Paper Info
Title
User-Centric Cluster Design and Analysis for Hybrid Sub-6GHz-mmWave-THz Dense Networks
Abstract
The terahertz (THz) waves with enormous bandwidth can be used along with the existing sub-6GHz and millimeter wave (mmWave) bands to achieve the ever evolving ecosystem of applications that need to be supported by the modern wireless networks. This paper investigates a user-centric dynamic base station (BS) clustering design for a hybrid network where THz, mmWave, and sub-6GHz BSs coexist. Invoking the proposed clustering model, the BS cooperation within each band is made possible by considering long term channel variations and all the surrounding BSs within a cluster with tunable size. A typical user is associated with the best BS cluster, from either a sub-6GHz, mmWave or THz tier based on the maximum signal-to-interference-plus-noise-ratio (SINR) criterion or the maximum rate criterion. Using tools from stochastic geometry, we assess the performance of the proposed user-centric hybrid system in terms of SINR and rate coverage performances, while accounting for: band specific propagation models, directional beamfroming, and BSs random locations. The accuracy of the analytical results is validated with Monte-Carlo simulations. The obtained results recognize a clear coverage/rate trade-off where a high fraction of THz BSs improves the rate significantly but may degrade the coverage performance. Thus, with carefully planned networks, enabling user-centric BS cooperation for hybrid wireless systems can achieve ultra-high rates while maintaining sufficient coverage in sixth-generation (6G) networks.
Year
DOI
Venue
2022
10.1109/TVT.2022.3170518
IEEE Transactions on Vehicular Technology
Keywords
DocType
Volume
6G,millimeter wave,molecular absorption coefficient,stochastic geometry,terahertz (THz) communication,user-centric networks
Journal
71
Issue
ISSN
Citations 
7
0018-9545
0
PageRank 
References 
Authors
0.34
33
4
Name
Order
Citations
PageRank
Khaled Humadi132.05
Imène Trigui200.68
Wei-Ping Zhu352.79
Wessam Ajib400.68