Max-Min Fairness of CR-RSMA-Based UAV Relay-Assisted Emergency Communication Network With Limited User Energy

In post-disaster scenarios, it is challenging for affected users to transmit data as quickly as possible before their residual energy (RE) is exhausted. Besides, the problem of limited users' RE causes severe transmission delay unfairness within the network. In this paper, we propose a novel two-phase scheme, called energy-aware unmanned aerial vehicle (UAV) relay transmission (EURT), to balance transmission delay of users and network fairness. Specifically, in the first phase, we pair users two-by-two based on their RE and minimize the maximum transmission delay among all pairs by jointly optimizing the bandwidth allocation, transmit powers, and UAV altitude. In the second phase, we design a cognitive radio (CR) inspired rate-splitting multiple access (RSMA) scheduling strategy to obtain the optimal power splitting factor for each pair. This strategy considers the user with a lower RE value in each pair as the primary user (PU) and the other one as the secondary user (SU), then minimizes the transmission delay of the SU while ensuring the quality of service (QoS) of the PU. Furthermore, we propose a novel evaluation framework to explore the degree of impact of RE and channel state information (CSI) on network delay fairness. Simulation results demonstrate that: i) the proposed EURT algorithm effectively improves performance metrics of networks in terms of transmission delays, throughput, energy consumption and energy efficiency; ii) The proposed algorithm achieves a trade-off between the minimum delay and the optimal network fairness by adjusting the QoS threshold of the PU.