EVALUATING THE IMPACT OF CROSS-CORRELATION PROPERTIES OF COMPLEX SIGNALS ON THE CHARACTERISTICS OF SMART RADIO SYSTEMS
DOI:
https://doi.org/10.18372/2310-5461.61.18511Keywords:
smart radio, complex signals, pseudorandom sequences, Gold sequences, Galois sequences, Kiosaki sequence, correlation, interference, spectral efficiencyAbstract
The article discusses modern problems and prospects for the development of "smart radio" systems using complex signals for effective use of the radio frequency spectrum. Cognitive radio systems use complex signals to efficiently use the radio frequency spectrum. It is emphasized that the ensemble size of complex signals is a key factor that affects various system characteristics such as immunity, data transmission efficiency, and spectral efficiency. Various methods can be used to increase the ensemble size of complex signals, including the use of pseudo-random sequences with low levels of sidelobes in the cross-correlation function, new complex signal generation algorithms (e.g., based on artificial intelligence), and new coding techniques that allow for increased ensemble size. without compromising data transmission efficiency.
The choice of a specific approach to increasing the size of the ensemble of complex signals depends on the specific requirements of the cognitive telecommunication system. An important task is the development of new methods of generating complex signals with high interference-resistant properties, which allow to increase the size of the ensemble without compromising the quality of service. This task is important for the development of next-generation "smart radio" systems.
The analysis of various methods of increasing the size of the ensemble of complex signals is presented. The maximum correlation immunity is calculated for different lengths of sequences and the results of research for five sequences are given: pseudorandom noise, nonlinear sequence, Galois sequence, Gold sequence and Kiyosaki sequence. This information can be used to select the optimal sequence taking into account the specific requirements of "smart radio" systems. The conclusions of the article can make a valuable contribution to the development of effective and productive telecommunication systems for future generations of "smart radio".
References
Lysechko V.P. Method for Generating Ensembles of Complex Signals Based on Sequences with Minimal Energy Interaction. Systems of Armament and Military Equipment. 2005. Issue No. 1 (1). Pp. 65-68.
Lysechko V.P., Stepanenko Y.G. Method for Combating Intrasystem Interference in Code Division Multiple Access Communication Systems. Radioelectronic and Computer Systems. 2010. Issue 5(46). P. 277–281.
Lysechko V. P., Stepanenko Y.G., Kachurovskyi H.N. Method for Expanding the Ensemble Volume of Short Video Pulse Sequences with Low Levels of Mutual Correlation. Collection of Scientific Papers of the Ukrainian State Academy of Railway Transport. 2010. Issue 116. P. 100–106.
Indyk S. V., Lysechko V. P., Zhuchenko O. S., Kitov V. S. The formation method of complex signals ensembles by frequency filtration of pseudo-random sequences with low interaction in the time domain. Radio Electronics, Computer Science, Control. 2020. Issue 4 (55). P. 7 – 15. DOI 10.15588/1607-3274-2020-4-1.
Petryshyn L.B. Theoretical Foundations of Form Transformation and Digital Information Processing in the Galois Basis: [Educational Manual]. Kyiv: IZiMN MOU, 1997. 237 p.
Prykhodko S.I., Shtompel M.A., Zhuchenko O.S., Lysechko V.P., Shuvalova Yu.S. Research on the Effectiveness of the Adaptive Decoding Method for Algebraic Convolutional Interleaving Codes. Information and Control Systems in Railway Transport. 2019. No. 2. P. 13–18.
Setoodeh P. Haykin S. Fundamentals of cognitive radio. Hoboken: John Wiley & Sons. 2017. 207 p. DOI:10.1002/9781119405818.
Arslan. H., Arslan Y. Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems. 2007. Springer. 2007. P. 327. ISBN 978-1-4020-5541-6.
Chien W.B., Yang C.K., Huang Y.H. Energy–saving cooperative spectrum sensing processor for cognitive radio system. IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 58(4), 2011. PP. 711–723.