TY - CHAP A1 - Hegde, Anupama A1 - Lobo, Silas A1 - Festag, Andreas T1 - Cellular-V2X for Vulnerable Road User Protection in Cooperative ITS T2 - 2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) UR - https://doi.org/10.1109/WiMob55322.2022.9941707 KW - Radio resource allocation in Cellular-V2X KW - VRU safety and protection KW - messaging services Y1 - 2022 UR - https://doi.org/10.1109/WiMob55322.2022.9941707 SN - 978-1-6654-6975-3 SP - 118 EP - 123 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Hegde, Anupama A1 - Song, Rui A1 - Festag, Andreas T1 - Radio Resource Allocation in 5G-NR V2X: A Multi-Agent Actor-Critic Based Approach JF - IEEE Access N2 - The efficiency of radio resource allocation and scheduling procedures in Cellular Vehicle-to-X (Cellular V2X) communication networks directly affects link quality in terms of latency and reliability. However, owing to the continuous movement of vehicles, it is impossible to have a centralized coordinating unit at all times to manage the allocation of radio resources. In the unmanaged mode of the fifth generation new radio (5G-NR) V2X, the sensing-based semi-persistent scheduling (SB-SPS) loses its effectiveness when V2X data messages become aperiodic with varying data sizes. This leads to misinformed resource allocation decisions among vehicles and frequent resource collisions. To improve resource selection, this study formulates the Cellular V2X communication network as a decentralized multi-agent networked markov decision process (MDP) where each vehicle agent executes an actor-critic-based radio resource scheduler. Developing further the actor-critic methodology for the radio resource allocation problem in Cellular V2X, two variants are derived: independent actor-critic (IAC) and shared experience actor-critic (SEAC). Results from simulation studies indicate that the actor-critic schedulers improve reliability, achieving a 15-20% higher probability of reception under high vehicular density scenarios with aperiodic traffic patterns. UR - https://doi.org/10.1109/ACCESS.2023.3305267 KW - Cellular V2X KW - radio resource allocation KW - deep reinforcement learning Y1 - 2023 UR - https://doi.org/10.1109/ACCESS.2023.3305267 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-39352 SN - 2169-3536 VL - 11 SP - 87225 EP - 87244 PB - IEEE CY - New York ER - TY - CHAP A1 - Song, Rui A1 - Hegde, Anupama A1 - Senel, Numan A1 - Knoll, Alois A1 - Festag, Andreas T1 - Edge-Aided Sensor Data Sharing in Vehicular Communication Networks T2 - 2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring) Proceedings UR - https://doi.org/10.1109/VTC2022-Spring54318.2022.9860849 KW - sensor data sharing and fusion KW - cooperative perception KW - vehicular communication KW - distributed estimation KW - measurement noise Y1 - 2022 UR - https://doi.org/10.1109/VTC2022-Spring54318.2022.9860849 SN - 978-1-6654-8243-1 SN - 2577-2465 PB - IEEE CY - Piscataway (NJ) ER - TY - CHAP A1 - Hegde, Anupama A1 - Festag, Andreas T1 - Mode Switching Performance in Cellular-V2X T2 - 2020 IEEE Vehicular Networking Conference (VNC) UR - https://doi.org/10.1109/VNC51378.2020.9318394 KW - Switches KW - Synchronization KW - Base stations KW - Vehicle-to-everything KW - Resource management KW - Global navigation satellite system KW - Sensors Y1 - 2021 UR - https://doi.org/10.1109/VNC51378.2020.9318394 SN - 978-1-7281-9221-5 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Hegde, Anupama A1 - Festag, Andreas T1 - Mode Switching Strategies in Cellular-V2X JF - IFAC-PapersOnLine UR - https://doi.org/10.1016/j.ifacol.2019.08.052 KW - Cellular-V2X KW - in-coverage mode KW - out-of-coverage mode KW - mode switching KW - latency Y1 - 2019 UR - https://doi.org/10.1016/j.ifacol.2019.08.052 SN - 2405-8963 VL - 52 IS - 8 SP - 81 EP - 86 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Hegde, Anupama A1 - Stahl, Ringo A1 - Lobo, Silas A1 - Festag, Andreas T1 - Modeling Cellular Network Infrastructure in SUMO T2 - SUMO Conference Proceedings N2 - Communication networks are becoming an