2015/05/05 by Emil Björnson, Luca Sanguinetti, Björnson, Emil +3 · 3 citations
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #Advanced Wireless Network Optimization #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT)
paper · pdf · doi:10.48550/arxiv.1505.01181
openalex publication_date 2015/05/05 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28
How would a cellular network designed for maximal energy efficiency look\nlike? To answer this fundamental question, tools from stochastic geometry are\nused in this paper to model future cellular networks and obtain a new lower\nbound on the average uplink spectral efficiency. This enables us to formulate a\ntractable uplink energy efficiency (EE) maximization problem and solve it\nanalytically with respect to the density of base stations (BSs), the transmit\npower levels, the number of BS antennas and users per cell, and the pilot reuse\nfactor. The closed-form expressions obtained from this general EE maximization\nframework provide valuable insights on the interplay between the optimization\nvariables, hardware characteristics, and propagation environment. Small cells\nare proved to give high EE, but the EE improvement saturates quickly with the\nBS density. Interestingly, the maximal EE is achieved by also equipping the BSs\nwith multiple antennas and operate in a "massive MIMO" fashion, where the array\ngain from coherent detection mitigates interference and the multiplexing of\nmany users reduces the energy cost per user.\n