Energy-Constrained Design of Joint NOMA-Diversity Schemes with Imperfect Interference Cancellation

Abstract

This study proposes a set of novel random access protocols combining Packet Repetition (PR) schemes, such as Contention Resolution Diversity Slotted Aloha (CRDSA) and Irregular Repetition SA (IRSA), with Non Orthogonal Multiple Access (NOMA). Differently from previous NOMA/CRDSA and NOMA/IRSA proposals, this work analytically derives the energy levels considering two realistic elements: the residual interference due to imperfect Interference Cancellation (IC), and the presence of requirements on the power spent for the transmission. More precisely, the energy-limited scenario is based on the relationship between the average available energy and the selected code modulation pair, thus being of specific interest for the implementation of the Internet of Things (IoT) technology in forthcoming fifth-generation (5G) systems. Moreover, a theoretical model based on the density evolution method is developed and numerically validated by extensive simulations to evaluate the limiting throughput and to explore the actual performance of different NOMA/PR schemes in energy-constrained scenarios.

A Novel Interference Avoidance Based on a Distributed Deep Learning Model for 5G-Enabled IoT

“…Decreasing the interference in IoT communication and 5G is an important issue that should be tackled, as it directly affects the system performance. In the literature, considerable research effort and solutions have been dedicated for the minimization of interference among devices in IoT-based networks such as optimization [ 9 , 10 , 11 , 12 , 13 , 14 ], deep learning [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ], modulation [ 23 , 24 ] and the Nash nocoopertaive power game [ 25 ].…”

“…An investigation of different scenarios for channel access management of indoor IoT communication was presented in [ 21 ], in which a distributed coordination scheme, based on reinforcement learning, allowed devices to learn to control their activity patterns based on the deep learning. The effect of imperfect inference cancelation and constraint transmission power requirements were studied in [ 22 ] where NOMA and packet diversity were jointly adopted.…”