2018/01/31 by Andrea Pizzo, Daniel Verenzuela, Luca Sanguinetti +1 · 20 citations
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Base station #Channel (broadcasting) #Computer science #Cooperative Communication and Network Coding #Efficient energy use #Electrical engineering #Engineering #Fading #Mathematical analysis #Mathematical optimization #Mathematics #Maximal-ratio combining #Millimeter-Wave Propagation and Modeling #Path loss #Spectral efficiency #Statistics #Stochastic geometry #Telecommunications #Telecommunications link #Topology (electrical circuits) #Upper and lower bounds #Wireless #cs.IT #math.IT
paper · pdf · doi:10.1109/tgcn.2018.2839346
published in IEEE Transactions on Green Communications and Networking 2(3), 735-750 (Institute of Electrical and Electronics Engineers) · 30 pages, 5 figures, 2 tables, https://ieeexplore.ieee.org/document/8362685/
openalex publication_date 2018/05/22 · arxiv created 2018/06/22 · arxiv updated 2018/06/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
This work aims to design the uplink (UL) of a cellular network for maximal energy efficiency (EE). Each base station (BS) is randomly deployed within a given area and is equipped with M antennas to serve K user equipments (UEs). A multislope (distance-dependent) path loss model is considered and linear processing is used, under the assumption that channel state information is acquired by using pilot sequences (reused across the network). Within this setting, a lower bound on the UL spectral efficiency and a realistic circuit power consumption model are used to evaluate the network EE. Numerical results are first used to compute the optimal BS density and pilot reuse factor for a Massive MIMO network with three different detection schemes, namely, maximum ratio combining, zero-forcing (ZF) and multicell minimum mean-squared error. The numerical analysis shows that the EE is a unimodal function of BS density and achieves its maximum for a relatively small density of BS, irrespective of the employed detection scheme. This is in contrast to the single-slope (distance-independent) path loss model, for which the EE is a monotonic non-decreasing function of BS density. Then, we concentrate on ZF and use stochastic geometry to compute a new lower bound on the spectral efficiency, which is then used to optimize, for a given BS density, the pilot reuse factor, number of BS antennas and UEs. Closed-form expressions are computed from which valuable insights into the interplay between optimization variables, hardware characteristics, and propagation environment are obtained.