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 capacity of the two user gaussian causal cognitive interference channel"
  Abstract: This paper considers the two-user Gaussian causal cognitive interference channel (GCCIC), which consists of two source-destination pairs that share the same channel and where one full-duplex cognitive source can causally learn the message of the primary source through a noisy link. The GCCIC is an interference channel with unilateral source cooperation that better models practical cognitive radio networks than the commonly used model which assumes that one source has perfect noncausal knowledge of the other source's message. First, the sum-capacity of the symmetric GCCIC is determined to within a constant gap. Then, the insights gained from the study of the symmetric GCCIC are extended to more general cases. In particular, the whole capacity region of the Gaussian Z-channel, i.e., when there is no interference from the primary user, and of the Gaussian S-channel, i.e., when there is no interference from the secondary user, are both characterized to within 2 bits. The fully connected general, i.e., no-symmetric, GCCIC is also considered and its capacity region is characterized to within 2 bits when, roughly speaking, the interference is not weak at both receivers. The parameter regimes where the GCCIC is equivalent, in terms of generalized degrees-of-freedom, to the noncooperative interference channel (i.e., unilateral causal cooperation is not useful), to the non-causal cognitive interference channel (i.e., causal cooperation attains the ultimate limit of cognitive radio technology), and to bilateral source cooperation are identified. These comparisons shed light into the parameter regimes and network topologies that in practice might provide an unbounded throughput gain compared to currently available (non cognitive) technologies.

Connected through hyperedge HE-1 (induced by source paper "multi user cognitive interference channels a survey and new capacity results"):
  with members:
    - "the two user causal cognitive interference channel novel outer bounds and constant gap result for the symmetric gaussian noise channel in weak interference"
    - "on the capacity region of the two user interference channel with a cognitive relay"
    - "real interference alignment exploiting the potential of single antenna systems"
    - "on the gaussian interference channel with half duplex causal cognition"
    - "multiuser cognitive radio networks an information theoretic perspective"
    - "approximate sum capacity of k user cognitive interference channels with cumulative message sharing"
    - "simultaneous nonunique decoding is rate optimal"
    - "three user cognitive interference channel capacity region with strong interference"

Connected through hyperedge HE-2 (induced by source paper "the two user causal cognitive interference channel novel outer bounds and constant gap result for the symmetric gaussian noise channel in weak interference"):
  with members:
    - "new outer bounds for the interference channel with unilateral source cooperation"
    - "capacity of all nine models of channel output feedback for the two user interference channel"
    - "an outer bound for the memoryless two user interference channel with general cooperation"
    - "on the capacity of interference channel with causal and noncausal generalized feedback at the cognitive transmitter"
    - "inner and outer bounds for the gaussian cognitive interference channel and new capacity results"
    - "dependence balance based outer bounds for gaussian networks with cooperation and feedback"
    - "interference channels with source cooperation"
    - "interference channels with destination cooperation"

Connected through hyperedge HE-3 (induced by source paper "multicoding schemes for interference channels"):
  with members:
    - "on the achievable rate regions for state dependent gaussian interference channel"
    - "a comparison of superposition coding schemes"
    - "simultaneous nonunique decoding is rate optimal"
    - "wireless network information flow a deterministic approach"
    - "the state dependent semideterministic broadcast channel"
    - "interference channels with source cooperation"
    - "interference channels with destination cooperation"
    - "interference mitigation through limited transmitter cooperation"

Connected through hyperedge HE-4 (induced by source paper "on the gaussian interference channel with half duplex causal cognition"):
  with members:
    - "interference channels with half duplex source cooperation"
    - "on the capacity of interference channel with causal and noncausal generalized feedback at the cognitive transmitter"
    - "inner and outer bounds for the gaussian cognitive interference channel and new capacity results"
    - "wireless network information flow a deterministic approach"
    - "dependence balance based outer bounds for gaussian networks with cooperation and feedback"
    - "interference channels with source cooperation"
    - "interference channels with destination cooperation"
    - "the two user gaussian interference channel a deterministic view"

Connected through hyperedge HE-5 (induced by source paper "new outer bounds for the interference channel with unilateral source cooperation"):
  with members:
    - "capacity of all nine models of channel output feedback for the two user interference channel"
    - "on the capacity of interference channel with causal and noncausal generalized feedback at the cognitive transmitter"
    - "interference channels with source cooperation"
    - "interference channels with destination cooperation"
    - "feedback capacity of the gaussian interference channel to within 2 bits"
    - "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)