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In this paper, to address backhaul capacity bottleneck and concurrentlyoptimize energy consumption and delay, we formulate a novel weighted-summulti-objective optimization problem where popular content caching placementand integrated access and backhaul (IAB) millimeter (mmWave) bandwidthpartitioning are optimized jointly to provide Pareto efficient optimalnon-dominating solutions. In such integrated networks analysis of what-ifscenarios to understand trade-offs in decision space, without losing sight ofoptimality, is important. A wide set of numerical investigations reveal thatcompared with the nominal single objective optimization schemes such asoptimizing only the delay or the energy consumption the proposed optimizationframework allows for a reduction of the aggregation of energy consumption anddelay by an average of 30% to 55%.

The Energy-Delay Pareto Front in Cache-enabled Integrated Access and Backhaul mmWave HetNets