Traffic-Aware Cost-Optimized Fronthaul Planning for Ultra-Dense Networks

TL;DR

This paper presents a traffic-aware optimization framework for planning cost-effective fronthaul networks in ultra-dense networks, balancing fiber and mmWave links to improve performance and reduce costs.

Contribution

It introduces a mixed-integer linear programming approach for hybrid fronthaul planning considering traffic demands, which is novel in optimizing both cost and performance.

Findings

The proposed method reduces overall fronthaul deployment costs.

It outperforms traditional schemes in terms of cost and reliability.

The approach adapts to evolving traffic demands effectively.

Abstract

The cost and limited capacity of fronthaul links pose significant challenges for the deployment of ultra-dense networks (UDNs), specifically for cell-free massive MIMO systems. Hence, cost-effective planning of reliable fronthaul networks is crucial for the future deployment of UDNs. We propose an optimization framework for traffic-aware hybrid fronthaul network planning, aimed at minimizing total costs through a mixed-integer linear program (MILP) that considers fiber optics and mmWave, along with optimizing key performance metrics. The results demonstrate superiority of the proposed approach, highlighting the cost-effectiveness and performance advantages when compared to different deployment schemes. Moreover, our results also reveal different trends that are critical for Service Providers (SPs) during the fronthaul planning phase of future-proof networks that can adapt to evolving traffic demands.