mmWave Backhaul Testbed Configurability Using Software-Defined Networking

Abstract EN

Future mobile data traffic predictions expect a significant increase in user data traffic, requiring new forms of mobile network infrastructures.

Fifth generation (5G) communication standards propose the densification of small cell access base stations (BSs) in order to provide multigigabit and low latency connectivity.

This densification requires a high capacity backhaul network.

Using optical links to connect all the small cells is economically not feasible for large scale radio access networks where multiple BSs are deployed.

A wireless backhaul formed by a mesh of millimeter-wave (mmWave) links is an attractive mobile backhaul solution, as flexible wireless (multihop) paths can be formed to interconnect all the access BSs.

Moreover, a wireless backhaul allows the dynamic reconfiguration of the backhaul topology to match varying traffic demands or adaptively power on/off small cells for green backhaul operation.

However, conducting and precisely controlling reconfiguration experiments over real mmWave multihop networks is a challenging task.

In this paper, we develop a Software-Defined Networking (SDN) based approach to enable such a dynamic backhaul reconfiguration and use real-world mmWave equipment to setup a SDN-enabled mmWave testbed to conduct various reconfiguration experiments.

In our approach, the SDN control plane is not only responsible for configuring the forwarding plane but also for the link configuration, antenna alignment, and adaptive mesh node power on/off operations.

We implement the SDN-based reconfiguration operations in a testbed with four nodes, each equipped with multiple mmWave interfaces that can be mechanically steered to connect to different neighbors.

We evaluate the impact of various reconfiguration operations on existing user traffic using a set of extensive testbed measurements.

Moreover, we measure the impact of the channel assignment on existing traffic, showing that a setup with an optimal channel assignment between the mesh links can result in a 44% throughput increase, when compared to a suboptimal configuration.