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 "complex linear physical layer network coding"):
  Abstract: This paper presents the results of a comprehensive investigation of complex linear physical-layer network (PNC) in two-way relay channels (TWRC). A critical question at relay R is as follows: "Given channel gain ratio $\eta = h_A/h_B$, where $h_A$ and $h_B$ are the complex channel gains from nodes A and B to relay R, respectively, what is the optimal coefficients $(\alpha,\beta)$ that minimizes the symbol error rate (SER) of $w_N=\alpha w_A+\beta w_B$ when we attempt to detect $w_N$ in the presence of noise?" Our contributions with respect to this question are as follows: (1) We put forth a general Gaussian-integer formulation for complex linear PNC in which $\alpha,\beta,w_A, w_B$, and $w_N$ are elements of a finite field of Gaussian integers, that is, the field of $\mathbb{Z}[i]/q$ where $q$ is a Gaussian prime. Previous vector formulation, in which $w_A$, $w_B$, and $w_N$ were represented by $2$-dimensional vectors and $\alpha$ and $\beta$ were represented by $2\times 2$ matrices, corresponds to a subcase of our Gaussian-integer formulation where $q$ is real prime only. Extension to Gaussian prime $q$, where $q$ can be complex, gives us a larger set of signal constellations to achieve different rates at different SNR. (2) We show how to divide the complex plane of $\eta$ into different Voronoi regions such that the $\eta$ within each Voronoi region share the same optimal PNC mapping $(\alpha_{opt},\beta_{opt})$. We uncover the structure of the Voronoi regions that allows us to compute a minimum-distance metric that characterizes the SER of $w_N$ under optimal PNC mapping $(\alpha_{opt},\beta_{opt})$. Overall, the contributions in (1) and (2) yield a toolset for a comprehensive understanding of complex linear PNC in $\mathbb{Z}[i]/q$. We believe investigation of linear PNC beyond $\mathbb{Z}[i]/q$ can follow the same approach.

Includes members:
  Member "on the subtleties of q pam linear physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coherent detection for short packet physical layer network coding with fsk modulation")
  Member "lattices over eisenstein integers for compute and forward":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "lattice coding for downlink multiuser transmission")
  Member "multilevel coding schemes for compute and forward with flexible decoding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "on the subtleties of q pam linear physical layer network coding")
  Member "an algebraic approach to physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lattice coding for downlink multiuser transmission")
  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 "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)