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 non cooperative method for path loss estimation in femtocell networks"
  Abstract: A macrocell superposed by indoor deployed femtocells forms a geography-overlapped and spectrum-shared two tier network, which can efficiently improve coverage and enhance system capacity. It is important for reducing inter-tier co-channel interference that any femtocell user (FU) can select suitable access channel according to the path losses between itself and the macrocell users (MUs). Path loss should be estimated non-cooperatively since information exchange is difficult between macrocell and femtocells. In this paper, a novel method is proposed for FU to estimate the path loss between itself and any MU independently. According to the adaptive modulation and coding (AMC) mode information broadcasted by the macrocell base station (BS), FU first estimates the path loss between BS and a MU by using Maximum a Posteriori (MAP) method. The probability distribution function (PDF) and statistics of the transmission power of the MU is then derived. According to the sequence of received powers from the MU, FU estimates the path loss between itself and the MU by using minimum mean square error (MMSE) method. Simulation results show that the proposed method can efficiently estimate the path loss between any FU and any MU in all kinds of conditions.

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.NI(Networking and Internet Architecture)