In this paper, we study the problem of joint in-band 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 nontractability 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 km 2 at 28 GHz with 1 GHz bandwidth. In ultradense network, the UE throughput at 28 GHz achieves 62× gain as compared to 2.4 GHz.
Vu et al. REF studied the joint in-band backhauling and interference mitigation problem in HCNs, which consists of a massive multiuser MIMO MBS overlaid with self-backhauled small cells.
Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks
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Computer Science Mathematics