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  5. Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks

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Preprint
English
2016

Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks

0 Datasets

0 Files

English
2016
arXiv (Cornell University)

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Matti Latva-aho
Matti Latva-aho

University Of Oulu

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Trung Kien Vu
Mehdi Bennis
Sumudu Samarakoon
+2 more

Abstract

In this paper, we study the problem of joint inband backhauling and interference mitigation in 5G heterogeneous networks (HetNets) in which a massive multiple-input multipleoutput (MIMO) macro cell base station equipped with a large number of antennas, overlaid with self-backhauled small cells is assumed. This problem is cast as a network utility maximization subject to wireless backhaul constraints. Due to the non-tractability of the problem, we first resort to random matrix theory to get a closed-form expression of the achievable rate and transmit power in the asymptotic regime, i.e., as the number of antennas and users grows large. Subsequently, leveraging the framework of stochastic optimization, the problem is decoupled into dynamic scheduling of macro cell users and backhaul provisioning of small cells as a function of interference and backhaul links. Via simulations, we evaluate the performance gains of our proposed framework under different network architectures and low/high frequency bands. Our proposed HetNet method achieves the achievable average UE throughput of 1.7 Gbps as well as ensures 1 Gbps cell-edge UE throughput when serving 200 UEs per km2 at 28 GHz with 1 GHz bandwidth. In ultra-dense network, the UE throughput at 28 GHz achieves 62x gain as compared to 2.4 GHz.

How to cite this publication

Trung Kien Vu, Mehdi Bennis, Sumudu Samarakoon, Mérouane Debbah, Matti Latva-aho (2016). Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks. arXiv (Cornell University)

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Publication Details

Type

Preprint

Year

2016

Authors

5

Datasets

0

Total Files

0

Language

English

Journal

arXiv (Cornell University)

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