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 "optimal rate diverse wireless network coding"):
  Abstract: This paper proposes an encoding/decoding framework for achieving the optimal channel capacities of the two-user broadcast channel where each user (receiver) has the message targeted for the other user (receiver) as side information. Since the link qualities of the channels from the base station to the two users are different, their respective single-user non-broadcast channel capacities are also different. A goal is to simultaneously achieve/approach the single-user non-broadcast channel capacities of the two users with a single broadcast transmission by applying network coding. This is referred to as the \emph{rate-diverse wireless network coding} problem. For this problem, this paper presents a capacity-achieving framework based on linear- structured nested lattice codes. The significance of the proposed framework, besides its theoretical optimality, is that it suggests a general design principle for linear rate-diverse wireless network coding going beyond the use of lattice codes. We refer to this design principle as the \emph{principle of virtual single-user channels}. Guided by this design principle, we propose two implementations of our encoding/decoding framework using practical linear codes amenable to decoding with affordable complexities: the first implementation is based on Low Density Lattice Codes (LDLC) and the second implementation is based on Bit-interleaved Coded Modulation (BICM). These two implementations demonstrate the validity and performance advantage of our framework.

Includes members:
  Member "lattice codes achieve the capacity of common message gaussian broadcast channels with coded side information":
    also connected through other hyperedges:
      (none)
  Member "lattice index coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cache aided modulation for heterogeneous coded caching over a gaussian broadcast channel")
  Member "on index coding in noisy broadcast channels with receiver message side information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal coding schemes for the three receiver awgn broadcast channel with receiver message side information")
  Member "wireless network coding via modified 802 11 mac phy design and implementation on sdr":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "implementation of uplink network coded modulation for two hop networks")
  Member "compute and forward harnessing interference through structured codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "private information retrieval over gaussian mac")
  Member "broadcast capacity region of two phase bidirectional relaying":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the dof of two way 2 2 2 relay networks with or without relay caching")
  Member "low density lattice codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "neural fuzzy extractors a secure way to use artificial neural networks for biometric user authentication")

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)