This paper investigates synchronization techniques for developing markerless telecommunication systems. In such systems, explicit markers are eliminated, which minimizes the amount of overhead. Markerless systems outperform traditional systems in tasks requiring high response speed and low latency. One of the key components of such systems is frame synchronization, which ensures correct identification and decoding of data packets at the receiving end without using explicit markers indicating the beginning or end of a packet. The study focuses on the effectiveness of frame synchronization techniques, since the accuracy and reliability of these techniques significantly affect the overall performance and stability of the system. Traditional synchronization techniques such as time synchronization, block counters, and checksums are analyzed. In addition, a new factorial coding technique is proposed that eliminates the need for explicit markers, thereby reducing the overhead and improving the channel efficiency. The results show that factorial coding improves synchronization accuracy, reduces latency, and provides better resilience to interference, making it a promising approach for next-generation markerless telecommunication systems.
Modern telecommunication systems are characterized by growing requirements for data transfer
speed, reliability and efficiency of network resource use. In the context of increasing traffic volumes
and the diversity of transmitted data, the task of developing methods that ensure fast and reliable
information transfer with minimal delays is becoming especially urgent [
These methods are a combination of various technologies and approaches aimed at optimizing
data transfer processes in telecommunication systems [
The main methods that are most often used include frame synchronization [
It is worth noting that these methods are based on the principle of using explicit markers to indicate the beginning and end of packets, error correction and other mechanisms that are most often used in traditional telecommunication systems. These systems were developed to ensure reliable and predictable data transmission in conditions of limited bandwidth and exposure of communication channels to various types of interference. Particular attention is paid to frame synchronization, since in traditional systems it ensures correct recognition of data packet boundaries. This is especially important for preventing errors associated with the loss or distortion of markers, which could lead to misinterpretation of data on the receiving side. Frame synchronization also helps traditional systems cope with noise and interference in the communication channel. Frame-level synchronization allows the system to quickly restore synchronization after errors occur, which improves the overall reliability of data transmission [19,20,21]. Many standardized communication protocols, such as Ethernet, GSM or Wi-Fi, use frame synchronization methods to ensure compatibility and reliability. These protocols are designed to operate in a variety of conditions and include time-tested methods such as the use of markers and checksums [22]. Frame synchronization in traditional systems is usually well documented and supported by a wide range of hardware and software. This simplifies the development and implementation of telecommunications systems, and ensures compatibility between different devices and networks.
However, if we consider traditional systems, there is a high probability of errors, interference and data loss.
The article proposes to study code synchronization methods for creating markerless systems. Such systems do not have explicit markers, which allows minimizing the amount of service information. Markerless systems outperform traditional ones in tasks that require high efficiency and low delays. One of the key components of such systems is frame synchronization, which ensures correct recognition and decoding of data packets on the receiving side without using explicit markers indicating the beginning and end of the packet.
The study of the efficiency of frame synchronization methods plays an important role in the creation of markerless telecommunication systems, since the overall performance and stability of the system depend on the accuracy and reliability of these methods. In this paper, the frame synchronization efficiency indicator is considered. Frame synchronization efficiency is understood as the ability of the system to correctly recognize the beginning and end of data frames in the information flow. Traditional frame synchronization methods, such as time synchronization, block counters and the use of checksums, are studied. A method with factorial coding is proposed that does not require explicit markers, which will reduce the amount of service information and increase the efficiency of channel use.
The study of the efficiency of frame synchronization methods for markerless telecommunication systems was carried out in several stages. The main attention was paid to the comparative analysis of traditional frame synchronization methods, such as time synchronization, block counters and the use of checksums and the factorial coding method.
At the first stage, key performance indicators of frame synchronization methods were determined, such as the noise level in the communication channel, bandwidth, and delays. The ability to dynamically change these parameters during experiments was also implemented to assess the stability of the methods to various transmission conditions.
At the second stage, modeling and data collection were carried out according to the selected parameters. The experimental setup includes software for modeling a telecommunication system and physical equipment, including computers and network devices connected through a configured switch. The software imitated data transmission between network nodes using the developed frame synchronization algorithm and factorial coding in the MATHLAB environment.
The third stage includes the analysis of data transmission results and the construction of an efficiency graph for each method.
Time synchronization ensures that time is coordinated between network nodes so that all participants in the data transfer process have the same time scale. The choice of parameters is shown in Figure 1, which includes the number of sending data blocks, the size of each data block, and the time interval between data blocks per second.
The principle of the method is important for preventing data transmission collisions and reducing errors. In simulation, this method shows high efficiency under stable network conditions, but its performance noticeably decreased with increasing time delays in the communication channel (Figure 2).
The "block counters" method allows tracking the serial numbers of transmitted data blocks. This approach ensures reliable synchronization even in conditions of significant interference, but requires complex algorithms for processing erroneous or lost blocks.
Here, the main parameters for data generation are set: the number of blocks (numBlocks) and the size of each block in elements (blockSize). These parameters determine the volume and structure of data for the experiment (Figure 4).
