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 "on the subtleties of q pam linear physical layer network coding"):
  Abstract: This paper investigates various subtleties of applying linear physical-layer network coding (PNC) with    $q$   -level pulse amplitude modulation (   $q$   -PAM) in two-way relay channels. A critical issue is how the PNC system performs when the received powers from the two users at the relay are imbalanced. In particular, how would the PNC system perform under slight power imbalance that is inevitable in practice, even when power control is applied? To answer these questions, this paper presents a comprehensive analysis of    $q$   -PAM PNC. Our contributions are as follows. First, we give a systematic way to obtain the analytical relationship between the minimum distance of the signal constellation induced by the superimposed signals of the two users (a key performance determining factor) and the channel-gain ratio of the two users, for all    $q$   . In particular, we show how the minimum distance changes in a piecewise linear fashion as the channel-gain ratio varies. Second, we show that the performance of    $q$   -PAM PNC is highly sensitive to imbalanced received powers from the two users at the relay, even when the power imbalance is slight (e.g., the residual power imbalance in a power-controlled system). This sensitivity problem is exacerbated as    $q$    increases, calling into question the robustness of high-order modulated PNC. Third, we propose an asynchronized PNC system in which the symbol arrival times of the two users at the relay are deliberately made to be asynchronous. We show that such asynchronized PNC, when operated with a belief propagation decoder, can remove the sensitivity problem, allowing a robust high-order modulated PNC system to be built.

Includes members:
  Member "multilevel coding schemes for compute and forward with flexible decoding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compute compress and forward exploiting asymmetry of wireless relay networks")
  Member "symbol and bit mapping optimization for physical layer network coding with pulse amplitude modulation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "complex linear physical layer network coding")
  Member "an algebraic approach to physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lattice coding for downlink multiuser transmission")
  Member "asynchronous physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an analysis of two user uplink asynchronous non orthogonal multiple access systems")
  Member "multiple input multiple output two way relaying a space division approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "passive beamforming and information transfer design for reconfigurable intelligent surfaces aided multiuser mimo systems")
  Member "reliable physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards massive connectivity support for scalable mmtc communications in 5g networks")
  Member "physical layer network coding tutorial survey and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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-8 (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)