Resource Allocation for Intelligent Reflecting Surface Enabled
Heterogeneous Networks
Abstract
Intelligent reflecting surface (IRS)-enabled communication systems
provide higher system capacity and spectral efficiency by reflecting the
incident signals from transmitters in a low-cost passive reflecting way.
However, it poses new challenges in resource allocation due to
surrounding interference and phase shift, especially when IRS is
employed in heterogeneous networks (HetNets). In this paper, a joint
power allocation and phase shift optimization problem is studied for the
downlink IRS-enabled HetNet, in which the IRS is deployed to enhance the
communications between small cell users (SCUs) and associated base
station (BS). The signal-to-interference-plus-noise ratio (SINR)
received at the SCU is maximized by jointly optimizing the transmit
power of the small-cell BS and the phase shift of the IRS, subject to
the constraints on the minimum SINR requirement of the macro-cell user
(MCU) and the phase shift. Although the formulated problem is
non-convex, we develop an optimal power allocation and the IRS’s passive
array coefficient solution for the single-user scenario. For the
multi-user scenario, we propose an iterative algorithm to maximize the
total rates of SCUs for obtaining a suboptimal solution by an
alternating iteration manner, where the sum of multiple-ratio fractional
programming problem is converted into a convex semidefinite program
(SDP) problem. Simulation results show that the proposed algorithm
significantly improves the achieved transmission rates of SCUs compared
to the case without the IRS.