Dynamic Resource Allocation in Next Generation Cellular Networks with Full-Duplex Self-backhauls

TL;DR

This paper proposes a novel self-backhaul scheme for small cell networks that combines full-duplex and massive MIMO technologies, optimizing power allocation to enhance network efficiency amid interference.

Contribution

It introduces a new self-backhaul scheme utilizing FD and massive MIMO, formulating and solving a non-convex power allocation problem with an iterative algorithm.

Findings

The proposed scheme effectively manages interference in dense small cell networks.

Simulation results show improved spectral efficiency and network throughput.

The iterative algorithm converges efficiently to optimize power allocation.

Abstract

With the dense deployment of small cell networks, low-cost backhaul schemes for small cell base stations (SBSs) have attracted great attentions. Self-backhaul using cellular communication technology is considered as a promising solution. Although some excellent works have been done on self-backhaul in small cell networks, most of them do not consider the recent advances of full-duplex (FD) and massive multiple-input and multiple-output (MIMO) technologies. In this paper, we propose a self-backhaul scheme for small cell networks by combining FD and massive MIMO technologies. In our proposed scheme, the macro base station (MBS) is equipped with massive MIMO antennas, and the SBSs have the FD communication ability. By treating the SBSs as \textit{special} macro users, we can achieve the simultaneous transmissions of the access link of users and the backhaul link of SBSs in the same frequency. Furthermore, considering the existence of inter-tier and intra-tier interference, we formulate the power allocation problem of the MBS and SBSs as an optimization problem. Because the formulated power allocation problem is a non-convex problem, we transform the original problem into a difference of convex program (DCP) by successive convex approximation method (SCAM) and variable transformation, and then solve it using a constrained concave convex procedure (CCCP) based iterative algorithm. Finally, extensive simulations are conducted with different system configurations to verify the effectiveness of the proposed scheme.