2021/02/05 by Bho Matthiesen, Eduard A. Jorswieck, Matthiesen, Bho +3
Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Network Optimization #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #Information Theory (cs.IT)
paper · pdf · doi:10.48550/arxiv.2102.03105
openalex publication_date 2021/02/05 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
A main challenge of 5G and beyond wireless systems is to efficiently utilize\nthe available spectrum and simultaneously reduce the energy consumption. From\nthe radio resource allocation perspective, the solution to this problem is to\nmaximize the energy efficiency instead of the throughput. This results in the\noptimal benefit-cost ratio between data rate and energy consumption. It also\noften leads to a considerable reduction in throughput and, hence, an\nunderutilization of the available spectrum. Contemporary approaches to balance\nthese metrics based on multi-objective programming theory often lack\noperational meaning and finding the correct operating point requires careful\nexperimentation and calibration. Instead, we propose the novel concept of\nhierarchical resource allocation where conflicting objectives are ordered by\ntheir importance. This results in a resource allocation algorithm that strives\nto minimize the transmit power while keeping the data rate close the maximum\nachievable throughput. In a typical multi-cell scenario, this strategy is shown\nto reduces the transmit power consumption by 65% at the cost of a 5% decrease\nin throughput. Moreover, this strategy also saves energy in scenarios where\nglobal energy efficiency maximization fails to achieve any gain over throughput\nmaximization.\n