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: "capacity limits of full duplex cellular network"
  Abstract: This paper explores the capacity limits of a wireless cellular network with full-duplex (FD) base station (BS) and half-duplex user terminals, in which three independent messages are communicated, i.e., uplink message $m_1$ from the uplink user to the BS, downlink message $m_2$ from the BS to the downlink user, and D2D message $m_3$ from the uplink user to the downlink user. Information theoretically, this wireless system can be interpreted as a generalization of the FD relay broadcast channel with side message transmitted from relay to destination. Our study starts with a simpler case that has only the uplink and the downlink transmissions of $(m_1,m_2)$. For the discrete memoryless channel model, we propose a novel strategy that uses the BS as a FD relay to facilitate interference cancellation. The paper further provides a new converse which is strictly tighter than the cut-set bound. Taken together and specialized to the Gaussian case, our inner and outer bounds yield a characterization of the capacity to within a constant gap for the scalar and the vector Gaussian channel models. Furthermore, the paper studies a general setup with $(m_1,m_2,m_3)$. For the discrete memoryless channel model, we incorporate Marton's broadcast coding to obtain an achievable rate region, which is larger than the existing ones. Regarding the converse, we derive a nontrivial outer bound by means of genie. For the scalar Gaussian channel model, it is shown that by using one of the two rate-splitting schemes depending on the channel condition, we can already achieve the capacity to within a constant gap. For the vector Gaussian channel model, we further show how dirty paper coding can be applied to coordinate the transmissions of $(m_1,m_2,m_3)$ in three different ways. Finally, simulations demonstrate the advantages of using the BS as a relay in the FD cellular network.

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)