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: "a unified effective capacity performance analysis of lp norm diversity reception over arbitrary and correlated generalized fading channels"
  Abstract: The effective capacity (EC) has been recently established as a rigorous alternative to the classical Shannon's ergodic capacity since it accounts for the delay constraints imposed by future wireless applications and their impact on the overall system performance. This paper presents a novel moment generating function (MGF)-based framework for the unified EC performance analysis of a generic Lp-norm diversity combining scheme operating over arbitrary and correlated generalized fading channels and a maximum delay constraint. The Lp-norm diversity is a generic diversity structure which includes as special cases various well-known diversity schemes such as equal gain combining (EGC) and maximal ratio combining (MRC). For MRC, the proposed methodology reduces to a previously published MGF-based approach for the evaluation of the EC, whereas, for EGC, analytical approach presented is novel and the associated performance evaluation results have not been published previously in the open technical literature. Based on this methodology, novel analytical closed-form expressions for the EC performance of dual branch Lp-norm diversity receivers operating over Gamma shadowed generalized Nakagami-m fading channels are deduced. For diversity order greater than two, a novel analytical approach for the asymptotic EC performance analysis is also developed and evaluated, revealing how basic system parameters affect the overall system performance. The overall mathematical formalism is validated with selected numerical and equivalent simulation performance evaluation results thus confirming the correctness of the proposed unified analytical methodology.

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)