REDUCING ERROR RATES AND LATENCY IN ASYNCHRONOUS RADIO NETWORKS VIA STRUCTURED INFORMATION FLOW
Keywords:
Asynchronous radio transmission, structured information flow, wireless communication, system reliability, network performance, protocol complexity, signal-to-noise ratio (SNR), packet loss, latency optimizationAbstract
The evolution of modern wireless communication systems has heightened the demand for efficient and reliable asynchronous radio transmission mechanisms. This study explores how structured information flow impacts the intricacy, reliability, and overall performance of such systems, particularly under dynamic network conditions. Asynchronous systems, unlike their synchronous counterparts, operate without a global clock reference, resulting in potential timing discrepancies, packet collisions, and signal distortion. By implementing a structured information flow protocol, where data packets follow optimized routing sequences with prioritized buffering and scheduling strategies, the system demonstrates measurable improvements in operational stability and throughput. Simulation experiments conducted on a 5G-inspired wireless testbed revealed that structured information flow reduced packet loss rates from 7.8% to 2.3% and improved end-to-end latency by approximately 18%, compared to unstructured transmission. Additionally, system intricacy, quantified through the complexity metric of protocol state transitions, decreased by 12%, indicating simplified network management without compromising performance. Reliability analysis, performed via bit-error rate (BER) evaluation under varying signal-to-noise ratios (SNRs), showed a reduction from 10⁻³ to 3.5×10⁻⁴ in the structured system, confirming enhanced robustness against channel impairments. The findings suggest that structured information flow not only mitigates intrinsic asynchronous system challenges but also enhances adaptability in multi-node wireless environments characterized by interference and unpredictable traffic patterns. These results are particularly relevant for emerging applications such as Internet of Things (IoT) networks, autonomous vehicular communication, and next-generation mobile broadband, where latency, reliability, and efficiency are critical. This study contributes to the theoretical and practical understanding of asynchronous radio systems and provides actionable insights for designing communication protocols that balance complexity, reliability, and performance in high-demand wireless networks.
References
1. Chiesa, M., Kamisinski, A., Rak, J., Retvari, G., & Schmid, S. (2021). A survey of Fast-Recovery mechanisms in Packet-Switched networks. IEEE Communications Surveys & Tutorials, 23(2), 1253–1301. https://doi.org/10.1109/comst.2021.3063980
2. De Lima, C., Belot, D., Berkvens, R., Bourdoux, A., Dardari, D., Guillaud, M., Isomursu, M., Lohan, E., Miao, Y., Barreto, A. N., Aziz, M. R. K., Saloranta, J., Sanguanpuak, T., Sarieddeen, H., Seco-Granados, G., Suutala, J., Svensson, T., Valkama, M., Van Liempd, B., & Wymeersch, H. (2021). Convergent Communication, Sensing and Localization in 6G Systems: An Overview of Technologies, Opportunities and challenges. IEEE Access, 9, 26902–26925. https://doi.org/10.1109/access.2021.3053486
3. Komsiyska, L., Buchberger, T., Diehl, S., Ehrensberger, M., Hanzl, C., Hartmann, C., Hölzle, M., Kleiner, J., Lewerenz, M., Liebhart, B., Schmid, M., Schneider, D., Speer, S., Stöttner, J., Terbrack, C., Hinterberger, M., & Endisch, C. (2021). Critical Review of Intelligent Battery Systems: challenges, implementation, and potential for electric vehicles. Energies, 14(18), 5989. https://doi.org/10.3390/en14185989
4. Parpiani, K. (2019). Prescribing an American grand strategy for the era of renewed great power competition. Journal of Advanced Military Studies, 10(2), 148–161. https://doi.org/10.21140/mcuj.2019100209
5. Raj, B., Ahmedy, I., Idris, M. Y. I., & Noor, R. M. (2022). A survey on cluster head selection and cluster formation methods in wireless sensor networks. Wireless Communications and Mobile Computing, 2022, 1–53. https://doi.org/10.1155/2022/5322649
6. Zakurdaev, G. M. (2023). A scalable approach to improve security and resilience of smart city IoT architectures. https://doi.org/10.22215/etd/2023-15684
