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: "on the effect of shadowing correlation on wireless network performance"
  Abstract: We propose and analyze a new shadowing field model meant to capture spatial correlations. The interference field associated with this new model is compared to that of the widely used independent shadowing model. Independent shadowing over links is adopted because of the resulting closed forms for performance metrics, and in spite of the well-known fact that the shadowing fields of networks are spatially correlated. The main purpose of this paper is to challenge this independent shadowing approximation. For this, we analyze the interference measured at the origin in networks where 1) nodes which are in the same cell of some random shadowing tessellation share the same shadow, or 2) nodes which share a common mother point in some cluster process share the same shadow. By leveraging stochastic comparison techniques, we give the order relation of the three main user performance metrics, namely coverage probability, Shannon throughput and local delay, under both the correlated and the independent shadowing assumptions. We show that the evaluation of the considered metrics under the independent approximation is systematically pessimistic compared to the correlated shadowing model. The improvement in each metric when adopting the correlated shadow model is quantified and shown to be quite significant.

Connected through hyperedge HE-1 (induced by source paper "exploiting randomly located blockages for large scale deployment of intelligent surfaces"):
  with members:
    - "intelligent reflecting surface versus decode and forward how large surfaces are needed to beat relaying"
    - "joint active and passive beamforming optimization for intelligent reflecting surface assisted swipt under qos constraints"
    - "holographic mimo surfaces for 6g wireless networks opportunities challenges and trends"
    - "a novel communication paradigm for high capacity and security via programmable indoor wireless environments in next generation wireless systems"
    - "large intelligent surface antennas lisa making reflective radios smart"
    - "secure wireless communication via intelligent reflecting surface"
    - "reflection probability in wireless networks with metasurface coated environmental objects an approach based on random spatial processes"
    - "resource allocation for secure irs assisted multiuser miso systems"

Connected through hyperedge HE-2 (induced by source paper "a tractable analysis of the blind spot probability in localization networks under correlated blocking"):
  with members:
    - "accurately accounting for random blockage in device to device mmwave networks"
    - "asymptotic blind spot analysis of localization networks under correlated blocking using a poisson line process"
    - "analysis of human body blockage in urban millimeter wave cellular communications"
    - "a tractable analysis of the improvement in unique localizability through collaboration"
    - "analysis of blockage effects on urban cellular 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)