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 "nested lattice codes for gaussian two way relay channels"):
  Abstract: In this paper, we consider a Gaussian two-way relay channel (GTRC), where two sources exchange messages with each other through a relay. We assume that there is no direct link between sources, and all nodes operate in full-duplex mode. By utilizing nested lattice codes for the uplink (i.e., MAC phase), and structured binning for the downlink (i.e., broadcast phase), we propose two achievable schemes. Scheme 1 is based on compute and forward scheme of [1] while scheme 2 utilizes two different lattices for source nodes based on a three-stage lattice partition chain. We show that scheme 2 can achieve capacity region at the high signal-to-noise ratio (SNR). Regardless all channel parameters, the achievable rate of scheme 2 is within 0.2654 bit from the cut-set outer bound for user 1. For user 2, the proposed scheme achieves within 0.167 bit from the outer bound if channel coefficient is larger than one, and achieves within 0.2658 bit from the outer bound if channel coefficient is smaller than one. Moreover, sum rate of the proposed scheme is within 0.334 bits from the sum capacity. These gaps for GTRC are the best gap-to-capacity results to date.

Includes members:
  Member "outer bounds for the capacity region of a gaussian two way relay channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the dof of two way 2 2 2 relay networks with or without relay caching")
  Member "nested lattice codes for gaussian relay networks with interference":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "generalized compute compress and forward")
  Member "on achievable rate regions of the asymmetric awgn two way relay channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "alternative awaiting and broadcast for two way relay fading channels")
  Member "lattice codes for the gaussian relay channel decode and forward and compress and forward":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding")
  Member "channel coding and decoding in a relay system operated with physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep learning based constellation optimization for physical network coding in two way relay networks")
  Member "compute and forward harnessing interference through structured codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "private information retrieval over gaussian mac")
  Member "approximate capacity of the two way relay channel a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "state space adaptive nonlinear self interference cancellation for full duplex communication")
  Member "joint source channel coding with side information using hybrid digital analog codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "minimum energy analysis for robust gaussian joint source channel coding with a square law profile")

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)