## 5 Energy Efficiency and Sustainability
### Energy Efficiency in the Context of RIS and HAP Integration  
HAPs are used for various purposes, including telecommunications, surveillance, and environmental monitoring. However, the challenge lies in the energy constraints associated with sustaining operations at such altitudes. Traditional communication systems on HAPs often face limitations in terms of energy consumption, impacting their endurance and overall effectiveness. When equipped with RISs, these platforms can significantly improve their performance metrics, particularly regarding energy efficiency. Energy efficiency is critical to RIS-enhanced HAPs, and researchers have devoted considerable efforts to analyzing its impact [72; 102]. They have studied the energy efficiency of RIS-enhanced HAPs in various scenarios, such as multiple-input single-output (MISO) and MIMO networks. RIS technology significantly reduces energy consumption by optimizing various parameters such as time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, and the RIS energy reflection coefficient [65]. Analyzing the energy efficiency of RIS-enhanced HAPs involves various factors, such as transmit power, channel conditions, data rates, and the energy consumption of the RIS itself, which must be considered [117]. RIS placement, configuration, and optimization techniques also affect energy efficiency [118].  
In the context of RIS-enhanced HAPs, the multi-objective optimization approach involves the joint optimization of various parameters. This includes time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, and the energy reflection coefficient of the RIS. This comprehensive optimization scheme aims at maximizing energy efficiency while ensuring fair and equitable distribution of resources among users in the network [119]. The optimization framework offers a significant step towards realizing the full potential of RIS-enhanced HAPs in meeting the ever-increasing demands for wireless communication while fostering sustainability and fairness in wireless networks. Using RIS reduces the number of reflections in the channel, resulting in a favorable channel that requires less transmit power for a given data rate [120].  
Optimizing the multi-user transmit beamforming power requirement for the active user set, researchers have proposed computationally efficient algorithms to minimize network power consumption and improve energy efficiency [121]. Moreover, introducing RIS-aided networks has enhanced energy efficiency [122]. In RIS-aided networks, the joint optimization of active beamforming and phase shifter design has significantly improved system performance and energy efficiency [123]. To address the energy efficiency of RIS-enhanced HAPs, various algorithms [65] and optimization techniques [124] have been developed. One approach is optimizing resource allocation by formulating a convex optimization problem and proposing low-complexity sub-optimal algorithms. Optimizing the BS's precoding matrix and the reflecting surface's reflection coefficient has maximized the weighted minimum rate for all users to ensure network fairness and minimize energy consumption [65].