  Large-scale cloud radio access network (LS-CRAN) is a highly promising
next-generation cellular network architecture whereby lots of base stations
(BSs) equipped with a massive antenna array are connected to a cloud-computing
based central processor unit via digital front/backhaul links. This paper
studies an asymptotic behavior of downlink (DL) performance of a LS-CRAN with
three practical constraints: 1) limited transmit power, 2) limited
front/backhaul capacity, and 3) limited pilot resource. As an asymptotic
performance measure, the scaling exponent of the
signal-to-interference-plus-noise-ratio (SINR) is derived for interference-free
(IF), maximum-ratio transmission (MRT), and zero-forcing (ZF) operations. Our
asymptotic analysis reveals four fundamental operating regimes and the
performances of both MRT and ZF operations are fundamentally limited by the UL
transmit power for estimating user's channel state information, not the DL
transmit power. We obtain the conditions that MRT or ZF operation becomes
interference-free, i.e., order-optimal with three practical constraints.
Specifically, as higher UL transmit power is provided, more users can be
associated and the data rate per user can be increased simultaneously while
keeping the order-optimality as long as the total front/backhaul overhead is
$\Omega(N^{\eta_{\rm{bs}}+\eta_{\rm{ant}}+\eta_{\rm{user}}+\frac{2}{\alpha}\rho^{\rm{ul}}})$
and $\Omega(N^{\eta_{\rm{user}}-\eta_{\rm{bs}}})$ pilot resources are
available. It is also shown that how the target quality-of-service (QoS) in
terms of SINR and the number of users satisfying the target QoS can
simultaneously grow as the network size increases and the way how the network
size increases under the practical constraints, which can provide meaningful
insights for future cellular systems.
