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 distortion of the eigenvalue spectrum in mimo amplify and forward multi hop channels"
  Abstract: Consider a wireless MIMO multi-hop channel with n_s non-cooperating source antennas and n_d fully cooperating destination antennas, as well as L clusters containing k non-cooperating relay antennas each. The source signal traverses all L clusters of relay antennas, before it reaches the destination. When relay antennas within the same cluster scale their received signals by the same constant before the retransmission, the equivalent channel matrix H relating the input signals at the source antennas to the output signals at the destination antennas is proportional to the product of channel matrices H_l, l=1,...,L+1, corresponding to the individual hops. We perform an asymptotic capacity analysis for this channel as follows: In a first instance we take the limits n_s->infty, n_d->infty and k->infty, but keep both n_s/n_d and k/n_d fixed. Then, we take the limits L->infty and k/n_d->infty. Requiring that the H_l's satisfy the conditions needed for the Marcenko-Pastur law, we prove that the capacity scales linearly in min{n_s,n_d}, as long as the ratio k/n_d scales at least linearly in L. Moreover, we show that up to a noise penalty and a pre-log factor the capacity of a point-to-point MIMO channel is approached, when this scaling is slightly faster than linear. Conversely, almost all spatial degrees of freedom vanish for less than linear scaling.

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)