# Scheduling of Industrial Control Traffic for Dynamic RAN Slicing with Distributed Massive MIMO +
## 2 Related Work  
The work in this paper follows on from our work in [16], where we considered the problem of scheduling for industrial control traffic in massive MIMO and LIS systems. In the current paper, we target the same use case, however with the addition of dynamic RAN slicing. This requires a new objective for the optimization problems. In [16], the objective we used was to minimize the maximum number of pilots used in any time slot. This assumes that there is a static number of pilots given to the control traffic and minimizes this number. However, this does not necessarily result in the fewest pilots used overall. In a dynamic slicing context, any unused pilots in the industrial control slice can be used by other slices. It is, therefore, better to have a larger base allocation of pilots for the industrial control slice but use fewer of these, leaving them available to be borrowed. In the current paper, we therefore consider a new objective of minimizing the number of pilots used per slot, that is, the pilot rate. This adds significant complexity to the optimization formulation and changes the way it should be solved in order to be feasible for use in real systems. Pilot allocation and scheduling for massive MIMO is an area that has received a lot of attention and concerted research effort since massive MIMO was first conceived. It is too much to discuss here, but a survey up to 2017 can be found in [17], and a more recent one concerning scheduling in 5G more broadly in [18]. However, thus far, little work has been conducted on user scheduling for massive MIMO in an industrial context, and in this work, even less deals with demanding industrial control traffic. Paper [19] considers the feasibility of supporting ultra-reliable low-latency communications (URLLC) traffic in a massive MIMO system but with grant-free access rather than scheduled access. While grant-free access is the most appropriate for certain types of URLLC traffic, especially sporadic traffic, such as alarms, it is not a good fit for industrial control traffic, which is periodic and frequent and thus lends itself better to a scheduled approach. Several works investigate massive MIMO as a communications technology for the industrial Internet of Things (IIoT). In [20], the authors consider a single-cell scenario in which a massive MIMO base station serves a much larger number of IIoT devices than its number of antennas. Similarly, [21] investigates whether it is feasible to use massive MIMO for IIoT, again in a single-cell scenario with a large number of low-power IIoT devices, focusing on different precoding techniques rather than link layer user scheduling. In [22], the focus is instead on power allocation in IIoT with massive MIMO, and the pilot and payload power are jointly optimized. While these works share the same industrial domain setting as our work, and in some cases, similar stringent requirements on latency and reliability, their focus is on access for massively many devices, typically with low per-device data rates. We instead focus on industrial control traffic, where the goal is to meet the latency and reliability requirements needed for high-frequency control loops, rather than serve a massive number of devices. A few works have previously been published on scheduling for industrial communications in massive MIMO systems. In [23], we considered the case of high-priority alarm traffic alongside industrial control traffic; however, in that work, we focused on the alarm traffic and did not provide a scheduling method for the control traffic. In that work, we also did not consider dynamic RAN slicing. Network slicing was proposed in the years leading up to the release of 5G as a means of providing QoS for its diverse use cases [12; 13], and since, has continued to attract significant interest from the research community [24]. In particular, RAN slicing aims to partition the resources in the radio access network between different slices [14; 15]. To do this, the particular radio technology must be taken into account.