Cloud-RAN (C-RAN) is a promising paradigm for the next generation radio access network infrastructure, which offers centralized and coordinated base-band signal processing in a BBU pool. This requires extremely low latency fronthaul links to achieve real-time signal processing. In this paper, we investigate massive MIMO pilot scheduling in a C-RAN infrastructure under a factory automation scenario. We use simulations to provide insights on the feasibility of C-RAN deployment for industrial communication, which has stringent criteria to meet Industry 4.0 standards. Our experiment results show that, concerning a pilot scheduling problem, the C-RAN system is capable of meeting the industrial criteria when there is fronthaul latency in the order of milliseconds.
With the promise of increased responsiveness and robustness of the emerging 5G technology, it is suddenly becoming feasible to deploy latency-sensitive control systems over the cloud via a mobile network. Even though 5G is herald to give lower latency and jitter than current mobile networks, the effect of the delay would still be non-negligible for certain applications.In this paper we explore and demonstrate the possibility of compensating for the unknown and time-varying latency introduced by a 5G mobile network for control of a latency-sensitive plant. We show that the latency from a prototype 5G test bed lacks significant short-term correlation, making accurate latency prediction a difficult task. Further, because of the unknown and time-varying latency our used simple interpolation-based model experiences some troubling theoretical properties, limiting its usability in real world environments. Despite this, we give a demonstration of the strategy which seems to increase robustness in a simulated plant. CCS CONCEPTS• Networks → Network performance evaluation; Wireless access points, base stations and infrastructure; • Computer systems organization → Embedded and cyber-physical systems;
A key enabler for Industry 4.0 is Fifth Generation Wireless Specifications (5G), within which network slicing is a promising technique to ensure customized quality of service for specific end-user groups in industrial scenarios. Massive Multiple Input Multiple Output (MIMO) plays a significant role in 5G but network slicing for massive MIMO has not yet been addressed. In this paper, we propose a network slicing scheme for a 5G Radio Access Network (RAN) with massive MIMO technology. Our simulations show that it is feasible to provide guaranteed performance in terms of high reliability, low latency, and a large number of connections by deploying our proposed scheme at the mMedium Access Control (MAC) layer of a massive MIMO base station.
The notion of Cloud RAN is taking a prominent role in narrative for the next generation wireless infrastructure. It is also seen as a mean to industrial communication systems. In order to provide reliable wireless connectivity for industrial deployments, by conventional means, the cloud infrastructure needs to be reliable and incur little latency, which however, is contradictory to the stochastic nature of cloud infrastructures. In this paper, we investigate the impact of stochastic delay on a radio resource allocation process deployed in Cloud RAN. We proceed to propose a strategy for realizing timely cloud responses and then adapt that strategy to a radio resource allocation problem. Further, we evaluate the strategies in an industrial IoT scenario using a simulated environment. Experimentation shows that, with our proposed strategy, a significant performance improvement on timely responses can be achieved even with noisy cloud environment. Improvements in resource utilization can be also attained for a resource allocation process deployed over Cloud RAN with this strategy.
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