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 bcjr algorithm for asynchronous physical layer network coding"
  Abstract: In practical asynchronous bi-directional relaying, symbols transmitted by two source nodes cannot arrive at the relay with perfect symbol alignment and the symbol-asynchronous multiple-access channel (MAC) should be seriously considered. Recently, Lu et al. proposed a Tanner-graph representation of symbol-asynchronous MAC with rectangular-pulse shaping and further developed the message-passing algorithm for optimal decoding of the asynchronous physical-layer network coding. In this paper, we present a general channel model for the asynchronous multiple-access channel with arbitrary pulse-shaping. Then, the Bahl, Cocke, Jelinek, and Raviv (BCJR) algorithm is developed for optimal decoding of asynchronous MAC channel. This formulation can be well employed to develop various low-complexity algorithms, such as Log-MAP algorithm, Max-Log-MAP algorithm, which are favorable in practice.

Connected through hyperedge HE-1 (induced by source paper "asynchronous physical layer network coding"):
  with members:
    - "optimal decoding algorithm for asynchronous physical layer network coding"
    - "physical layer network coding tutorial survey and beyond"
    - "implementation of physical layer network coding"
    - "channel coded collision resolution by exploiting symbol misalignment"
    - "a message passing approach for joint channel estimation interference mitigation and decoding"
    - "channel coding and decoding in a relay system operated with physical layer network coding"
    - "collision resolution by exploiting symbol misalignment"
    - "physical network coding in two way wireless relay channels"

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)