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: "map aware models for indoor wireless localization systems an experimental study"
  Abstract: The accuracy of indoor wireless localization systems can be substantially enhanced by map-awareness, i.e., by the knowledge of the map of the environment in which localization signals are acquired. In fact, this knowledge can be exploited to cancel out, at least to some extent, the signal degradation due to propagation through physical obstructions, i.e., to the so called non-line-of-sight bias. This result can be achieved by developing novel localization techniques that rely on proper map-aware statistical modelling of the measurements they process. In this manuscript a unified statistical model for the measurements acquired in map-aware localization systems based on time-of-arrival and received signal strength techniques is developed and its experimental validation is illustrated. Finally, the accuracy of the proposed map-aware model is assessed and compared with that offered by its map-unaware counterparts. Our numerical results show that, when the quality of acquired measurements is poor, map-aware modelling can enhance localization accuracy by up to 110% in certain scenarios.

Connected through hyperedge HE-1 (induced by source paper "single anchor localization and orientation performance limits using massive arrays mimo vs beamforming"):
  with members:
    - "direct localization for massive mimo"
    - "error bounds for uplink and downlink 3d localization in 5g mmwave systems"
    - "performance limits and geometric properties of array localization"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "massive mimo for next generation wireless systems"
    - "emerging technologies and research challenges for 5g wireless networks"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "fundamental limits of wideband localization part i a general framework"

Connected through hyperedge HE-2 (induced by source paper "static force field representation of environments based on agents nonlinear motions"):
  with members:
    - "incremental learning of environment interactive structures from trajectories of individuals"
    - "online pedestrian group walking event detection using spectral analysis of motion similarity graph"
    - "decentralized self organizing potential field based control for individually motivated mobile agents in a cluttered environment a vector harmonic potential field approach"

Connected through hyperedge HE-3 (induced by source paper "location verification systems under spatially correlated shadowing"):
  with members:
    - "location verification systems for vanets in rician fading channels"
    - "location spoofing detection for vanets by a single base station in rician fading channels"
    - "optimal information theoretic wireless location verification"
    - "cramer rao bounds for joint rss doa based primary user localization in cognitive radio networks"
    - "an information theoretic location verification system for wireless networks"

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)