# Emerging Trends in Hybrid Wireless Communication and Data Management for the Industry 4.0
## 3 Challenges
### Communication Challenges  
The identified communication requirements impose significant challenges to the underlying communication system. Extremely low latencies require the rapid allocation of the radio resources to transmit the data, or the pre-allocation of such resources. The maximum end-to-end latency tolerated limits the number of possible retransmissions to successfully deliver the data. Under relaxed latency constraints, a high number of retransmissions are possible, which relaxes the necessary PER (PacketError Rate) and therefore the MCS (Modulation and Coding Scheme) to be used. We can indeed relate the CSA and the maximum tolerated PER together with the number of retransmissions using the following equation, considering that the same PER is experienced in all the retransmissions and that packet loses are independent from each other:  
\[PER=\left(1-CSA\right)^{1/retx} \tag{1}\]  
where _retx_ is the maximum number of retransmissions that can be performed within the maximum latency. Figure 2a shows the relationship between \(PER\) and \(1-CSA\) for different values of the number of retransmissions using logarithmic scales for clarity. As it can be observed, achieving a \(CSA\) between \(1-10^{-6}\) and \(1-10^{-8}\) requires a \(PER\) between \(10^{-4}\) and \(10^{-3}\) if only 2 retransmissions are allowed (which would be the case if the required latency is very low).  
The \(PER\) can also be used to estimate the mean time between failures (_MTBF_) [23], which is a popular indicator of the communication service reliability and can be defined as the average elapsed time between inherent failures of a system, during normal system operation. If we consider that a system failure is produced whenever a piece of data cannot be successfully transmitted within the required maximum end-to-end latency, we can estimate the _MTBF_ from the underlying \(PER\). Assuming a constant failure probability, the \(MTBF\) can be calculated as the reciprocal of the failure probability of the system [23]. Considering only communication failures, the failure probability can be expressed as:  
\[F=PER^{retx} \tag{2}\]  
since all the retransmissions would need to fail to produce the loss of data before the tolerated latency. The \(MTBF\) can be therefore expressed as a function of the \(PER\), \(retx\), and the maximum tolerated latency, \(L\), as:  
\[MTBF=L/F=L/PER^{retx} \tag{3}\]  
Figure 2b shows the \(MTBF\) as a function of the \(PER\) for different number of possible retransmissions considering \(L\) = 10 ms. As it can be observed, for medium and high \(PER\) values, the system is very likely to fail and therefore \(MTBF\) values are low. As the \(PER\) is decreased (as a result of, e.g., a better interference management, channel access of PHY layer performance), the \(MTBF\) can be significantly increased, especially if the number of possible retransmissions increases.  
Figure 2: Communication service availability (CSA) and mean time between failures (MTBF) as a function of the packet error rate (PER) and the number of possible retransmissions (_retx_) for \(L\) = 10 ms.