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 gaussian z interference channel with processing energy cost"
  Abstract: This work considers a Gaussian interference channel with processing energy cost, which explicitly takes into account the energy expended for processing when each transmitter is on. With processing overhead, bursty transmission at each transmitter generally becomes more advantageous. Assuming on-off states do not carry information, for a two-user Z-interference channel, the new regime of very strong interference is identified and shown to be enlarged compared with the conventional one. With the interfered receiver listening when its own transmitter is silent, for a wide range of cross-link power gains, one can either achieve or get close to the interference-free upper bound on sum rate.

Connected through hyperedge HE-1 (induced by source paper "energy efficient communication over gaussian interference networks with processing energy cost"):
  with members:
    - "on the sum capacity of k user cascade gaussian z interference channel"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "capacity bounds for the gaussian interference channel"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-2 (induced by source paper "transmission schemes for gaussian interference channels with transmitter processing energy"):
  with members:
    - "on the sum capacity of k user cascade gaussian z interference channel"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "capacity bounds for the gaussian interference channel"
    - "gaussian interference channel capacity to within one bit"

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)