increasingly important part of the mobility system. They allow traffic participants to be connected and to exchange information related to traffic and roads. The information exchange impacts the behavior of traffic participants, such as the selection of travel routes or their mobility dynamics. Considering infrastructure-based networks, the information exchange depends on the availability of the network infrastructure and the quality of the communication links. Specifically in urban areas, today’s 4G and 5G networks deploy small cells of high capacity, which do not provide ubiquitous cellular coverage due to their small range, signal blocking, etc. Therefore, the accurate modeling of the network infrastructure and its integration in simulation scenarios in microscopic traffic simulation software is gaining relevance. Unlike traffic infrastructure, such as traffic lights, the simulation of a cellular network infrastructure is not natively supported in SUMO. Instead, the protocols, functions and entities of the communication system with the physical wireless transmission are modeled in a dedicated and specialized network simulator that is coupled with SUMO. The disadvantage of this approach is that the simulated SUMO entities, typically vehicles, are not aware which portions of the roads are covered by wireless cells and what quality the wireless communication links have. In this paper, we propose a method for modeling the cellular infrastructure in SUMO that introduces a cellular coverage layer to SUMO. This layer models cell sites in a regular hexagonal grid, where each site is served by a base station. Following commonly accepted guidelines for the evaluation of cellular communication system, the method facilitates standardized and realistic modeling of the cellular coverage, including cell sites, antenna characteristics, cell association and handover. In order to ease the applicability of the method, we describe the work flow to create cell sites. As a representative case, we have applied the method to InTAS, the SUMO Ingolstadt traffic scenario and applied real data for the cellular infrastructure. We validate the approach by simulating a Cellular V2X system with sidelink connectivity in an urban macro cell environment by coupling SUMO enhanced by the proposed connectivity sublayer with ARTERY-C, a network simulator for Cellular V2X. As a proof-of-concept, we present a signal-to-interference noise ratio (SINR) coverage map and further evaluate the impact of different types of interference. We also demonstrate the effect of advanced features of cellular networks such as inter-cell interference coordination (ICIC) and sidelink communication modes of Cellular V2X with dynamic switching between the in-coverage and out-of-coverage mode. UR - https://doi.org/10.52825/scp.v2i.97 Y1 - 2022 UR - https://doi.org/10.52825/scp.v2i.97 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-14785 SN - 2750-4425 VL - 2 SP - 99 EP - 113 PB - TIB Open Publishing CY - Hannover ER - TY - CHAP A1 - Hegde, Anupama A1 - Festag, Andreas T1 - Artery-C: An OMNeT++ Based Discrete Event Simulation Framework for Cellular V2X T2 - MSWiM '20: Proceedings of the 23rd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems UR - https://doi.org/10.1145/3416010.3423240 KW - LTE-V2X KW - Cellular V2X KW - resource allocation KW - simulation Y1 - 2020 UR - https://doi.org/10.1145/3416010.3423240 SN - 978-1-4503-8117-8 SP - 47 EP - 51 PB - ACM CY - New York ER - TY - CHAP A1 - Hegde, Anupama A1 - Delooz, Quentin A1 - Mariyaklla, Chethan L. A1 - Festag, Andreas A1 - Klingler, Florian T1 - Radio Resource Allocation for Collective Perception in 5G-NR Vehicle-to-X Communication Systems T2 - 2023 IEEE Wireless Communications and Networking Conference (WCNC): Proceedings UR - https://doi.org/10.1109/WCNC55385.2023.10118606 KW - Cellular V2X KW - radio resource allocation KW - scheduling KW - collective perception Y1 - 2023 UR - https://doi.org/10.1109/WCNC55385.2023.10118606 SN - 978-1-6654-9122-8 SN - 1558-2612 PB - IEEE CY - Piscataway ER -