Minimizing Energy Consumption in 6G Assisted Holographic Communication

6G holographic communication requires massive data rates together with stringent Quality of Service (QoS) requirements which demands energy efficient resource utilization for sustainable energy usage. This work introduces an energy distribution strategy to optimize 6G base station sustainability for holographic communication from energy harvesting sources. The problem is modeled as an LP optimization problem. We propose a greedy heuristic algorithm for local optimal solution which performs successive energy distribution by moving its "energy" usage between scheduling slots. The study evaluates the efficacy of the proposed method by comparing it to the optimal results obtained from Linear Programming (LP) optimization and a random generic energy distribution baseline. Simulation results show that our greedy heuristic algorithm leads to enhanced energy efficiency which delivers close to the performance of the LP optimization while minimizing computational requirements. The proposed framework creates the groundwork for sustainable and energy-aware resource management solutions for default 6G holographic networks.