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A main challenge of 5G and beyond wireless systems is to efficiently utilizethe available spectrum and simultaneously reduce the energy consumption. Fromthe radio resource allocation perspective, the solution to this problem is tomaximize the energy efficiency instead of the throughput. This results in theoptimal benefit-cost ratio between data rate and energy consumption. It alsooften leads to a considerable reduction in throughput and, hence, anunderutilization of the available spectrum. Contemporary approaches to balancethese metrics based on multi-objective programming theory often lackoperational meaning and finding the correct operating point requires carefulexperimentation and calibration. Instead, we propose the novel concept ofhierarchical resource allocation where conflicting objectives are ordered bytheir importance. This results in a resource allocation algorithm that strivesto minimize the transmit power while keeping the data rate close the maximumachievable throughput. In a typical multi-cell scenario, this strategy is shownto reduces the transmit power consumption by 65% at the cost of a 5% decreasein throughput. Moreover, this strategy also saves energy in scenarios whereglobal energy efficiency maximization fails to achieve any gain over throughputmaximization.

Hierarchical Resource Allocation: Balancing Throughput and Energy Efficiency in Wireless Systems