Abstract:
Intelligent Reflecting Surface (IRS), with the potential to realize smart radio
environment, has emerged as an energy efficient and a cost effective technology to support the services and demands foreseen for coming decades.
On the other hand, non-orthogonal multiple access (NOMA), has been recognized as an effective technology to enhance spectral efficiency (SE) and
support massive connectivity. The merger of IRS and NOMA can provide
an efficient multiple access solution for beyond fifth generation (B5G) and
sixth generation (6G) networks. In this thesis, we investigate a downlink
IRS-aided multi-carrier (MC) NOMA system, where the IRS is deployed to
especially assist the blocked users to establish communication with the base
station (BS). To maximize the system sum rate under network quality-ofservice (QoS), rate fairness and successive interference cancellation (SIC)
constraints, we formulate a problem for joint optimization of IRS elements,
sub-channel assignment and power allocation. The formulated problem is
mixed non-convex. Therefore, a novel three stage algorithm is proposed for
optimization of IRS elements, sub-channel assignment and power allocation.
Firstly, the IRS elements are optimized using bisection method based iterative algorithm. Then, the sub-channel assignment problem is solved one-to-one stable matching algorithm. Finally, the power allocation problem
is solved under the given sub-channel and optimal number of IRS elements using Lagrangian dual decomposition method based on Lagrangian multipliers.
Moreover, in an effort to demonstrate the low-complexity of the proposed resource allocation scheme, we provide the complexity analysis of the proposed
algorithms. Simulation results are presented to validate the effectiveness of
the proposed resource allocation approach.
