Cross-Layer Design and Performance Analysis for Ultra-Reliable Factory of the Future Based on 5G Mobile Networks

Abstract

To provide a new level of reliability, latency, and support a massive number of users and smart objects, a new 5G multi-services air interface needs to be addressed for the factory of the future (FoF). However, there are limitations in providing connectivity to a dynamic machine in a factory due to several strict industrial automation requirements. In particular, the strict wireless communication latency and reliability requirements are the major challenges to enable the Industry 4.0 vision. In this paper, a PHY-MAC layer cross-layer model that combines a semi-persistent scheduling at the medium access control layer and NOMA at the physical layer has been proposed to address the limitations. The work extensively investigates the performance of the factory of the future with various considerations of 5G spectrums (in this case 3.5 GHz and 28 GHz), speeds and frequency diversity. In addition, the packet error rate (PER), outage probability and throughput in MAC are evaluated in terms of network density deployment (sparse, moderate, dense), different kinds of speed; 0 km/h, 3 km/h, 7 km/h and 10 km/h, under two 5G frequency spectrums. Through extensive simulations, the considered 5G system parameters produced better results in terms of reliability, where the results showed that the frequency diversity outperformed non-diversity by 2 dB. In a sparse network, the PER results showed better results compared to the dense network density by 2 dB (MMSE), 8 dB (LS-Linear) and 2 dB (LS-Spline). Besides that, robotics in sparse network density and stationary exhibited the best PER results, which is as low as 10 -7 . Moreover, the performance of mid-band frequency outperformed the high-band frequency by 1.8dB (MMSE) in dense condition and 1.5 dB (MMSE) in sparse deployment at PER = 10 -6 . Hence, this study could be a useful insight for the factory of the future services that are utilizing a 5G mid-band spectrum as well as a high-band spectrum.

Application Layer-Forward Error Correction Raptor Q Codes in 5G Mobile Networks for Factory of the Future

“…(2) MAC layer: indoor factory cross-layer design simulator as proposed in work [45] where the results obtained from [45] are to be used and analyzed The indoor factory broadcast concept is based on [48], where it enables a simple, rapid, and large-scale transmission of messages without feedback to the sensors/actuators. It eliminates the need for complicated routing and avoids coverage limitations by reducing reliance on high-cost infrastructure rollout.…”

“…The MAC system model has been explained in our previous work in [45]. To summarize, a cross-layer design for an indoor factory of the future is designed and developed to suit the stringent requirements for URLLC.…”

“…To summarize, a cross-layer design for an indoor factory of the future is designed and developed to suit the stringent requirements for URLLC. In work [45], a cross-layer strategy is proposed by utilizing semi-persistent scheduling (SPS) at MAC and code-domain NOMA at PHY to achieve an ultra-reliable communication (URC) for potential 5G mobile network deployment for the factory of the future. By having outputs from [45], results of PER mac , throughput mac , and outage probability are critically evaluated and analyzed by varying multiple parameters such as network densities (sparse, moderate, and dense), various speed of sensors/actuators that are realistic to the indoor factory scenarios (static, 3 km/h, 7 km/h, and 10 km/h), and two allocated 5G frequency spectrums, which is mid-band (3.5 GHz) and high band (28 GHz).…”

“…The reason for using two different types of spectrums at MAC layer is to investigate the characteristics of the spectrums when it is deployed in an indoor factory. Based on the results in [45], it is shown that the mid-band spectrum outperformed the high band due to the high-band spectrum being highly susceptible to the clutters present in the factory. The traffic model considered in the MAC layer block is periodic since SPS is utilized in the MAC layer; it has the advantage of manipulating the previous knowledge regarding the traffic characteristics.…”

“…(1) This paper is the extended work from [30] where the authors investigated and designed the PHY-MAC cross-layer model by introducing the NOMA technique at the PHY layer and utilizing semi-persistent scheduling at the MAC layer in an indoor factory scenario. However, the proposed work in [45] had only been investigated until the MAC layer and not entirely investigated until the system/application level of the indoor factory. Hence, this paper focuses on the APP layer performance analysis by introducing Raptor Q codes to improve the overall reliability and end-toend delay by tackling the packet losses…”