Dynamic Multipath Resource Management for Ultra Reliable Low Latency Services One of the core novel features of 5G networks is the support of ultrareliable low latency communications (URLLC). This will pave the way for a plethora of mission critical applications in diverse sectors including health, security, gaming, and manufacturing, among others, through guaranteed premium grade reliability and delay; yet, this requires the development of innovative mechanisms that can address the existing challenges. In this work, we focus on the simultaneous utilization of multiple paths via different wireless interfaces and networks in order to deliver data from source to destination in a timely manner and with high reliability. We formulate the problem as a mixed integer program and generate an optimized strategy to efficiently utilize the resources among the different paths. Simulation results are presented for various scenarios to quantify performance gains with respect to other alternative approaches.

TwinTimescale Radio Resource Management for UltraReliable and LowLatency Vehicular Networks To efficiently support safetyrelated vehicular applications, the ultrareliable and lowlatency communication (URLLC) concept has become an indispensable component of vehicular networks (VNETs). Due to the high mobility of VNETs, exchanging nearinstantaneous channel state information (CSI) and making reliable resource allocation decisions based on such shortterm CSI evaluations are not practical. In this paper, we consider the downlink of a vehicletoinfrastructure (V2I) system conceived for URLLC based on idealized perfect and realistic imperfect CSI. By exploiting the benefits of the massive MIMO concept, a twostage radio resource allocation problem is formulated based on a novel twintimescale perspective for avoiding the frequent exchange of nearinstantaneous CSI. Specifically, based on the prevalent roadtraffic density, Stage 1 is constructed for minimizing the worstcase transmission latency on a longterm timescale. In Stage 2, the base station allocates the total power at a shortterm timescale according to the largescale fading CSI encountered for minimizing the maximum transmission latency across all vehicular users. Then, a primary algorithm and a secondary algorithm are conceived for our V2I URLLC system to find the optimal solution of the twintimescale resource allocation problem, with special emphasis on the complexity imposed. Finally, our simulation results show that the proposed resource allocation scheme significantly reduces the maximum transmission latency, and it is not sensitive to the fluctuation of roadtraffic density.