human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the pre log of gaussian broadcast with feedback can be two"
  Abstract: A generic intuition says that the pre-log, or multiplexing gain, cannot be larger than the minimum of the number of transmit and receive dimensions. This suggests that for the scalar broadcast channel, the pre-log cannot exceed one. By contrast, in this note, we show that when the noises are anti-correlated and feedback is present, then a pre-log of two can be attained. In other words, in this special case, in the limit of high SNR, the scalar Gaussian broadcast channel turns into two parallel AWGN channels. Achievability is established via a coding strategy due to Schalkwijk, Kailath, and Ozarow.

Connected through hyperedge HE-1 (induced by source paper "posterior matching for gaussian broadcast channels with feedback"):
  with members:
    - "on the capacity of symmetric gaussian interference channels with feedback"
    - "posterior matching scheme for gaussian multiple access channel with feedback"
    - "mimo mac bc duality with linear feedback coding schemes"
    - "lqg control approach to gaussian broadcast channels with feedback"
    - "optimal feedback communication via posterior matching"

Connected through hyperedge HE-2 (induced by source paper "a novel time varying coding scheme for the gaussian broadcast channel with feedback"):
  with members:
    - "lqg control approach to gaussian broadcast channels with feedback"
    - "optimal feedback communication via posterior matching"

Connected through hyperedge HE-3 (induced by source paper "lqg control approach to gaussian broadcast channels with feedback"):
  with members:
    - "an achievable rate region for the broadcast channel with feedback"
    - "control theoretic approach to communication with feedback fundamental limits and code design"
    - "on the capacity of the discrete memoryless broadcast channel with feedback"
    - "lecture notes on network information theory"
    - "linear sum capacity for gaussian multiple access channels with feedback"
    - "optimal feedback communication via posterior matching"
    - "feedback capacity of stationary gaussian channels"

Connected through hyperedge HE-4 (induced by source paper "feedback can double the prelog of some memoryless gaussian networks"):
  with members:
    - "lqg control approach to gaussian broadcast channels with feedback"
    - "interference channels with rate limited feedback"
    - "feedback capacity of the gaussian interference channel to within 2 bits"
    - "on the capacity of the discrete memoryless broadcast channel with feedback"
    - "on the gaussian mac with imperfect feedback"
    - "on cognitive interference networks"
    - "the multiplexing gain of mimo x channels with partial transmit side information"

Question: Please tell me which class the center node 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)