Semi-Static Modulation Compression Optimization for Next Generation RANs

Abstract

Next generation Radio Access Networks (RANs) consider virtualized architectures in which base station functions are distributed in different logical nodes that are connected through fronthaul links. To reduce the required fronthaul capacity, modulation compression is considered as a key enabler. Modulation compression achieves fronthaul capacity reduction at the cost of reducing the maximum modulation order that can be used over the air interface, thus creating a cell-fronthaul trade-off. The trade-off is further accentuated and needs to be optimized appropriately when multiple cells share the same fronthaul link. In this paper, a multi-cell scenario with a shared fronthaul link across multiple cells is considered, and we focus on optimizing the modulation compression of each cell. We propose semi-static optimization procedures that aim at maximizing the air interface performance subject to a shared fronthaul capacity constraint, by taking into account the average traffic load and system configuration of every cell. The problem is formulated as a convex optimization problem, which allows deriving the optimal maximum modulation order that is permitted per cell, under two different optimization criteria. Then, we use a dynamic multi-cell 5G NR system-level simulator based on ns-3 to evaluate the proposed optimized solutions.