IoT and Massive Connectivity: Massive MIMO Optimization for IoT Connectivity in 5G and Beyond Networks
Praveen Hegde, Robin Joseph Varughese

TL;DR
This paper explores optimizing Massive MIMO technology to improve IoT connectivity in 5G and beyond networks, addressing challenges like pilot contamination and energy efficiency.
Contribution
It provides a comprehensive survey of recent advances in channel estimation, beamforming, and resource allocation for Massive MIMO in IoT scenarios.
Findings
Simulation results show trade-offs between capacity, latency, and energy use.
Identifies optimal operating points for diverse IoT applications.
Discusses future integration with advanced network technologies.
Abstract
The IoT's explosive growth has led to a massive number of connected devices, which demand high-speed and pervasive connectivity, posing significant challenges for current-generation wireless communication infrastructures. Considering our evolution toward 5G and beyond 5G (B5G) and 6G networks, providing scalable, reliable, and low-latency communication for billions of devices is therefore essential. Massive Multi-Input Multi-Output (Massive MIMO) is a promising technology for fulfilling the requirements of 5G, as it can spatially multiplex a large number of users and increase the spectral efficiency per user. In this paper, we focus on optimizing the performance of Massive MIMO systems in IoT connectivity and low-latency use cases for 5G and B5G. It studies key issues, including pilot contamination, energy efficiency, and user scheduling, among dense IoT deployments. In addition, it…
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