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This paper surveys the optimization frameworks and performance analysismethods for large intelligent surfaces (LIS), which have been emerging asstrong candidates to support the sixth-generation wireless physical platforms(6G). Due to their ability to adjust the behavior of interactingelectromagnetic (EM) waves through intelligent manipulations of the reflectionsphase shifts, LIS have shown promising merits at improving the spectralefficiency of wireless networks. In this context, researchers have beenrecently exploring LIS technology in depth as a means to achieve programmable,virtualized, and distributed wireless network infrastructures. From a systemlevel perspective, LIS have also been proven to be a low-cost, green,sustainable, and energy-efficient solution for 6G systems. This paper providesa unique blend that surveys the principles of operation of LIS, together withtheir optimization and performance analysis frameworks. The paper firstintroduces the LIS technology and its physical working principle. Then, itpresents various optimization frameworks that aim to optimize specificobjectives, namely, maximizing energy efficiency, sum-rate, secrecy-rate, andcoverage. The paper afterwards discusses various relevant performance analysisworks including capacity analysis, the impact of hardware impairments oncapacity, uplink/downlink data rate analysis, and outage probability. The paperfurther presents the impact of adopting the LIS technology for positioningapplications. Finally, we identify numerous exciting open challenges forLIS-aided 6G wireless networks, including resource allocation problems, hybridradio frequency/visible light communication (RF-VLC) systems, healthconsiderations, and localization.

Intelligent Surfaces for 6G Wireless Networks: A Survey of Optimization and Performance Analysis Techniques