Optimization of channel packet loss in wireless sensor communication systems using model predictive control

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