  This study introduces two innovative methodologies aimed at augmenting energy
efficiency in satellite-to-ground communication systems through the integration
of multiple Reflective Intelligent Surfaces (RISs). The primary objective of
these methodologies is to optimize overall energy efficiency under two distinct
scenarios. In the first scenario, denoted as Ideal Environment (IE), we enhance
energy efficiency by decomposing the problem into two sub-optimal tasks. The
initial task concentrates on maximizing power reception by precisely adjusting
the phase shift of each RIS element, followed by the implementation of
Selective Diversity to identify the RIS element delivering maximal power. The
second task entails minimizing power consumption, formulated as a binary linear
programming problem, and addressed using the Binary Particle Swarm Optimization
(BPSO) technique. The IE scenario presupposes an environment where signals
propagate without any path loss, serving as a foundational benchmark for
theoretical evaluations that elucidate the systems optimal capabilities.
Conversely, the second scenario, termed Non-Ideal Environment (NIE), is
designed for situations where signal transmission is subject to path loss.
Within this framework, the Adam algorithm is utilized to optimize energy
efficiency. This non ideal setting provides a pragmatic assessment of the
systems capabilities under conventional operational conditions. Both scenarios
emphasize the potential energy savings achievable by the satellite RIS system.
Empirical simulations further corroborate the robustness and effectiveness of
our approach, highlighting its potential to enhance energy efficiency in
satellite-to-ground communication systems.
