# Multiantenna NOMA with Finite Blocklength: A Pragmatic Paradigm for Ultra-Dense Networking

## TL;DR

This paper proposes a new NOMA system for IoT networks with many low-power sensors, using multiple antennas and FEC codes to enable efficient communication.

## Contribution

A new NOMA design with FEC codes for ultra-dense IoT networks is proposed, showing near-capacity performance with reduced complexity.

## Key findings

- Three FEC codes (CCs, polar codes, LDPCs) achieve near-capacity performance in finite-blocklength scenarios.
- Convolutional codes offer comparable performance with lower complexity, suitable for IoT sensor networks.
- Large dimensional analysis provides deterministic SINR expressions for massive connectivity scenarios.

## Abstract

This paper addresses the design and performance analysis of nonorthogonal multiple access (NOMA) for ultra-dense networking of the Internet of Things (IoT) based on low-power sensors. The proposed NOMA schemes consist of an Nr-antenna access point and K single antenna sensors given K≫Nr. A power allocation technique and forward error correction (FEC) are combined to enable concurrent uplink transmission and the successful separation of all K sensors at the access point. In scenarios where K≫Nr, large dimensional analysis is employed to derive a deterministic expression for the received signal-to-interference-plus-noise ratio (SINR) within the finite blocklength regime. Three distinct Forward Error Correction (FEC) codes—convolutional codes (CCs), polar codes, and low-density parity-check codes (LDPCs)—are assessed. These evaluations indicate that all three codes achieve near-capacity performance while supporting massive connectivity in the finite-blocklength context. Notably, convolutional codes demonstrate comparable performance with reduced complexity, a desirable attribute for prolonging the life cycle of wireless sensor network-based IoT applications.