  Low earth orbit (LEO) satellite systems with sensing functionality are
envisioned to facilitate global-coverage service and emerging applications in
6G. Currently, two fundamental challenges, namely, inter-beam interference
among users and power limitation at the LEO satellites, limit the full
potential of the joint design of sensing and communication. To effectively
control the interference, a rate-splitting multiple access (RSMA) scheme is
employed as the interference management strategy in the system design. On the
other hand, to address the limited power supply at the LEO satellites, we
consider low-resolution quantization digital-to-analog converters (DACs) at the
transmitter to reduce power consumption, which grows exponentially with the
number of quantization bits. Additionally, optimizing the total energy
efficiency (EE) of the system is a common practice to save the power. However,
this metric lacks fairness among users. To ensure this fairness and further
enhance EE, we investigate the max-min fairness EE of the RSMA-assisted
integrated sensing and communications (ISAC)-LEO satellite system. In this
system, the satellite transmits a quantized dual-functional signal serving
downlink users while detecting a target. Specifically, we optimize the
precoders for maximizing the minimal EE among all users, considering the power
consumption of each radio frequency (RF) chain under communication and sensing
constraints. To tackle this optimization problem, we proposed an iterative
algorithm based on successive convex approximation (SCA) and Dinkelbach's
method. Numerical results illustrate that the proposed design and RSMA
architecture outperforms strategies maximizing the total EE of the system,
space-division multiple access (SDMA), and orthogonal multiple access (OMA) in
terms of max-min fairness EE and the communication-sensing trade-off.
