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 "capacity of coded index modulation"):
  Abstract: We consider the special case of index coding over the Gaussian broadcast channel where each receiver has prior knowledge of a subset of messages at the transmitter and demands all the messages from the source. We propose a concatenated coding scheme for this problem, using an index code for the Gaussian channel as an inner code/modulation to exploit side information at the receivers, and an outer code to attain coding gain against the channel noise. We derive the capacity region of this scheme by viewing the resulting channel as a multiple-access channel with many receivers, and relate it to the 'side information gain' -- which is a measure of the advantage of a code in utilizing receiver side information -- of the inner index code/modulation. We demonstrate the utility of the proposed architecture by simulating the performance of an index code/modulation concatenated with an off-the-shelf convolutional code through bit-interleaved coded-modulation.

Includes members:
  Member "lattice index coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cache aided modulation for heterogeneous coded caching over a gaussian broadcast channel")
  Member "joint network and gelfand pinsker coding for 3 receiver gaussian broadcast channels with receiver message side information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "layered space time index coding")
  Member "the capacity of three receiver awgn broadcast channels with receiver message side information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lattice codes achieve the capacity of common message gaussian broadcast channels with coded side information")
  Member "on the index coding problem and its relation to network coding and matroid theory":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "efficient 3d road map data exchange for intelligent vehicles in vehicular fog networks")
  Member "broadcasting with side information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "privacy utility tradeoff in a guessing framework inspired by index coding")

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)