IRS-Assisted Massive MIMO-NOMA Networks with Polarization Diversity

no code implementations • 27 May 2021 • Arthur S. de Sena, Pedro H. J. Nardelli, Daniel B. da Costa, F. Rafael M. Lima, Liang Yang, Petar Popovski, Zhiguo Ding, Constantinos B. Papadias

In this paper, the appealing features of a dual-polarized intelligent reflecting surface (IRS) are exploited to improve the performance of dual-polarized massive multiple-input multiple-output (MIMO) with non-orthogonal multiple access (NOMA) under imperfect successive interference cancellation (SIC).

IRS-Assisted Massive MIMO-NOMA Networks: Exploiting Wave Polarization

no code implementations • 7 Dec 2020 • Arthur S. de Sena, Pedro H. J. Nardelli, Daniel B. da Costa, F. Rafael M. Lima, Liang Yang, Petar Popovski, Zhiguo Ding, Constantinos B. Papadias

By considering the downlink of a multi-cluster scenario, the IRSs assist the base station (BS) to multiplex subsets of users in the polarization domain.

Deep Reinforcement Learning for QoS-Constrained Resource Allocation in Multiservice Networks

no code implementations • 3 Mar 2020 • Juno V. Saraiva, Iran M. Braga Jr., Victor F. Monteiro, F. Rafael M. Lima, Tarcisio F. Maciel, Walter C. Freitas Jr., F. Rodrigo P. Cavalcanti

In this article, we study a Radio Resource Allocation (RRA) that was formulated as a non-convex optimization problem whose main aim is to maximize the spectral efficiency subject to satisfaction guarantees in multiservice wireless systems.

Distributed Optimization reinforcement-learning +1