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: "asymptotic equipartition property of output when rate is above capacity"
  Abstract: The output distribution, when rate is above capacity, is investigated. It is shown that there is an asymptotic equipartition property (AEP) of the typical output sequences, independently of the specific codebook used, as long as the codebook is typical according to the standard random codebook generation. This equipartition of the typical output sequences is caused by the mixup of input sequences when there are too many of them, namely, when the rate is above capacity. This discovery sheds some light on the optimal design of the compress-and-forward relay schemes.

Connected through hyperedge HE-1 (induced by source paper "half duplex active eavesdropping in fast fading channels a block markov wyner secrecy encoding scheme"):
  with members:
    - "the gaussian multiple access wire tap channel"

Connected through hyperedge HE-2 (induced by source paper "interference alignment and a noisy interference regime for many to one interference channels"):
  with members:
    - "ergodic fading interference channels sum capacity and separability"
    - "capacity regions and sum rate capacities of vector gaussian interference channels"
    - "on the degrees of freedom of finite state compound wireless networks settling a conjecture by weingarten et al"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "interference alignment with asymmetric complex signaling settling the host madsen nosratinia conjecture"
    - "capacity of a class of symmetric simo gaussian interference channels within o 1"
    - "gaussian interference networks sum capacity in the low interference regime and new outer bounds on the capacity region"
    - "capacity bounds for the gaussian interference channel"

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)