When RIS Meets GEO Satellite Communications: A New Sustainable Optimization Framework in 6G

Abstract

Low Earth Orbit (LEO) satellite networks are expected to play a crucial role in providing high-speed internet access and low-latency communication worldwide. However, some challenges can affect the performance of LEO satellite networks. For example, they can face energy and spectral efficiency challenges, such as high power consumption and spectral congestion, due to the increasing number of satellites. Furthermore, mobile ground users tend to operate with low directive antennas, which pose significant challenges in closing the LEO-toground communication link, especially when operating at a highfrequency range. To overcome these challenges, energy-efficient technologies like reconfigurable intelligent surfaces (RIS) and advanced spectrum management techniques like non-orthogonal multiple access (NOMA) can be employed. RIS can improve signal quality and reduce power consumption, while NOMA can enhance spectral efficiency by sharing the same resources among multiple users. This paper proposes an energy-efficient RIS-assisted downlink NOMA communication for LEO satellite networks. The proposed framework simultaneously optimizes the transmit power of ground terminals of the LEO satellite and the passive beamforming of RIS while ensuring the quality of services. Due to the nature of the considered system and optimization variables, the energy efficiency maximization problem is non-convex. In practice, obtaining the optimal solution for such problems is very challenging. Therefore, we adopt alternating optimization methods to handle the joint optimization in two steps. In step 1, for any given phase shift vector, we calculate satellite transmit power towards each ground terminal using the Lagrangian dual method. Then, in step 2, given the transmit power, we design passive beamforming for RIS by solving the semi-definite programming. We also compare our solution with a benchmark framework having a fixed phase shift design and a conventional NOMA framework without involving RIS. Numerical results show that the proposed optimization framework achieves 21.47% and 54.9% higher energy efficiency compared to the benchmark and conventional frameworks.

Reconfigurable Intelligent Surfaces Empowered THz Communication in LEO Satellite Networks

“…( 12). According to the central limit theorem (CLT), A follows a Gaussian distribution for N 1 with the mean and variance given in (18), where L 1/2 (•) stands for the Laguerre polynomial of degree 1/2. As A follows a Gaussian distribution, SNR is non-central chi-square distributed with one degree of freedom.…”

“…As detailed in [15], RISs can provide energy efficiency for the same QoS level. RISs are expected to be a key enabler for THz waves in small satellites of the future [16] due to the energy efficiency [17] and low hardware complexity [18] provided by RISs. In [19], an architecture for RIS-assisted LEO satellite communications with RISs deployed at satellite and ground nodes and cooperative passive beamforming are proposed.…”

Random Graph-Based M-QAM Classification for MIMO Systems

“…Softmax is employed in classification to widen the distance between classes when it gets to the output layer. A parallel hybrid network for the AMC problem is suggested in [40].…”

Precoding for High Throughput Satellite Communication Systems: A Survey

“…It has also been considered to enhance LEO inter-satellite links in the terahertz band in [277]. Further, RIS-assisted networks have been studied for GEO satellites in [278], where the RIS adjusts the phase of the signal from the satellite towards the ground user to boost the effective gain of the system. Therein, the transmit power of the satellite is jointly optimized with the phase shifts applied at the RIS to maximize the channel capacity.…”