# Sixth-Generation (6G) Networks for Improved Machine-to-Machine (M2M) Communication in Industry 4.0
## 1 Introduction  
The demand for wireless connectivity has been growing exponentially over the last 15 years. In five years' time, there will be approximately 17 billion devices connected to the mobile network, generating a flow of one thousand exabytes of data per month. It will also be necessary to transition from fifth-generation (5G) to sixth-generation (6G) systems to meet the growing demand for services and requirements for innovative applications, including in industry. Sixth-generation (6G) networks, which are intended to support mass connectivity and ensure an increase in efficiency and quality of service for all users, including industrial ones, will have to supply effective solutions to many technical problems. This is particularly the case with multiple antennas and multiple-input multiple-output (MIMO) technologies for 6G networks, namely massive MIMO (mMIMO), extremely large MIMO (XL-MIMO), intelligent reflecting surface (IRS), and cell-free mMIMO (CF-mMIMO) [1]. The characteristics of 6G networks include ultra-reliable low-latency communications (URLLC), ultra-high throughput, high energy and spectrum efficiency, ultra-dense connectivity, integrated sensing, and secure communications. Given the high load and computational complexity, technologies are already working to provide 6G communications to mass users: IRS, unmanned aerial vehicles (UAVs), non-orthogonal multiple access (NOMA), etc. Optimizing the functionality of a 6G system may be difficult or even impossible using traditional mathematical methods--instead, machine learning (ML), deep learning (DL), and reinforcement learning (RL) are increasingly being proposed (Figure 1) [2]. This article aims to provide an overview of the challenges in the area of 6G networks for improved machine-to-machine (M2M) communication in Industry 4.0 and the proposed solutions, taking into account the disruptive technologies that are yet to be developed. M2M uses the Industrial Internet of Things (IIoT) to communicate between machines forcollaborative automation and intelligent optimization. This requires high-quality connections, ubiquitous communication, and interoperable interactions. Manufacturing IIoT applications are focused on collaboration through M2M messaging (CoM2M). The scalable interoperability of production applications is necessary for machine cooperation and data interoperability at the communication and semantic levels. The novelty and contribution of this work lie in the emphasis on 6G technologies, which are still being developed and are planned to be implemented in the next five years. A coherent look at these development areas can reveal gaps or unevenly developing areas, as well as opportunities for development in subsequent substantive areas and time steps. However, we would like to draw attention to the fact that this is a one-sided view: from the point of view of M2M and Industry 4.0/5.0. Therefore, we focus not on what 6G is, but what it can be in Industry 5.0 after 2030, if we take advantage of all the opportunities associated with it. Perhaps engineers and scientists from research areas such as the Green Deal or smart technology will have different expectations and priorities that are not necessarily contradictory to ours. The market for Industry 5.0 networks and technologies is focused on people and their environment and is more than a set of visions, concepts, and technologies that did not fit into the 5G concept--it is the opportunity to shape the intelligent industry from scratch to solutions that will appear on the market after 2030 as products, services, or processes. To improve readability, all acronyms appearing in the article are explained in Table 1 below (in alphabetical order).