human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "asynchronous convolutional coded physical layer network coding"):
  Abstract: This paper investigates the decoding process of asynchronous convolutional-coded physical-layer network coding (PNC) systems. Specifically, we put forth a layered decoding framework for convolutional-coded PNC consisting of three layers: symbol realignment layer, codeword realignment layer, and joint channel-decoding network coding (Jt-CNC) decoding layer. Our framework can deal with phase asynchrony and symbol arrival-time asynchrony between the signals simultaneously transmitted by multiple sources. A salient feature of this framework is that it can handle both fractional and integral symbol offsets; previously proposed PNC decoding algorithms (e.g., XOR-CD and reduced-state Viterbi algorithms) can only deal with fractional symbol offset. Moreover, the Jt-CNC algorithm, based on belief propagation (BP), is BER-optimal for synchronous PNC and near optimal for asynchronous PNC. Extending beyond convolutional codes, we further generalize the Jt-CNC decoding algorithm for all cyclic codes. Our simulation shows that Jt-CNC outperforms the previously proposed XOR-CD algorithm and reduced-state Viterbi algorithm by 2dB for synchronous PNC. For phase-asynchronous PNC, Jt-CNC is 4dB better than the other two algorithms. Importantly, for real wireless environment testing, we have also implemented our decoding algorithm in a PNC system built on the USRP software radio platform. Our experiment shows that the proposed Jt-CNC decoder works well in practice.

Includes members:
  Member "a hierarchical modulation for upgrading digital broadcast systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "digital domain power division multiplexed dual polarization coherent optical ofdm transmission")
  Member "physical layer network coding for two way relaying with qam":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wireless bidirectional relaying latin squares and graph vertex coloring")
  Member "asynchronous physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an analysis of two user uplink asynchronous non orthogonal multiple access systems")
  Member "joint ldpc and physical layer network coding for asynchronous bi directional relaying":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "asynchronous physical layer network coding symbol misalignment estimation and its effect on decoding")
  Member "optimal decoding algorithm for asynchronous physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "differential distributed space time coding with imperfect synchronization in frequency selective channels")
  Member "physical layer network coding tutorial survey and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "random access for massive machine type communications")
  Member "implementation of physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coherent detection for short packet physical layer network coding with fsk modulation")
  Member "channel coding and decoding in a relay system operated with physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deep learning based constellation optimization for physical network coding in two way relay networks")

Question: Please tell me which class the source paper 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)