# Study and Analysis of Interference Signals of the LTE System of the GNSS Receiver
## 2 Criteria for Evaluating Solutions of Noise Elimination in a GNSS Receiver  
Both the detection methods and the methods of reducing the impact of noise coming from the GNSS receiver and their impact on the operation of the receiver can be assessed in terms of the complexity of their practical implementation and effectiveness. However, this method of assessment is very general and most often insufficient from the point of view of the recipient/user of the offered system. Then, it is necessary to make a more measurable evaluation in the form of numerical parameter values.  
Due to the very specific and innovative nature of this type of solutions, no standard set of assessment of such parameters has been established so far, so the authors of this article have attempted to define them. These parameters are universal in nature, which means that they are not only used to assess the effectiveness of a specific system analyzed in this paper but can also be used to compare other anti-noise solutions.  
The authors of this article propose the following approach to the issue of assessing the effectiveness of the noise suppression system. It should be noted that the detection of noise can be assessed by analogy to the parameters used in radiolocation, where the detection process involves the signal with the noise included and not the impulse reflected from the object as in the case of radar. The basic terms of the radiolocation theory are the probability of detection \(P_{o}\) and the probability of misidentification of a PRN (Pseudo Random Noise) signal, i.e., a pseudo random signal produced by a satellite.  
The first informs about how many cases there are in which the noise will be correctly detected, and it is desirable to make it as high as possible. In turn, the second one describes how often the system will signal noise detection in the GNSS receiver, and the values of both these probabilities depend, among others, on the determined detection threshold.  
When choosing the threshold, it is necessary to make a compromise between \(P_{d}\) and \(P_{a}\). Depending on the desired properties, it is possible to take the lower limit of the acceptable \(P_{o}\) or limit \(P_{a}\) from the top. In addition to the threshold, the probability of detection is influenced by factors depending on the selected detection method. In the case of the method of comparing phase delays adopted here, the increase in the estimation error of these delays, is caused, among others, by a decrease in the SNR (signal-to-noise ratio), which is the signal processed in the GNSS receiver.  
When assessing the effectiveness of noise elimination methods, it is first of all necessary to determine to what extent this elimination affects the number of true and incomplete navigation signals and their \(\frac{C}{N_{0}}\) parameter values. Noise elimination methods based on the processing of received GNSS signals should have two features. Firstly, they strongly suppress signals from external devices (LTE receivers) or separate them from useful signals.  
Secondly, it is important to enable the proper functioning of the GNSS receiver and ensure the availability of the location service based on the processed signal. In the case of the zero control method, the suppression of an unwanted signal depends on the direction of signal arrival and the estimation error of this direction, which is a function of, among others, \(\frac{C}{N_{0}}\), the ratio of this signal.  
In turn, the measure of the availability of the location service is the probability of the visibility of a certain number of satellites. They can be statistically determined as the percentage of time that an anti-noise receiver is able to receive a given number of true GPS (Global Positioning System) signals, assuming there are no obstructions in the propagation paths between the satellites and the antenna of the receiver.