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 "physical layer network coding for two way relaying with qam"):
  Abstract: The design of modulation schemes for the physical layer network-coded two-way relay network has been studied in literature and it is known that every network coding map that satisfies the exclusive law is representable by a Latin Square. This relationship has been used to get network coding maps satisfying the exclusive law. But, only the scenario in which the end nodes use M-PSK signal sets has been addressed previously. In this paper, we address the case in which the end nodes use M-QAM signal sets. In a fading scenario, for certain channel conditions γejθ, termed singular fade states, the end-to-end performance is greatly reduced. By formulating a procedure for finding the exact number of singular fade states for QAM, we show that square QAM signal sets give lesser number of singular fade states compared to PSK signal sets. This reduces the computational complexity at the relay node. It is shown that the criterion for partitioning the complex plane, for the purpose of using a particular network code for a particular fade state, is different from that used for M-PSK. Using a modified criterion, we describe a procedure to analytically partition the complex plane representing the channel condition. We show that when M-QAM (M >4) signal set is used, the conventional XOR network mapping fails to remove the ill effects of γejθ=1, which is a singular fade state for all signal sets of arbitrary size. We show that a doubly block circulant Latin Square removes this singular fade state for M-QAM. Finally it is shown that M-QAM gives superior performance over M-PSK.

Includes members:
  Member "an adaptive modulation scheme for two user fading mac with quantized fade state feedback":
    also connected through other hyperedges:
      (none)
  Member "physical layer network coding for two way relaying with qam and latin squares":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed space time coding for wireless two way relaying")
  Member "performance analysis of adaptive physical layer network coding for wireless two way relaying":
    also connected through other hyperedges:
      (none)
  Member "wireless bidirectional relaying and latin squares":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed space time coding for wireless two way relaying")
  Member "channel quantization for physical layer network coded two way relaying":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed space time coding for wireless two way relaying")
  Member "multilevel coding schemes for compute and forward":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "space time coded spatial modulated physical layer network coding for two way relaying")
  Member "physical network coding in two way wireless relay channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "coherent detection for short packet physical layer network coding with fsk modulation")

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)