  The integration of a near-space information network (NSIN) with the
reconfigurable intelligent surface (RIS) is envisioned to significantly enhance
the communication performance of future wireless communication systems by
proactively altering wireless channels. This paper investigates the problem of
deploying a RIS-integrated NSIN to provide energy-efficient, ultra-reliable and
low-latency communications (URLLC) services. We mathematically formulate this
problem as a resource optimization problem, aiming to maximize the effective
throughput and minimize the system power consumption, subject to URLLC and
physical resource constraints. The formulated problem is challenging in terms
of accurate channel estimation, RIS phase alignment, theoretical analysis, and
effective solution. We propose a joint resource allocation algorithm to handle
these challenges. In this algorithm, we develop an accurate channel estimation
approach by exploring message passing and optimize phase shifts of RIS
reflecting elements to further increase the channel gain. Besides, we derive an
analysis-friend expression of decoding error probability and decompose the
problem into two-layered optimization problems by analyzing the monotonicity,
which makes the formulated problem analytically tractable. Extensive
simulations have been conducted to verify the performance of the proposed
algorithm. Simulation results show that the proposed algorithm can achieve
outstanding channel estimation performance and is more energy-efficient than
diverse benchmark algorithms.
