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: "massive mimo for drone communications applications case studies and future directions"
  Abstract: Unmanned aerial vehicles (UAVs), or drones, are proliferating. Several applications, such as surveillance, disaster management, and drone racing, place high requirements on the communication with the drones - in terms of throughout, reliability, 3D connectivity, and latency. Existing wireless technologies, notably WiFi, that are currently used for drone communications are limited to short ranges and low-mobility situations. A new, scalable technology is needed to meet future demands. Massive MIMO, a promising technology component of emerging 5G cellular networks, has the potential to meet these requirements. Specifically, Massive MIMO offers significant range extensions, support for fast-moving drones, and the possibility to spatially multiplex entire swarms of drones communicating simultaneously.

Connected through hyperedge HE-1 (induced by source paper "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges"):
  with members:
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "supporting uav cellular communications through massive mimo"
    - "uav aided offloading for cellular hotspot"
    - "the essential guide to realizing 5g connected uavs with massive mimo"
    - "performance analysis for practical unmanned aerial vehicle networks with los nlos transmissions"
    - "promises and caveats of uplink iot ultra dense networks"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"

Connected through hyperedge HE-2 (induced by source paper "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"):
  with members:
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "comp in the sky uav placement and movement optimization for multi user communications"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "uav aided offloading for cellular hotspot"
    - "energy minimization for wireless communication with rotary wing uav"

Connected through hyperedge HE-3 (induced by source paper "understanding uav cellular communications from existing networks to massive mimo"):
  with members:
    - "cellular connected uav potentials challenges and promising technologies"
    - "supporting uav cellular communications through massive mimo"
    - "the essential guide to realizing 5g connected uavs with massive mimo"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "interference mitigation methods for unmanned aerial vehicles served by cellular networks"
    - "reshaping cellular networks for the sky the major factors and feasibility"
    - "massive mimo for communications with drone swarms"

Connected through hyperedge HE-4 (induced by source paper "multi beam uav communication in cellular uplink cooperative interference cancellation and sum rate maximization"):
  with members:
    - "mobile networks connected drones field trials simulations and design insights"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "massive mimo for communications with drone swarms"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "coexistence of terrestrial and aerial users in cellular networks"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "optimized uplink transmission in multi antenna c ran with spatial compression and forward"

Connected through hyperedge HE-5 (induced by source paper "the essential guide to realizing 5g connected uavs with massive mimo"):
  with members:
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "cellular connected uav potentials challenges and promising technologies"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "a telecom perspective on the internet of drones from lte advanced to 5g"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "interference mitigation methods for unmanned aerial vehicles served by cellular networks"
    - "reshaping cellular networks for the sky the major factors and feasibility"
    - "massive mimo unlicensed a new approach to dynamic spectrum access"

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)