsistent data structures, and inconsistent protection information. Classical communication theory usually assumes that the noise in the channel is white Gaussian noise, and most of the current wireless communication systems have artificial noise with strong correlation, whose power far exceeds natural noise [2]. They believe that noise is not subject to Gaussian distribution and has a strong correlation. Using classic theory to analyze modern communication systems will bring large errors. Therefore, it is significant to study the channel model and noise cancellation methods under the noise of communication faults in information systems. The inverse symmetric method (PISM) uses the correlation between band-limited noise and its digital features to eliminate noise. It can extract weak signals from strong noise and greatly improve the signal-to-noise ratio. At present, there are many kinds of communication methods that can communicate under the condition of small signal-to-noise ratio, such as DSSS (Spread Spectrum), FHSS (Frequency-Hopping Spread Spectrum), etc., but they are all completed under the premise of greatly expanding the bandwidth. Many people in China and abroad are looking for new ways of communication, in order to save bandwidth and communicate in a strong noise environment [3; 4]. There are three methods to overcome the strong noise, and all of them can communicate when the SNR (SIGNAL-NOISE RATIO) is less than one. The first is the \"spectrum inversion method\" proposed by [PERSON] et al. in October 1979. The second is the \"Monett mixing method\" proposed by [PERSON] in March 2000. The third is the \"anti-relative law\" proposed by China, all of which have been patented. The signal submerged in noise can be detected by spectrum inversion, Monett mixing, and anti-relative symmetry. The spectrum inversion method makes use of the uncorrelation of inversion noise and non-inversion noise, while the inverse relative multiplication uses the correlation of band limited noise and its digital characteristics to eliminate noise. Because most channels belong to the constant parameter channel, that is, noise belongs to stationary or wide stationary random process [5], its digital characteristics do not change with time. When we divide the channel in the frequency domain or time domain, the noise between adjacent frequency bands or adjacent time slots has a strong statistical correlation. Both the spectrum inversion method and the anti-relative method can improve the signal-to-noise ratio, but the equipment of the anti-relative method is simpler. Both the Monett mixing method and the anti-relativism method make use of the fact that the noise and the signal are uncorrelated. The Monett mixer can greatly improve the signal-to-noise ratio, and it can display its advantages, especially in microwave communication. The spectrum inversion method is suitable for military wireless communication with double sided pseudo noise signal. The anti-relative symmetry method and Monett mixing method are applicable to aerospace communication and portable mobile communication [6]. These three new methods can make the equipment smaller, lighter, and more energy-efficient, thus prolonging the battery life of cellular mobile phones. All these three technologies are beyond the theoretical upper bound of the Shannon formula and have a very broad application prospect.