The generated data block with a counter is added to the general array “allDataWithCounters”. After generating and adding all data blocks to the general array, the data is sorted by the first column, which contains the block counters, using the “sortrows” function (Figure 5).
This allows the original sequence of blocks to be restored, even if they were “received” in a different order.
The code then outputs the sorted data blocks, showing their counters and contents, allowing the synchronization result to be visually seen (Figure 6).
In the synchronization method, "checksums" are used to confirm the integrity of blocks and their correct order [22,23]. The choice of parameters is shown in Figure 8.
This method showed high efficiency in detecting and correcting errors, but its performance depended on the checksum calculation algorithm. Initialization of the array for storing data blocks with checksums is shown in Figure 9.
Displaying all generated data blocks together with their checksums, simulating the process of their “sending” (Figure 10).
When diagnosing network or file problems, checksums can help determine whether an error occurred during data transmission or not (Figure 11).
Inseparable factorial coding telecommunication systems [24] use non-standard and redundant frame structures that do not provide a separate SFD field and can perform a transport function for transmitting short packets [25]. Since the lengths of all code words in an inseparable factorial code are equal, frame synchronization methods use a permutation of elements and M. The method proposed in [24] complements the processing of binary symbols obtained from the communication channel using a majority gate or n -bit majority scheme with correlation processing [26]. numbers in a set each element in this set with bits
In this paper, the frame synchronization system uses a permutation , which is a sequence of . A fixed-length binary code is used to encode , as shown in Table I[24].
2 3 4 5 6 7 0000 0001 0010 0011 0100 0101 0110 0111 8 9 10 11 12 12 14 15
According to [24], the criterion for choosing a synchronization word is the maximum value of the minimum Hamming distance between the binary representation of the permutation and each of its circular shifts. The correct synchronization probability [24] is:
The method of frame synchronization of an inseparable factorial code with a bit error probability close to 0.5 uses a comprehensive approach, including both theoretical modeling and practical implementation in the MATHLAB programming language. The initial data of the experiment are presented in Figure 13.
The probability of bit error (“P_e”) is set at 0.49 to get closer to the critical value of 0.5.
These parameters were chosen based on the need to clearly demonstrate the operation of the developed methods under high noise conditions (Figure 14).
For each data block, a checksum is calculated, which includes the sum of the values of the data block bits and their ordinal numbers, taken modulo 256. This allows for increased reliability of error detection by taking into account not only the states of the bits, but also their positions in the block.
The checksums are compared for the original and received data blocks. A discrepancy between the checksums indicates the presence of errors, after which the counter of detected errors “errorsDetected” is incremented (Figure 15).
At the end, the total number of detected errors relative to the total number of sent data blocks is output. This gives an idea of the effectiveness of the used checksum method under high probability conditions.
Assuming that there is noise in the communication channel, which affects the probability of an error in the transmission of individual bits, we set the task of determining the probability of successful synchronization of data blocks for different noise levels.
The key parameters for the simulation were: The probability of a bit error in the channel (P_e), varied from 0 to 0.5; The size of the data block (S), equal to 256 bits; The number of data blocks (N), equal to 1000.
Based on the results obtained, it was found that with an increase in the probability of a bit error, the probability of successful synchronization of a data block decreases significantly. The graph generated by the code (Figure 16) demonstrated an inversely proportional dependence of the probability of successful synchronization on the probability of a bit error.
In particular, when “P_e” was equal to 0.1, the probability of successful synchronization was quite high, but when “P_e” approached 0.5, the probability of successful synchronization tended to zero.
After performing a series of experiments for each synchronization method, a comparison of their efficiency was carried out (Figure 18).
In this paper, efficiency is considered as the probabilities of correct and false synchronization.
It was found that the checksum method showed the highest performance under conditions with a bit error probability of up to 0.3. However, with a further increase in "P_e", its performance decreased faster than that of the block counter method.
The time synchronization method turned out to be the least effective due to its high sensitivity to changes in data transmission delays, which was especially noticeable at high "P_e".
Block counters demonstrated the best overall error tolerance under conditions of high error probability, maintaining relatively high performance even at "P_e" close to 0.5.
In this paper, several frame synchronization methods for creating markerless telecommunication systems were investigated and analyzed. Traditional methods, such as time synchronization, block counters and the use of checksums, have demonstrated their reliability in conditions with a moderate level of interference and errors.
The experiments and their analysis not only revealed the most effective synchronization methods under conditions of high bit error probability, but also opened the way for future research aimed at further improving the efficiency and reliability of data transmission.
In the context of modern tasks that require high efficiency and minimal delays, traditional frame synchronization methods may not be effective enough. Markerless systems, which do not use explicit markers, offer significant advantages in these conditions.
The main contribution of this work is the development and proposal of a factorial coding method for frame synchronization in markerless systems. This method allows minimizing the amount of service information, reducing redundancy, and allows transmitting more useful data, which is especially important for high-speed communication systems. Thus, the proposed factorial coding method is promising for tokenless communication systems and can significantly improve their performance, especially in scenarios requiring high data rate and low latency.
