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 "oblivious processing in a fronthaul constrained gaussian channel"):
  Abstract: We consider systems for which the transmitter conveys messages to the receiver through a capacity-limited relay station. The channel between the transmitter and the relay-station is assumed to be frequency selective additive Gaussian. It is assumed that the transmitter can shape the spectrum and adapt the coding technique as to optimize performance.The relay operation is oblivious, that is, the specific codebooks used are unknown, while the spectral shape of the transmitted signal is available. We find the reliable information rate that can be achieved in this setting, and to that end employ Gaussian bottleneck results combined with Shannon's incremental frequency approach

Includes members:
  Member "sampling stationary signals subject to bitrate constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tradeoffs between convergence speed and reconstruction accuracy in inverse problems")
  Member "distortion rate function of sub nyquist sampled gaussian sources":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analog to digital compression a new paradigm for converting signals to bits")
  Member "distributed mimo receiver achievable rates and upper bounds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access 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)