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: "the impact of noise correlation and channel phase information on the data rate of the single symbol ml decodable distributed stbcs"
  Abstract: Very recently, we proposed the row-monomial distributed orthogonal space-time block codes (DOSTBCs) and showed that the row-monomial DOSTBCs achieved approximately twice higher bandwidth efficiency than the repetitionbased cooperative strategy [1]. However, we imposed two limitations on the row-monomial DOSTBCs. The first one was that the associated matrices of the codes must be row-monomial. The other was the assumption that the relays did not have any channel state information (CSI) of the channels from the source to the relays, although this CSI could be readily obtained at the relays without any additional pilot signals or any feedback overhead. In this paper, we first remove the row-monomial limitation; but keep the CSI limitation. In this case, we derive an upper bound of the data-rate of the DOSTBC and it is larger than that of the row-monomial DOSTBCs in [1]. Secondly, we abandon the CSI limitation; but keep the row-monomial limitation. Specifically, we propose the row-monomial DOSTBCs with channel phase information (DOSTBCs-CPI) and derive an upper bound of the data-rate of those codes. The rowmonomial DOSTBCs-CPI have higher data-rate than the DOSTBCs and the row-monomial DOSTBCs. Furthermore, we find the actual row-monomial DOSTBCs-CPI which achieve the upper bound of the data-rate.

Connected through hyperedge HE-1 (induced by source paper "high rate distributed training embedded complex orthogonal designs for relay networks"):
  with members:
    - "training embedded single symbol ml decodable distributed stbcs for relay networks"

Connected through hyperedge HE-2 (induced by source paper "high rate single symbol decodable precoded dstbcs for cooperative networks"):
  with members:
    - "distributed space time codes for cooperative networks with partial csi"

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)