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5G Massive MIMO Architectures: Self-Backhauled Small Cells versus Direct Access

Authors :
Bonfante, Andrea
Giordano, Lorenzo Galati
López-Pérez, David
Garcia-Rodriguez, Adrian
Geraci, Giovanni
Baracca, Paolo
Butt, M. Majid
Marchetti, Nicola
Source :
IEEE Transactions on Vehicular Technology ( Volume: 68 , Issue: 10 , Oct. 2019 )
Publication Year :
2018

Abstract

In this paper, we focus on one of the key technologies for the fifth-generation wireless communication networks, massive multiple-input-multiple-output (mMIMO), by investigating two of its most relevant architectures: 1) to provide in-band backhaul for the ultra-dense network (UDN) of self-backhauled small cells (SCs), and 2) to provide direct access (DA) to user equipments (UEs). Through comprehensive 3GPP-based system-level simulations and analytical formulations, we show the end-to-end UE rates achievable with these two architectures. Differently from the existing works, we provide results for two strategies of self-backhauled SC deployments, namely random and ad-hoc, where in the latter SCs are purposely positioned close to UEs to achieve line-of-sight (LoS) access links. We also evaluate the optimal backhaul and access time resource partition due to the in-band self-backhauling (s-BH) operations. Our results show that the ad-hoc deployment of self-backhauled SCs closer to the UEs with optimal resource partition and with directive antenna patterns, provides rate improvements for cell-edge UEs that amount to 30% and tenfold gain, as compared to mMIMO DA architecture with pilot reuse 3 and reuse 1, respectively. On the other hand, mMIMO s-BH underperforms mMIMO DA above the median value of the UE rates when the effect of pilot contamination is less severe, and the LoS probability of the DA links improves.<br />Comment: The paper is published at IEEE Transactions on Vehicular Technology (TVT 2019). arXiv admin note: text overlap with arXiv:1806.10969

Details

Database :
arXiv
Journal :
IEEE Transactions on Vehicular Technology ( Volume: 68 , Issue: 10 , Oct. 2019 )
Publication Type :
Report
Accession number :
edsarx.1809.03953
Document Type :
Working Paper
Full Text :
https://doi.org/10.1109/TVT.2019.2937652