Stochastic Design of Active RIS-Assisted Satellite Downlinks under Interference, Folded Noise, and EIRP Constraints

Active reconfigurable intelligent surfaces (RISs) can mitigate the double-fading loss of passive reflection in satellite downlinks. However, their gains are limited by random co-channel interference, gain-dependent amplifier noise, and regulatory emission constraints. This paper develops a stochastic reliability framework for active RIS-assisted satellite downlinks by modeling the desired and interfering channels, receiver noise, and RIS amplifier noise as random variables. The resulting instantaneous signal-to-interference-plus-noise ratio (SINR) model explicitly captures folded cascaded amplifier noise and reveals a finite high-gain SINR ceiling. To guarantee a target outage level, we formulate a chance-constrained max-SINR design that jointly optimizes the binary RIS configuration and a common amplification gain. The chance constraint is handled using a sample-average approximation (SAA) with a violation budget. The resulting feasibility problem is solved as a mixed-integer second-order cone program (MISOCP) within a bisection search over the SINR threshold. Practical implementation is enforced by restricting the gain to an admissible range determined by small-signal stability and effective isotropic radiated power (EIRP) limits. We also derive realization-wise SINR envelopes based on eigenvalue and l1-norm bounds, which provide interpretable performance limits and fast diagnostics. Monte Carlo results show that these envelopes tightly bound the simulated SINR, reproduce the predicted saturation behavior, and quantify performance degradation as interference increases. Overall, the paper provides a solver-ready, reliability-targeting design methodology whose achieved reliability is validated through out-of-sample Monte Carlo testing under realistic randomness and hardware constraints.

Balanced Performance Between Energy-Delay and Bit Error Rate in UAV Relay Networks

This paper presents a new strategy for simultaneously reducing energy consumption, transmission delays, and bit error rate in Unmanned Aerial Vehicle UAV networks. A UAV is fitted with a wireless Bidirectional Relay BR to enable coverage network extension and increase transmission throughput. The downside of the BR advantages is the delay in data transmission caused by the UAV movement. A consequence of this delay is increased total energy consumption, causing further degradation in bit error rate performance, especially at high SNR levels. In wireless communication, the trade-off between delay and energy consumption is, fortunately, possible to improve performance. Therefore, this study aims to enhance UAV network performance by reducing energy consumption, data transmission delay, and bit error rate. A multi-objective algorithm is employed to generate an adaptive optimal energy allocation strategy based on the balance between energy consumption and transmission delays. The results of theoretical analysis are illustrated with several examples. As herein demonstrated, the proposed solution effectively balances delay and energy efficiency in a customised system design and improves the bit error rate in UAV networks