  We consider the potential for positioning with a system where antenna arrays
are deployed as a large intelligent surface (LIS), which is a newly proposed
concept beyond massive-MIMO where future man-made structures are electronically
active with integrated electronics and wireless communication making the entire
environment \lq\lq{}intelligent\rq\rq{}. In a first step, we derive
Fisher-information and Cram\'{e}r-Rao lower bounds (CRLBs) in closed-form for
positioning a terminal located perpendicular to the center of the LIS, whose
location we refer to as being on the central perpendicular line (CPL) of the
LIS. For a terminal that is not on the CPL, closed-form expressions of the
Fisher-information and CRLB seem out of reach, and we alternatively find
approximations of them which are shown to be accurate. Under mild conditions,
we show that the CRLB for all three Cartesian dimensions ($x$, $y$ and $z$)
decreases quadratically in the surface-area of the LIS, except for a terminal
exactly on the CPL where the CRLB for the $z$-dimension (distance from the LIS)
decreases linearly in the same. In a second step, we analyze the CRLB for
positioning when there is an unknown phase $\varphi$ presented in the analog
circuits of the LIS. We then show that the CRLBs are dramatically increased for
all three dimensions but decrease in the third-order of the surface-area.
Moreover, with an infinitely large LIS the CRLB for the $z$-dimension with an
unknown $\varphi$ is 6 dB higher than the case without phase uncertainty, and
the CRLB for estimating $\varphi$ converges to a constant that is independent
of the wavelength $\lambda$. At last, we extensively discuss the impact of
centralized and distributed deployments of LIS, and show that a distributed
deployment of LIS can enlarge the coverage for terminal-positioning and improve
the overall positioning performance.
