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 "coherent detection for short packet physical layer network coding with fsk modulation"):
  Abstract: This paper investigates coherent detection for physical-layer network coding (PNC) with short packet transmissions in a two-way relay channel (TWRC). PNC turns superimposed EM waves into network-coded messages to improve throughput in a relay system. To achieve this, accurate channel information at the relay is a necessity. Much prior work applies preambles to estimate the channel. For long packets, the preamble overhead is low because of the large data payload. For short packets, that is not the case. To avoid excessive overhead, we consider a set-up in which short packets do not have preambles. A key challenge is how the relay can estimate the channel and detect the network-coded messages jointly based on the received signals from the two end users. We design a coherent detector that makes use of a belief propagation (BP) algorithm to do so. For concreteness, we focus on frequency-shift-keying (FSK) modulation. We show how the BP algorithm can be simplified and made practical with Gaussian-mixture passing. In addition, we demonstrate that prior knowledge on the channel distribution is not needed with our framework. Benchmarked against the detector with prior knowledge of the channel distribution, numerical results show that our detector can have nearly the same performance without such prior knowledge.

Includes members:
  Member "noncoherent detection for physical layer network coding":
    also connected through other hyperedges:
      (none)
  Member "practical power balanced non orthogonal multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a low complexity recursive approach toward code domain noma for massive communications")
  Member "ultra reliable short packet communications half duplex or full duplex relaying":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "effective capacity of noma with finite blocklength for low latency communications")
  Member "complex linear physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "implementation of uplink network coded modulation for two hop networks")
  Member "mobile lattice coded physical layer network coding with practical channel alignment":
    also connected through other hyperedges:
      (none)
  Member "on the subtleties of q pam linear physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "noncoherent detection for physical layer network coding")
  Member "reliable physical layer network coding supporting real applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mobile lattice coded physical layer network coding with practical channel alignment")
  Member "ultra reliable communication in 5g wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "ultra reliable communication via optimum power allocation for harq retransmission schemes")

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)