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: "error vector magnitude analysis in generalized fading with co channel interference"
  Abstract: In this paper, we derive the data-aided Error Vector Magnitude (EVM) in an interference limited system when both the desired signal and interferers experience independent and non identically distributed $\kappa$-$\mu$ shadowed fading. Then it is analytically shown that the EVM is equal to the square root of number of interferers when the desired signal and interferers do not experience fading. Further, EVM is derived in the presence of interference and noise, when the desired signal experiences $\kappa$-$\mu$ shadowed fading and the interferers experience independent and identical Nakagami fading. Moreover, using the properties of the special functions, the derived EVM expressions are also simplified for various special cases.

Connected through hyperedge HE-1 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading"):
  with members:
    - "asymptotic performance analysis of generalized user selection for interference limited multiuser secondary networks"
    - "asymptotic maximal order statistic for sir in κ μ shadowed fading"
    - "mimo underlay cognitive radio optimized power allocation effective number of transmit antennas and harvest transmit tradeoff"
    - "outage probability and rate for kappa mu shadowed fading in interference limited scenario"
    - "coverage analysis in downlink poisson cellular network with kappa mu shadowed fading"
    - "relay selection improves the security reliability trade off in cognitive radio systems"
    - "spectrum sharing multi hop cooperative relaying performance analysis using extreme value theory"
    - "the effects of limited channel knowledge on cognitive radio system capacity"

Connected through hyperedge HE-2 (induced by source paper "asymptotic maximal order statistic for sir in κ μ shadowed fading"):
  with members:
    - "outage probability and rate for kappa mu shadowed fading in interference limited scenario"
    - "coverage analysis in downlink poisson cellular network with kappa mu shadowed fading"
    - "massive mimo ten myths and one critical question"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "massive mimo performance evaluation based on measured propagation data"
    - "massive mimo for next generation wireless systems"
    - "on the sum of correlated squared kappa mu shadowed random variables and its application to performance analysis of mrc"
    - "spectrum sharing multi hop cooperative relaying performance analysis using extreme value theory"

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)