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 equal rate capacity of the awgn multiway relay channel"):
  Abstract: The   $L$  -user additive white Gaussian noise multiway relay channel is investigated, where   $L$   users exchange information at the same rate through a single relay. A new achievable rate region, based on the functional-decode-forward coding strategy, is derived. For the case where there are three or more users, and all nodes transmit at the same power, the capacity is obtained. For the case where the relay power scales with the number of users, it is shown that both compress-forward and functional-decode-forward achieve rates within a constant number of bits of the capacity at all SNR levels; in addition, functional-decode-forward outperforms compress-forward and complete-decode-forward at high SNR levels.

Includes members:
  Member "the capacity region of multiway relay channels over finite fields with full data exchange":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the single uniprior index coding problem the single sender case and the multi sender extension")
  Member "an optimal coding strategy for the binary multi way relay channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "maximizing data rate for multiway relay channels with pairwise transmission strategy")
  Member "the multi way relay channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi agent reinforcement learning for energy harvesting two hop communications with full cooperation")
  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 "the case for structured random codes in network capacity theorems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lattice codes achieve the capacity of common message gaussian broadcast channels with coded side information")
  Member "physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "implementation of uplink network coded modulation for two hop 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)