Heterogeneous Cellular Networks Using Wireless Backhaul: Fast Admission Control and Large System Analysis

TL;DR

This paper develops fast, low-complexity algorithms for admission control in heterogeneous cellular networks with wireless backhaul, using $$-relaxation and large system analysis to optimize SAP selection and resource allocation.

Contribution

It introduces novel iterative algorithms for joint SAP selection and beamforming that are efficient for small-to-medium and large systems, leveraging random matrix theory for asymptotic optimality.

Findings

Algorithms achieve near-optimal performance in simulations.

Large system analysis reduces dependence on real-time channel information.

Proposed methods are computationally efficient for different system sizes.

Abstract

We consider a heterogeneous cellular network with densely underlaid small cell access points (SAPs). Wireless backhaul provides the data connection from the core network to SAPs. To serve as many SAPs and their corresponding users as possible with guaranteed data rates, admission control of SAPs needs to be performed in wireless backhaul. Such a problem involves joint design of transmit beamformers, power control, and selection of SAPs. In order to tackle such a difficult problem, we apply $\ell_1$-relaxation and propose an iterative algorithm for the $\ell_1$-relaxed problem. The selection of SAPs is made based on the outputs of the iterative algorithm. This algorithm is fast and enjoys low complexity for small-to-medium sized systems. However, its solution depends on the actual channel state information, and resuming the algorithm for each new channel realization may be unrealistic for large systems. Therefore, we make use of random matrix theory and also propose an iterative algorithm for large systems. Such a large system iterative algorithm produces asymptotically optimum solution for the $\ell_1$-relaxed problem, which only requires large-scale channel coefficients irrespective of the actual channel realization. Near optimum results are achieved by our proposed algorithms in simulations.