High-Altitude Platform (HAP) and Low-Altitude Platform (LAP) Networks with Rate-Splitting Multiple Access (RSMA): A Survey of Recent Research

In this article, we explore a new approach to resource allocation in multi-user downlink wireless networks, which can significantly improve the sum-rate of the system while ensuring interference alignment. The proposed algorithm is based on the alternating optimization (AO) method and guarantees the convergence of the sum-rate by repeating the optimization process until convergence is reached.
To begin with, we define the problem at hand: given a set of multiple users, design an efficient resource allocation strategy that maximizes the sum-rate while reducing interference among the users. The proposed solution leverages the rate-splitting and power allocation techniques to achieve this goal.
The article then delves into the system model, which takes into account the imperfect availability of channel state information (CSI) at the central unit (CU). The authors demonstrate that by using norm-bounded models, the problem can be solved even in the presence of imperfect CSI.
Next, the authors propose an AO-based algorithm to solve the optimization problem. The algorithm is designed to iteratively adjust the sets of orthogonal channels and power allocation factors until convergence is reached. Each iteration consists of two steps: first, the algorithm computes the optimal rate and power allocation for each user based on the current channel conditions; second, it updates the channel assignment and power allocation factors based on the computed rates and interference considerations.
The authors evaluate the performance of their proposed algorithm through simulations, comparing it to existing resource allocation schemes. The results demonstrate that the AO-based algorithm can significantly improve the sum-rate of the system while ensuring interference alignment. In fact, the proposed scheme achieves a 30% increase in sum-rate compared to the benchmark schemes.
Finally, the authors highlight the practical implications of their findings and discuss potential extensions of the proposed approach. They note that the algorithm can be easily integrated with other techniques, such as joint optimization of transmit power and bit allocation, to further improve system performance.
In conclusion, this article provides a valuable contribution to the field of wireless communication by proposing an efficient resource allocation scheme for multi-user downlink networks. By leveraging the rate-splitting and power allocation techniques, the proposed algorithm can significantly improve the sum-rate while ensuring interference alignment. The authors provide a thorough analysis of their proposal and demonstrate its effectiveness through simulations, making this work a valuable reference for researchers and practitioners in the field.