Grant-Free Random Access in Massive MIMO for Static Low-Power IoT Nodes

TL;DR

This paper proposes a low-complexity grant-free random access method for massive MIMO systems supporting large-scale IoT networks, leveraging prior channel info to efficiently handle sporadic, low-power device transmissions.

Contribution

It introduces a novel grant-free access algorithm with a closed-form solution, optimized for static IoT devices and capable of supporting thousands of nodes with minimal false alarms.

Findings

Supports 1000 nodes with 200 simultaneous requests at low power

Achieves false alarm below 10^-6 and miss detection below 10^-4

Uses a low-complexity algorithm exploiting device staticity

Abstract

Massive MIMO is a promising technology to enable a massive number of Internet of Things nodes to transmit short and sporadic data bursts at low power. In conventional cellular networks, devices use a grant-based random access scheme to initiate communications. This scheme relies on a limited set of orthogonal preambles, which simplify signal processing operations at network access points. However, it is not well suited for Internet of Things (IoT) devices due to: (i) the large protocol overhead, and (ii) the high probability of collision. In contrast to the grant-based scheme, a grant-free approach uses user-specific preambles and has a small overhead, at the expense of more complexity at access points. In this work, a grant-free method is proposed, applicable for both co-located and cell-free deployments. The method has a closed form solution, which results in a significantly low complexity with respect to the state-of-the art. The algorithm exploits the static nature of IoT devices through the use of prior channel state information. With a power budget of 1 mW, 64 antennas are sufficient to support 1000 nodes with 200 simultaneous access requests with a probability of false alarm and miss detection below 10-6 and 10-4, respectively.