ANALYSIS OF THE PROSPECTS FOR APPLYING THE STATE-SPACE METHOD IN MODERN MOBILE COMMUNICATION SYSTEMS

Abstract

Due to the rapid development of mobile networks, their integration into all
spheres of society, and a significant increase in signal complexity, modern processing methods are in a state
of continuous evolution. From a mathematical perspective, signal processing in 5/6G systems using MIMO
technologies is an extremely challenging task. Classical signal processing methods, such as Zero Forcing,
are characterized by a cubic increase in computational complexity. This makes it impossible to
simultaneously use the ultra-low latency scenario, uRLLC, with the ultra-high throughput scenario, eMBB.
This paper proposes an approach to signal processing using the state-space method. Through simulation
modeling, it has been proven that the transition from channel matrix inversion to state vector computation
allows for a reduction in computational complexity from cubic O(N3
), to quadratic O(N2
). Experimental
results for MIMO systems with up to 512 antennas demonstrate a significant reduction in the algorithm's
execution time. It is concluded that representing the dynamics of a multidimensional channel in the standard
state-space form ensures deterministic processing latency, allowing for an effective balance between the
requirements of ultra-high throughput (eMBB) and ultra-low latency (URLLC) in current and future mobile
communication systems.
Keywords: state-space, Massive MIMO, optimal reception, multidimensional signals, computational
complexity, Zero Forcing, 5G/6G, URLLC, eMBB

References
1. Л.Н. Беркман, Л.О. Комарова, О.І. Чумак. Системи електрозв’язку та сигнали.
Навчальний посібник. – Київ: ДУТ, 2015.
2. В. К. Стеклов, Л. Н. Беркман. Теорія електричного зв’язку. – Київ: Техніка, 2006. 552 с.
3. Recommendation ITU-R M.2160-0. Framework and overall objectives of the future
development of IMT for 2030 and beyond. Geneva : International Telecommunication Union, 2023.
19 p. URL: https://www.itu.int/rec/R-REC-M.2160-0-202311-I/en.
4. Jiang W., Han B., Habibi M. A., Schotten H. D. The Road Towards 6G: A Comprehensive
Survey // IEEE Open Journal of the Communications Society. 2021. Vol. 2. P. 334–366. DOI:
https://doi.org/10.1109/OJCOMS.2021.3057679.
5. Albreem M. A., Juntti M., Shahabuddin S. Massive MIMO Detection Techniques: A Survey
// IEEE Communications Surveys & Tutorials. 2019. Vol. 21, No. 4. P. 3109–3132. DOI:
https://doi.org/10.1109/COMST.2019.2935810.
6. Popovski P., Trillingsgaard K. F., Simeone O., Durisi G. 5G Wireless Network Slicing for
eMBB, URLLC, and mMTC: A Communication-Theoretic View // IEEE Access. 2018. Vol. 6. P.
55765–55779. DOI: https://doi.org/10.1109/ACCESS.2018.2872781.