Large-scale cloud radio access networks: Fundamental asymptotic analysis

Abstract

Large-scale cloud radio access network (LS-CRAN) is a highly promising next-generation cellular network architecture whereby many 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 the asymptotic behavior of downlink (DL) performance of a LS-CRAN. 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. 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.