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: "performance analysis and design of maximum ratio combining in channel aware mimo decision fusion"
  Abstract: In this paper we present a theoretical performance analysis of the maximum ratio combining (MRC) rule for channel-aware decision fusion over multiple-input multiple-output (MIMO) channels for (conditionally) dependent and independent local decisions. The system probabilities of false alarm and detection conditioned on the channel realization are derived in closed form and an approximated threshold choice is given. Furthermore, the channel-averaged (CA) performances are evaluated in terms of the CA system probabilities of false alarm and detection and the area under the receiver operating characteristic (ROC) through the closed form of the conditional moment generating function (MGF) of the MRC statistic, along with Gauss-Chebyshev (GC) quadrature rules. Furthermore, we derive the deflection coefficients in closed form, which are used for sensor threshold design. Finally, all the results are confirmed through Monte Carlo simulations.

Connected through hyperedge HE-1 (induced by source paper "rician mimo channel and jamming aware decision fusion"):
  with members:
    - "decision fusion with unknown sensor detection probability"
    - "massive mimo for wireless sensing with a coherent multiple access channel"
    - "optimality of received energy in decision fusion over rayleigh fading diversity mac with non identical sensors"
    - "optimal power allocation for distributed detection over mimo channels in wireless sensor networks"

Connected through hyperedge HE-2 (induced by source paper "the area under a receiver operating characteristic curve over nakagami q fading channels"):
  with members:
    - "analytic solutions to a marcum q function based integral and application in energy detection of unknown signals over multipath fading channels"
    - "analytic performance evaluation of underlay relay cognitive networks with channel estimation errors"

Connected through hyperedge HE-3 (induced by source paper "the area under a receiver operating characteristic curve over enriched multipath fading conditions"):
  with members:
    - "analytic solutions to a marcum q function based integral and application in energy detection of unknown signals over multipath fading channels"
    - "analytic performance evaluation of underlay relay cognitive networks with channel estimation errors"

Connected through hyperedge HE-4 (induced by source paper "decision fusion with unknown sensor detection probability"):
  with members:
    - "optimality of received energy in decision fusion over rayleigh fading diversity mac with non identical sensors"

Connected through hyperedge HE-5 (induced by source paper "orthogonality and cooperation in collaborative spectrum sensing through mimo decision fusion"):
  with members:
    - "optimality of received energy in decision fusion over rayleigh fading diversity mac with non identical sensors"
    - "coalition formation games for collaborative spectrum sensing"

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)