Eastern-European Journal of Enterprise Technologies | 2026
Authors: Ormanbekova A.; Khabay A.; Tuleshov Y.; Sarsenbayev N.; Julayeva Z.; Ibekeyev S.; Abulkhanova M.; Tlegenov A.; Igen M.
DOI: 10.15587/1729-4061.2026.352116
Journal: Eastern-European Journal of Enterprise Technologies
Year: 2026
Publisher: Technology Center
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
The object of the study is an IEEE 802.15.4 (2.4 GHz) wireless networked control system (WNCS) closing the loop over a wireless sensor network. Fading and interference increase packet loss and delay, reducing stability margins and control quality. The unresolved problem is the lack of a unified end-to-end (E2E) loss model that links PHY signal quality, multi-hop routing and medium access to closed-loop behavior and can be embedded into controller synthesis. An SINR-based channel model (path loss, lognormal shadowing, multipath fading) is mapped to BER and packet error probability; E2E loss for single-hop and multi-hop routes is obtained using Bernoulli and finite-state Markov (FSMC) processes. For verification, original packet traces are captured with an IEEE 802.15.4 sniffer/logger and stored before processing (timestamp, node identifier, sequence number, RSSI/LQI and delivery outcome) to compute PER, latency and burstiness and to parameterize the SINR-to-PER mapping and loss models. Simulations show that TDMA/TSCH achieves up to 40% lower loss than CSMA/CA, while E2E loss rises from 3% to 32% as hop count increases from 1 to 8. An MPC-based co-design jointly adapts transmit power, sampling period and retransmissions. Compared with a fixed-parameter LQR baseline, E2E PER is reduced from 4.45% to 3.66%, average delay from 0.20 s to 0.12 s, and integral absolute error by 50%. The gains are attributed to reduced contention under TDMA scheduling and predictor-driven MPC adaptation. The approach targets industrial monitoring and control with fixed sampling, slowly varying interference and static multi-hop topologies, where parameters can be identified offline and used for online MPC adaptation Copyright © 2026, Authors.
Bernoulli process; CSMA/CA; finite-state Markov chain; MPC; packet loss; SINR; TDMA; wireless sensor network; WNCS