  This paper surveys the optimization frameworks and performance analysis
methods for large intelligent surfaces (LIS), which have been emerging as
strong candidates to support the sixth-generation wireless physical platforms
(6G). Due to their ability to adjust the behavior of interacting
electromagnetic (EM) waves through intelligent manipulations of the reflections
phase shifts, LIS have shown promising merits at improving the spectral
efficiency of wireless networks. In this context, researchers have been
recently exploring LIS technology in depth as a means to achieve programmable,
virtualized, and distributed wireless network infrastructures. From a system
level perspective, LIS have also been proven to be a low-cost, green,
sustainable, and energy-efficient solution for 6G systems. This paper provides
a unique blend that surveys the principles of operation of LIS, together with
their optimization and performance analysis frameworks. The paper first
introduces the LIS technology and its physical working principle. Then, it
presents various optimization frameworks that aim to optimize specific
objectives, namely, maximizing energy efficiency, sum-rate, secrecy-rate, and
coverage. The paper afterwards discusses various relevant performance analysis
works including capacity analysis, the impact of hardware impairments on
capacity, uplink/downlink data rate analysis, and outage probability. The paper
further presents the impact of adopting the LIS technology for positioning
applications. Finally, we identify numerous exciting open challenges for
LIS-aided 6G wireless networks, including resource allocation problems, hybrid
radio frequency/visible light communication (RF-VLC) systems, health
considerations, and localization.
