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

TL;DR

This paper proposes a novel framework for joint in-band backhauling and interference mitigation in 5G HetNets, utilizing random matrix theory and stochastic optimization to enhance user throughput and network performance.

Contribution

It introduces a new joint optimization approach for backhaul and interference management in 5G HetNets using advanced mathematical tools.

Findings

Achieves 1.7 Gbps average user throughput at 28 GHz.

Ensures 1 Gbps cell-edge throughput with 200 UEs per km².

62x throughput gain at 28 GHz compared to 2.4 GHz.

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.