5G QoS Flow Migration Over URLLC Relays

Abstract

Ultra-Reliable Low Latency Communications (URLLC), a key area of 5G, is designed to support dependable and time-sensitive communications. Yet when addressing Quality of Service (QoS) requirements, traditional 5G does not consider delay spread an interference metric reported back to the base station (as delay spread approaches the duration of the cyclic prefix, the channel capacity decreases due to inter-symbol interference). As IoT equipment may lack the processing capability to mitigate delay spread’s effects, not accounting for delay spread in reported channel condition metrics can result in resources not being assigned in an efficient manner.For out-of-coverage remote devices, such as in smart factories and Industrial Internet of Things [1] (IIoT), Non-Orthogonal Multiple Access (NOMA) small cells or Layer 3 User Equipment (UE) to Network (UE-to-Network) relays must be relied on to extend the network to localized areas. Due to power domain NOMA’s Resource Block (RB) multiplexing, in a multi-level NOMA system the impact of delay spread on the set of viable resource allocations becomes more evident as the interference generated can render 2nd level RBs unusable. Consequently, the likelihood of achieving URLLC’s low End-to-End Radio Latency requirements becomes more difficult in multi-level NOMA systems.In this paper we investigate a tractable methodology to mitigate the impact of delay spread and improve the End-to-End latency of IIoT devices via 5G NOMA multicast flow numerology migration for URLLC NOMA relays used in a non-public network. We derive a theoretically optimal integer linear programming (ILP) resource allocation algorithm and present a tractable low-complexity approximation algorithm, 5G Multicast Flow Migration over NOMA (5GMFMN). In terms of end-to-end radio latency, our evaluation shows 5GMFMN yields results similar to ILP, and both algorithms can yield over 4× improvement over traditional 5G at a max delay spread of 2.1µs.