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 energy distortion tradeoff of gaussian broadcast channels with feedback"):
  Abstract: This work studies the relationship between the energy allocated for transmitting a pair of correlated Gaussian sources over a two-user Gaussian broadcast channel with noiseless channel output feedback (GBCF) and the resulting distortion at the receivers. Our goal is to characterize the minimum transmission energy required for broadcasting a pair of source samples, such that each source can be reconstructed at its respective receiver to within a target distortion, when the source-channel bandwidth ratio is not restricted. This minimum transmission energy is defined as the energy-distortion tradeoff (EDT). We derive a lower bound and three upper bounds on the optimal EDT. For the upper bounds, we analyze the EDT of three transmission schemes: two schemes are based on separate source-channel coding and apply encoding over multiple samples of source pairs, and the third scheme is a joint source-channel coding scheme that applies uncoded linear transmission on a single source-sample pair and is obtained by extending the Ozarow–Leung (OL) scheme. Numerical simulations show that the EDT of the OL-based scheme is close to that of the better of the two separation-based schemes, which makes the OL scheme attractive for energy-efficient, low-latency and low-complexity source transmission over GBCFs.

Includes members:
  Member "on the ozarow leung scheme for the gaussian broadcast channel with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mimo mac bc duality with linear feedback coding schemes")
  Member "interactive schemes for the awgn channel with noisy feedback":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "feedback channel communication with low precision arithmetic")
  Member "insufficiency of linear feedback schemes in gaussian broadcast channels with common message":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the ozarow leung scheme for the gaussian broadcast channel with feedback")
  Member "mimo mac bc duality with linear feedback coding schemes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "concatenated coding using linear schemes for gaussian broadcast channels with noisy channel output feedback")
  Member "source channel coding theorems for the multiple access relay channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the secrecy capacity of gaussian mimo channels with finite memory full version")
  Member "lqg control approach to gaussian broadcast channels with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "youla coding and computation of gaussian feedback capacity")
  Member "optimality and approximate optimality of source channel separation in networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a new approach to lossy network compression of a tuple of correlated multivariate gaussian rvs")
  Member "variations on a theme by schalkwijk and kailath":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "feedback channel communication with low precision arithmetic")

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)