The article represents a model of radio signals as a periodically correlated stochastic process, which made it possible to implement a synphase method of effective detection of radio signals in telecommunication networks with noises. Based on the synphase processing method, a method and algorithm for detecting radio signals in telecommunication networks with noises is implemented by calculating correlation components as quantitative indicators that reliably reflect the fact of the presence/absence of a useful radio signal component. A computer (software) tool for synphase detection of radio signals in telecommunication networks with a graphical user interface is implemented in the Matlab environment. The process of synphase detection of radio signals in telecommunication networks with noise of different power which confirmed the correct functioning of the developed method and algorithm of synphase detection of radio signals.
The procedure of effective detection of the useful component of radio signals in telecommunication networks with interference is the main problem of radio signal preprocessing in the telecommunications industry. Basic developments in this direction are the works of V.A. Kotelnykov, V.I. Tikhonov and
Known algorithms for processing radio signals for their detection of a useful component in
telecommunication networks with interference are implemented using filtering methods [
Therefore, the use all PCSP arsenal for the development of a new method, algorithm and computer tool for processing radio signals for their detection in telecommunication networks with interference is actual problem.
2023 Copyright for this paper by its authors. 2. Mathematical representation telecommunication networks of the model of radio signals in
In the development process, the telecommunications network is the most vulnerable link that is affected by disturbances of various power (Fig. 1).
The mathematical representation of the model of radio signals is aimed at describing real signals, taking into account all the features of the influence of various types of interference on the network itself. In this case, the connection between the input and output signal is represented mathematically in the form of an expression:
K t st nk t , t R .
k 1 (1) where nk t - k-th additive interference affecting the network, in particular, the incoming radio signal st throughout the observation time.
The experimental implementation of a radio signal, in particular, on the example of an amplitudemodulated signal, is shown in Fig. 2.
All modulated radio signals in the process of their transmission are characterized by indicators of stochasticity and periodicity, which are through the influence of interference and the harmonic component in the modulation of radio signals.
Therefore, when implementing the method of processing radio signals in networks with noises, it is necessary to adequately present their model, which is a determining factor in the effectiveness of methods and means of detecting signals, in particular, their useful component.
These requirements are satisfied by a model of the type of periodically correlated stochastic
process, which has a powerful arsenal for processing radio signals and is suitable for their detection in
telecommunication networks with noises. Such evidence is substantiated in the work of
Khvostivska L.V. and L.M. Koval [
Radio signals in telecommunication networks with interference are represented as PCSP in the
form of an expression [
T , t R kZ where k t - the stochastic component of the radio signal in telecommunication networks with noises; - periodic component of the radio signal in telecommunication networks with a period indicator.
The mathematical presentation of the model of a radio signal in telecommunication networks with
noises through PCSP according to the energy theory of stochastic signals [
Synphase processing of the radio signal provides the process of estimating the correlation
components taking into account covariance statistics bt,u [
eik 2T t where (2) (3) (4) Bk u 1 Т
bˆt,uexp ik T 0 2
t dt ,
T
N 1 0 0
bˆ (t,u) t u kT t kT ,
k0
where T – radio signal period (calculated according to the methodology given in the work [
Figure 3 shows the structural sequence of the research process of detecting useful radio signals in telecommunication networks with noises.
The structural elements of the sequence are as follows: - Synphase processing of radio signals in telecommunication networks with noises according to expression (3), which calculates the detection rate in the form of correlation components Bk u .
- Evaluation of the calculated correlation components according to the form and values of which will ensure the process of detecting radio signals.
- Making a decision based on the form and indicators of the estimated correlation components regarding the presence/absence of useful radio signals in telecommunication networks with noises.
The algorithm for synphase radio signal processing in telecommunication networks with noises is shown in Fig. 4.
Start
The developed algorithm created prerequisites for the implementation of a computer tool for synphase processing as the basis of the method of synphase detection of radio signals in telecommunication networks with noises. The developed algorithm is also of practical importance for cyber-physical systems [12, 13].
The result of synphase detection of radio signals in telecommunication networks with noises in the form of calculated correlation components with the interference power level (dispersion level 0 V2) is shown in the form of a 3D implementation in Fig. 5.
(a) (b) Figure 5: The result of synphase detection of a radio signal at noise’s dispersion level of 0 V2: a) radio signal; b) components as a detection indicator
In this case, the radio signal is clearly localized (Fig. 6), as in the case without noises in Fig. 5.
The level of harmful dispersion was increased to 1.2 V2, which exceeds the level of the most useful radio signal, and the components shown in Fig. 7 were calculated. The result of the localization of the radio signal component is identical to the above results, that is, the detection is obvious without any difficulty.
From the calculated detection indicators in Fig. 5-7, it can be seen that the radio signal in telecommunication networks with noises is clearly localized, which ensures the process of its reliable and effective detection without any difficulty.
Therefore, the correlation components ensure the formation of logical and justified conclusions regarding the presence or absence of a useful radio signal (Fig. 5-7).
For a more detailed evaluation of the calculated correlation components Bk u , their averaged evaluation by components was used, as suggested by M.O. Khvostivskyi [11] according to the expression:
M k Bk u 1 Nk
Bk u , u 1, Nu , k 1, N k .
Nk k1 (5) where u –shift value; Nu – total number of components k; Nk – shift length.
The result of averaging radio signal components Bk u according to expression (5) at different levels of noises dispersion is shown in Fig. 8.
The estimated components through their averaging (Fig. 8) make it possible to compare the detection results in more detail than in the case of non-averaged components (Fig. 5-7), which ensures the process of effective and reliable detection of radio signals in telecommunication networks with noises.
Using MATLAB GUIDE, a computer tool with a graphic interface was developed to detect useful radio signals in a telecommunication network with noises (Fig. 9).
The implemented computer tool provides a procedure for automating the synphase detection of a useful radio signal in telecommunication networks with noises of different power.
The results of processing radio signals as a periodically correlated stochastic processes in telecommunication networks with noises in the form of averaged correlation components state that the developed synphase method, algorithm and computer tool organize the process of tracking and synphase detection of the presence of a useful radio signal component against the background of noises of different power. This fact indicates the effectiveness of the process of detecting useful radio signals as periodically correlated stochastic processes when using the synphase method.
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