Robust Data Transmission Rate Allocation to Improve Energy Efficiency in 6G Networks

The future sixth-generation (6G) network is expected to support both sensing and communications. Since the sensing performance will highly rely on the residual battery of smart devices, energy efficiency is one of the main concerns in the design of 6G. Motivated by these facts, we design an energy efficient data transmission rate allocation approach for 6G networks. To have a more realistic deployment, we assume that perfect channel state information is not available. Imperfect channel state information (CSI) might waste energy sources or degrade quality of service (QoS). Thus, we apply the maximum likelihood estimation (MLE) method to estimate the true channel characteristics for a given set of observations. The proposed approach is robust against unknown channel statistics and allows adapting UEs transmission rate to the channel quality which reduce energy consumption and guarantees QoS. Both numerical analysis and simulation results confirm the effectiveness of the proposed work in terms of energy efficiency and throughput maximization.