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 computation of the higher order statistics of the channel capacity over generalized fading channels"
  Abstract: The higher-order statistics (HOS) of the channel capacity $\mu_n=\mathbb{E}[\log^n(1+\gamma_{end})]$, where $n\in\mathbb{N}$ denotes the order of the statistics, has received relatively little attention in the literature, due in part to the intractability of its analysis. In this letter, we propose a novel and unified analysis, which is based on the moment generating function (MGF) technique, to exactly compute the HOS of the channel capacity. More precisely, our mathematical formalism can be readily applied to maximal-ratio-combining (MRC) receivers operating in generalized fading environments (i.e., the sum of the correlated noncentral chi-squared distributions / the correlated generalized Rician distributions). The mathematical formalism is illustrated by some numerical examples focussing on the correlated generalized fading environments.

Connected through hyperedge HE-1 (induced by source paper "on the asymptotic analysis of the high order statistics of the channel capacity over generalized fading channels"):
  with members:
    - "a novel ergodic capacity analysis of diversity combining and multihop transmission systems over generalized composite fading channels"
    - "on the computation of the higher order statistics of the channel capacity for amplify and forward multihop transmission"
    - "a novel unified expression for the capacity and bit error probability of wireless communication systems over generalized fading channels"
    - "a unified mgf based capacity analysis of diversity combiners over generalized fading channels"
    - "extended generalized k egk a new simple and general model for composite fading channels"

Connected through hyperedge HE-2 (induced by source paper "on the relationships between average channel capacity average bit error rate outage probability and outage capacity over additive white gaussian noise channels"):
  with members:
    - "on the asymptotic analysis of the high order statistics of the channel capacity over generalized fading channels"
    - "asymptotic capacity analysis for adaptive transmission schemes under general fading distributions"
    - "a novel ergodic capacity analysis of diversity combining and multihop transmission systems over generalized composite fading channels"
    - "a unified mgf based capacity analysis of diversity combiners over generalized fading channels"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-3 (induced by source paper "a unified effective capacity performance analysis of lp norm diversity reception over arbitrary and correlated generalized fading channels"):
  with members:
    - "unified framework for the effective rate analysis of wireless communication systems over miso fading channels"
    - "a new formula for the ber of binary modulations with dual branch selection over generalized k"
    - "a unified mgf based capacity analysis of diversity combiners over generalized fading channels"

Connected through hyperedge HE-4 (induced by source paper "on high order capacity statistics of spectrum aggregation systems over kappa mu and kappa mu shadowed fading channels"):
  with members:
    - "on the sum of correlated squared kappa mu shadowed random variables and its application to performance analysis of mrc"
    - "statistical characterization of kappa mu shadowed fading"
    - "on the computation of the higher order statistics of the channel capacity for amplify and forward multihop transmission"

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)