human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "ultra reliable and low latency wireless communication tail risk and scale"
  Abstract: Ensuring ultra-reliable and low-latency communication (URLLC) for 5G wireless networks and beyond is of capital importance and is currently receiving tremendous attention in academia and industry. At its core, URLLC mandates a departure from expected utility-based network design approaches, in which relying on average quantities (e.g., average throughput, average delay and average response time) is no longer an option but a necessity. Instead, a principled and scalable framework which takes into account delay, reliability, packet size, network architecture, and topology (across access, edge, and core) and decision-making under uncertainty is sorely lacking. The overarching goal of this article is a first step to fill this void. Towards this vision, after providing definitions of latency and reliability, we closely examine various enablers of URLLC and their inherent tradeoffs. Subsequently, we focus our attention on a plethora of techniques and methodologies pertaining to the requirements of ultra-reliable and low-latency communication, as well as their applications through selected use cases. These results provide crisp insights for the design of low-latency and high-reliable wireless networks.

Connected through hyperedge HE-1 (induced by source paper "optimized age of information tail for ultra reliable low latency communications in vehicular networks"):
  with members:
    - "a general formula for the stationary distribution of the age of information and its application to single server queues"
    - "optimal control of status updates in a multiple access channel with stability constraints"
    - "average peak age of information minimization in uav assisted iot networks"
    - "saddlepoint approximations for rayleigh block fading channels"
    - "optimal status updating with a finite battery energy harvesting source"
    - "statistical guarantee optimization for aoi in single hop and two hop systems with periodic arrivals"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "dynamic task offloading and resource allocation for ultra reliable low latency edge computing"

Connected through hyperedge HE-2 (induced by source paper "distributed federated learning for ultra reliable low latency vehicular communications"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "client selection for federated learning with heterogeneous resources in mobile edge"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "federated learning for ultra reliable low latency v2v communications"
    - "federated learning strategies for improving communication efficiency"
    - "joint communication and control for wireless autonomous vehicular platoon systems"
    - "ultra reliable and low latency vehicular transmission an extreme value theory approach"
    - "joint status sampling and updating for minimizing age of information in the internet of things"

Connected through hyperedge HE-3 (induced by source paper "towards reliable uav swarm communication in d2d enhanced cellular network"):
  with members:
    - "unmanned aerial vehicles uavs a survey on civil applications and key research challenges"
    - "cellular connected uav uplink association power control and interference coordination"
    - "multi beam uav communication in cellular uplink cooperative interference cancellation and sum rate maximization"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "ultra reliable uav communication using altitude and cooperation diversity"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "uplink cooperative noma for cellular connected uav"
    - "a d2d based protocol for ultra reliable wireless communications for industrial automation"

Connected through hyperedge HE-4 (induced by source paper "intelligent resource slicing for embb and urllc coexistence in 5g and beyond a deep reinforcement learning based approach"):
  with members:
    - "extreme urllc vision challenges and key enablers"
    - "coexistence mechanism between embb and urllc in 5g wireless networks"
    - "embb urllc resource slicing a risk sensitive approach"
    - "ultra reliable and low latency vehicular transmission an extreme value theory approach"
    - "coexistence of urllc and embb services in the c ran uplink an information theoretic study"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "urllc embb slicing to support vr multimodal perceptions over wireless cellular systems"

Connected through hyperedge HE-5 (induced by source paper "effective capacity of noma with finite blocklength for low latency communications"):
  with members:
    - "on the performance of non orthogonal multiple access in the finite blocklength regime"
    - "effective capacity and power allocation for machine type communication"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "short packet downlink transmission with non orthogonal multiple access"
    - "performance analysis of noma for ultra reliable and low latency communications"
    - "effective capacity in wireless networks a comprehensive survey"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"

Connected through hyperedge HE-6 (induced by source paper "resource allocation for secure multi user downlink miso urllc systems"):
  with members:
    - "secure short packet communications for mission critical iot applications"
    - "resource allocation for multi user downlink miso ofdma urllc systems"
    - "resource allocation for multi user downlink urllc ofdma systems"
    - "robust and secure resource allocation for full duplex miso multicarrier noma systems"
    - "wiretap channels nonasymptotic fundamental limits"
    - "coding in the finite blocklength regime bounds based on laplace integrals and their asymptotic approximations"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "energy efficient packet scheduling with finite blocklength codes convexity analysis and efficient algorithms"

Connected through hyperedge HE-7 (induced by source paper "risk sensitive task fetching and offloading for vehicular edge computing"):
  with members:
    - "application of machine learning in wireless networks key techniques and open issues"
    - "ultra reliable and low latency vehicular transmission an extreme value theory approach"
    - "a survey on mobile edge computing the communication perspective"
    - "backhaul aware interference management in the uplink of wireless small cell networks"

Connected through hyperedge HE-8 (induced by source paper "deep learning based wireless resource allocation with application to vehicular networks"):
  with members:
    - "learning to branch accelerating resource allocation in wireless networks"
    - "spectrum sharing in vehicular networks based on multi agent reinforcement learning"
    - "learning to detect"
    - "learning optimal resource allocations in wireless systems"
    - "deep learning based end to end wireless communication systems with conditional gan as unknown channel"
    - "distributed power control for large energy harvesting networks a multi agent deep reinforcement learning approach"
    - "power allocation in multi user cellular networks deep reinforcement learning approaches"
    - "toward intelligent vehicular networks a machine learning framework"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)