arXiv subjects

Hoang D. Le

Publications and source records attributed to Hoang D. Le.

3 recordsLinked to original sources

arXiv2026

Energy Efficiency Maximization for Integrated Sensing and Communications in Satellite-UAV MIMO Systems

This paper investigates energy efficiency maximization in an integrated sensing and communication framework for satellite-UAV MIMO systems, where a LEO satellite and a UAV simultaneously serve ground users and perform target sensing. Both the satellite and UAV are equipped with uniform planar arrays of transmit antennas, enabling a distributed multi-user and multi-target architecture. We derive the achievable downlink throughput by considering that the high-altitude satellite maintains a line-of-sight (LoS) link with users, while adopting a probabilistic model for the UAV that accounts for the likelihood of both LoS and non-line-of-sight conditions. The energy efficiency maximization problem is formulated as a complex non-convex optimization problem, subject to power constraints, quality of service (QoS) requirements, and beampattern gain constraints for accurate sensing. To tackle this challenge, we propose an efficient alternating optimization algorithm capable of handling the complex search space and QoS guarantees. Numerical results across diverse scenarios with multiple users demonstrate that the proposed method achieves high energy efficiency while meeting both communication and sensing performance targets.

cs.IT↗

arXiv2025

Multi-user Visible Light Communications with Probabilistic Constellation Shaping and Precoding

This paper proposes a joint design of probabilistic constellation shaping (PCS) and precoding to enhance the sum-rate performance of multi-user visible light communications (VLC) broadcast channels subject to signal amplitude constraint. In the proposed design, the transmission probabilities of bipolar $M$-pulse amplitude modulation ($M$-PAM) symbols for each user and the transmit precoding matrix are jointly optimized to improve the sum-rate performance. The joint design problem is shown to be a complex multivariate non-convex problem due to the non-convexity of the objective function. To tackle the original non-convex optimization problem, the firefly algorithm (FA), a nature-inspired heuristic optimization approach, is employed to solve a local optima. The FA-based approach, however, suffers from high computational complexity. Thus, using zero-forcing (ZF) precoding, we propose a low-complexity design, which is solved using an alternating optimization approach. Additionally, considering the channel uncertainty, a robust design based on the concept of end-to-end learning with autoencoder (AE) is also presented. Simulation results reveal that the proposed joint design with PCS significantly improves the sum-rate performance compared to the conventional design with uniform signaling. For instance, the joint design achieves $\mathbf{17.5\%}$ and $\mathbf{19.2\%}$ higher sum-rate for 8-PAM and 16-PAM, respectively, at 60 dB peak amplitude-to-noise ratio. Some insights into the optimal symbol distributions of the two joint design approaches are also provided. Furthermore, our results show the advantage of the proposed robust design over the non-robust one under uncertain channel conditions.

eess.SY↗

arXiv2024

Joint Design of Probabilistic Constellation Shaping and Precoding for Multi-user VLC Systems

This paper proposes a joint design of probabilistic constellation shaping (PCS) and precoding to enhance the sum-rate performance of multi-user visible light communications (VLC) broadcast channels subject to signal amplitude constraint. In the proposed design, the transmission probabilities of bipolar $M$-pulse amplitude modulation ($M$-PAM) symbols for each user and the transmit precoding matrix are jointly optimized to improve the sum-rate performance. The joint design problem is shown to be a complex non-convex problem due to the non-convexity of the objective function. To tackle the problem, the firefly algorithm (FA), a nature-inspired heuristic optimization approach, is employed to solve a local optima to the original non-convex optimization problem. The FA-based approach, however, suffers from high computational complexity. Therefore, we propose a low-complexity design based on zero-forcing (ZF) precoding, which is solved using an alternating optimization (AO) approach. Simulation results reveal that the proposed joint design with PCS significantly improves the sum-rate performance compared to the conventional design with uniform signaling. Some insights into the optimal symbol distributions of the two joint design approaches are also provided.

eess.SY↗