Coverage Analysis of mmWave and THz-Enabled Aerial and Terrestrial Heterogeneous NetworksShow others and affiliations
2021 (English)In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016Article in journal (Refereed) Published
Abstract [en]
Heterogeneous networks (HetNets) are becoming a promising solution for future wireless systems to satisfy the high data rate requirements. This paper introduces a stochastic geometry framework for the analysis of the downlink coverage probability in a multi-tier HetNet consisting of a macro-base station (MBS) operating at sub-6 GHz, millimeter wave (mmWave)-enabled unmanned aerial vehicles (UAVs) operating at 28 GHz, and small BSs operating both at mmWave and THz frequencies. The analytical expressions for the coverage probability for each tier have been derived in the paper. Monte Carlo simulations are then performed to validate the analytical expressions. The effectiveness of the HetNet is analyzed on various performance metrics including association and coverage probabilities for different network parameters. We show that the mmWave and THz-enabled cells provide significant improvement in the achievable data rates because of their high available bandwidths, however, they have a degrading effect on the coverage probability due to their high propagation losses. IEEE
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2021.
Keywords [en]
millimeter wave, SINR coverage probability., TeraHertz, UAVs, Antennas, Bandwidth, Heterogeneous networks, Monte Carlo methods, Probability, Stochastic systems, Terahertz waves, Analytical expressions, Available bandwidth, Coverage probabilities, Future wireless systems, Heterogeneous network (HetNets), Millimeter waves (mmwave), Performance metrics, Stochastic geometry, Millimeter waves
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:miun:diva-43694DOI: 10.1109/TITS.2021.3086958Scopus ID: 2-s2.0-85113246442OAI: oai:DiVA.org:miun-43694DiVA, id: diva2:1611315
2021-11-152021-11-152021-11-15Bibliographically approved