This research has been/was/is funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan "AP23489168 Methods and protocols for secure information exchange based on factorial coding of data and transformations in finite matrix fields."
[9] J. Hamkins, Frame synchronization without attached sync markers, in 2011 Aerospace
Conference, pp. 1-7, 2011. doi: 10.1109/AERO.2011.5747327. [10] D. Tarchi, G. Corazza, A. Vanelli‐Coralli, Adaptive coding and modulation techniques for next generation hand-held mobile satellite communications, IEEE International Conference on Communications (ICC), 9 June 2013. doi:10.1109/ICC.2013.6655277. [11] S. Salih, M.M.A. Suliman, Implementation of adaptive modulation and coding techniques using
Matlab, Proceedings ELMAR-2011, pp. 137-139, 2011. [12] L. Srividya, P.N. Sudha, Adaptive Channel Coding to Enhance the Performance in Rayleigh Channel, Int. J. of Adv. Comput. Sci. and Appl., vol. 15, no. 6, pp. 504–511, 2024. doi: 10.14569/IJACSA.2024.0150652. [13] S. Kumari, L. Gahalod, S.Changlani, Study of Different Types of Error Detection and Correction Code in Wireless Communication, Int. J. of Scientific Res. in Sci., Eng. and Tech., pp. 448-455, 2022. doi: 10.32628/IJSRSET2293138. [14] P. Santini, M. Battaglioni, M. Baldi, and F.Chiaraluce, Analysis of the error correctioncapability of LDPC and MDPC codes under parallelbit-flipping decoding and application tocryptography, IEEE Trans. Communication, vol.68, no. 8, pp. 4648_4660, 2020. [15] K. Pearson, On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling, Philosophical Magazine, Series 5, vol. 50, no. 302, pp. 157–175, 1900. [16] M.Z. Yakubova, O.A. Manankova, K.A. Tashev, K.A., G.S.Sadikova, Methodology of the determining for Pearson's criterion based on researching the value of delays in the transmitting of information over a multiservice network, 2020 International Conference on Information Science and Communications Technologies, ICISCT 2020, 2020. doi: 10.1109/ICISCT50599.2020.9351419. [17] B. Lee, S. Park, D. J. Love, H. Ji, and B. Shim, Packet Structure and Receiver Design for Low Latency Wireless Communications With Ultra-Short Packets, in IEEE Transactions on Communications, vol. 66, no. 2, pp. 796-807, Feb. 2018, doi: 10.1109/TCOMM.2017.2755012. [18] E. Faure, A. Shcherba, B. Stupka, Permutation-based frame synchronisation method for short packet communication systems, In: Proc. 11th IEEE Intl. Conf. on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Cracow, Poland, 22-25 Sept., p. 1073–1077. [19] E. Faure, V. Shvydkyi, A. Shcherba, O. Kharin, B. Stupka, Method of cyclic synchronization based on permutations, Bull. Cherkasy State Technol. Uni., vol. 4, November 2020, pp. 67–76. doi: 10.24025/2306-4412.4.2020.222439. [20] J. Al-Azzeh, E. Faure, A. Shcherba and B. Stupka, Permutation-based frame synchronization method for data transmission systems with short packets, Egypt. Inform. J., vol. 23, no. 3, September 2022, pp. 529–545. doi: 10.1016/j.eij.2022.05.005. [21] E. Faure, A. Shcherba, Y. Vasiliu, and A. Fesenko, Cryptographic key exchange method for data factorial coding, in CEUR Workshop Proceedings, vol. 2654, pp. 643-653, 2020. [22] E. Faure, A. Shcherba, A. Kharin, Factorial code with a given number of inversions, Radio
Electron. Comput. Sci. Control, vol. 2, no. 2, pp. 143–53, 2018. [23] E. Faure, V. Shvydkyi, A. Lavdanskyi, O. Kharin, Methods of factorial coding of speech signals,
Radio Electron. Comput. Sci. Control, vol.4, no. 4, pp.186–98, 2019. [24] J.S. Al-Azzeh, B. Ayyoub, E. Faure, V. Shvydkyi, O. Kharin, A. Lavdanskyi, Telecommunication Systems with Multiple Access Based on Data Factorial Coding, in International Journal on Communications Antenna and Propagation (IRECAP), vol. 10, no. 2, pp. 102-113, 2020, doi: 10.15866/irecap.v10i2.17216. [25] G. Durisi, T. Koch, and P. Popovski, Toward Massive, Ultrareliable, and Low-Latency Wireless
Communication with Short Packets, Proceedings of the IEEE, vol. 104, no. 9, pp. 1711-1726, 2016. [26] K.-U. Schmidt, Low-correlation sequences, Des. Codes Cryptog., vol. 78, no. 1, pp. 237–267, 2016. doi: 10.1007/s10623-015-0154-7.