The future connectivity landscape, and notably, the 5G wireless systems will feature Ultra-Reliable Low Latency Communication (URLLC). The coupling of high reliability and low latency requirements in URLLC use cases makes the wireless access design very challenging, in terms of both the protocol design and of the associated transmission techniques. This paper aims to provide a broad perspective on the fundamental tradeoffs in URLLC, as well as the principles used in building access protocols. Two specific technologies are considered in the context of URLLC: massive MIMO and multi-connectivity, also termed interface diversity . This paper also touches on the importance of the proper statistical methodology for designing and assessing extremely high-reliability levels.
5G is currently being standardized and addresses, among other things, new URLLC services. These are characterized by the need to support reliable communication, where successful data transmission can be guaranteed within low latency bounds, like 1 ms, at a low failure rate. This article describes the functionality of both the NR and LTE radio interfaces to provide URLLC services. Achievable latency bounds are evaluated, and the expected spectral efficiency is demonstrated. It is shown that both NR and LTE can fulfill the ITU 5G requirements on URLLC; however, this comes at the cost of reduced spectral efficiency compared to mobile broadband services without latency or reliability constraints. Still, the impact on the overall network performance is expected to be moderate. This paper studies Ultra-Reliable Low-Latency Communications (URLLC), an important service class of emerging 5G networks. In this class, multiple unreliable transmissions must be combined to achieve reliable latency: a user experiences a frame success when the entire L bits are received correctly within a deadline, and its latency performance is reliable when the frame success rate is above a threshold. When jointly serving multiple users, a natural URLLC scheduling question arises: given the uncertainty of the wireless channel, can we find a scheduling policy that allows all users to meet a target reliable latency objective? This is called the URLLC SLA Satisfaction (USS) problem. The USS problem is an infinite horizon constrained Markov Decision Process, for which, after establishing a convenient property, we are able to derive an optimal policy based on dynamic programming. Our policy suffers from the curse of dimensionality, hence for large instances we propose a class of knapsack-inspired computationally efficient — but not necessarily optimal — policies. We prove that every policy in that class becomes optimal in a fluid regime, where both the deadline and L scale to infinity, while our simulations show that the policies perform well even in small practical instances of the USS problem.  Supporting ultra-reliable and low-latency communications (URLLC) is one of the major goals in 5G communication systems. Previous studies focus on ensuring end-to-end delay requirement by reducing transmission delay and coding delay, and only consider reliability in data transmission. However, the reliability reflected by overall packet loss also includes other components such as queueing delay violation. Moreover, which tools are appropriate to design radio resource allocation under constraints on delay, reliability, and availability is not well understood. As a result, how to optimize resource allocation for URLLC is still unclear. In this article, we first discuss the delay and packet loss components in URLLC and the network availability for supporting the quality of service of users. Then we present tools for resource optimization in URLLC. Last, we summarize the major challenges related to resource management for URLLC, and perform a case study.