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Energy consumption represents a major part of the operating expenses ofmobile network operators. With the densification foreseen with 5G and beyond,energy optimization has become a problem of crucial importance. While energyoptimization is widely studied in the literature, there are limited insightsand algorithms for energy-saving techniques for Integrated Access and Backhaul(IAB), a self-backhauling architecture that ease deployment of dense cellularnetworks reducing the number of fiber drops. This paper proposes a noveloptimization model for dynamic joint routing and energy optimization in IABnetworks. We leverage the closed-loop control framework introduced by the OpenRadio Access Network (O-RAN) architecture to minimize the number of active IABnodes while maintaining a minimum capacity per User Equipment (UE). Theproposed approach formulates the problem as a binary nonlinear program, whichis transformed into an equivalent binary linear program and solved using theGurobi solver. The approach is evaluated on a scenario built upon open data oftwo months of traffic collected by network operators in the city of Milan,Italy. Results show that the proposed optimization model reduces the RAN energyconsumption by 47%, while guaranteeing a minimum capacity for each UE.

Joint Routing and Energy Optimization for Integrated Access and Backhaul with Open RAN