A Randomized Greedy Heuristic for Steerable Wireless Backhaul Reconfiguration

Nina Skorin-Kapov,Andreas Kassler,Hakim Ghazzai,Ricardo Santos

doi:10.3390/electronics10040434

Nina Skorin-Kapov, Andreas Kassler + Show 2 more

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https://doi.org/10.3390/electronics10040434

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Abstract

In this paper, we consider the reconfiguration of wireless backhaul networks with mechanically steerable antennas in the presence of changing traffic demands. Reconfiguration requires the scheduling and coordination of several operations, including antenna alignment and link establishment/removal, with minimal disruption to existing user traffic. Previously, we proposed a Mixed Integer Linear Program (MILP) to orchestrate such reconfiguration with minimal packet loss. While the MILP solves the problem optimally for a limited number of discrete reconfiguration time slots, it does not scale well. In this paper, we propose an iterative randomized greedy algorithm to obtain suboptimal solutions in reduced time. The algorithm schedules the reconfiguration of wireless links by ranking them according to a set of attributes with associated weights and selecting them according to a randomized greedy function. Results on six different network scenarios indicate that the proposed algorithm can achieve good quality solutions in significantly less time. Furthermore, by extending the reconfiguration time beyond the maximum number of time slots solvable by the MILP, the proposed heuristic can obtain superior solutions for some problem instances. The number of iterations of the algorithm can be tuned for its applicability in both offline and online planning scenarios.

Highlights

To cope with growing mobile traffic predictions, 5G networks and beyond aim to improve usage of the wireless spectrum and leverage dense deployments of small cell (SC) base stations [1]
We evaluate Iter-RG-SBRA for multiple topologies and compare solution quality and execution time with those obtained by the optimal Mixed Integer Linear Program (MILP), a sub-optimal MILP which fixes a subset of the decision variables, and the case of Direct Reconfiguration (DR), where the transition to the target topology is initiated immediately and no intermediate links are formed
A Randomized Greedy Heuristic for Steerable Backhaul Reconfiguration In [14], we proposed an exact MILP for the described steerable wireless backhaul reconfiguration problem

Summary

Introduction

To cope with growing mobile traffic predictions, 5G networks and beyond aim to improve usage of the wireless spectrum and leverage dense deployments of small cell (SC) base stations [1] As it is not feasible and/or cost-effective to connect a massive amount of small cells through optical links to the core network, a promising alternative is the usage of a wireless mesh backhaul that is composed of various millimeter-wave (mmWave) links [2]. By forming multi-hop paths, small cells can forward aggregated user equipment (UE) traffic via mmWave links towards gateway nodes which are connected to the core through fiber cables This type of architecture has received considerable attention by the 3GPP under the name of Integrated Access and Backhaul (IAB) and has been recognized as a cost-effective alternative to a wired backhaul [3]. IAB has recently been standardized in 3GPP Rel-16 for 5G NR [4]

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Conclusion