Joint load balancing and interference mitigation in 5G HETNETS
Trung Kien Vu, Mehdi Bennis, Sumudu Samarakoon, M\'erouane Debbah, and, Matti Latva-aho

TL;DR
This paper proposes a joint load balancing and interference mitigation framework for 5G HetNets with massive MIMO macro cells and self-backhauled small cells, demonstrating significant performance improvements through stochastic optimization.
Contribution
It introduces a novel stochastic optimization-based approach for joint load balancing and interference mitigation in 5G HetNets with full-duplex small cells and macro MIMO base stations, including a dynamic user association algorithm.
Findings
Open access small cells perform close to closed access at lower frequencies.
Full-duplex small cells outperform closed access at higher frequencies.
Achieves up to 5.6x gain in cell-edge performance in ultra-dense networks.
Abstract
We study the problem of joint load balancing and interference mitigation in heterogeneous networks (HetNets) in which massive multiple-input multiple-output (MIMO) macro cell base station (BS) equipped with a large number of antennas, overlaid with wireless self-backhauled small cells (SCs) are assumed. Self-backhauled SC BSs with full-duplex communication employing regular antenna arrays serve both macro users and SC users by using the wireless backhaul from macro BS in the same frequency band. We formulate the joint load balancing and interference mitigation problem as a network utility maximization subject to wireless backhaul constraints. Subsequently, leveraging the framework of stochastic optimization, the problem is decoupled into dynamic scheduling of macro cell users, backhaul provisioning of SCs, and offloading macro cell users to SCs as a function of interference and backhaul…
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