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 "simultaneous nonunique decoding is rate optimal"):
  Abstract: It is shown that simultaneous nonunique decoding is rate-optimal for the general K-sender, L-receiver discrete memoryless interference channel when encoding is restricted to randomly generated codebooks, superposition coding, and time sharing. This result implies that the Han-Kobayashi inner bound for the two-user-pair interference channel cannot be improved simply by using a better decoder such as the maximum likelihood decoder. It also generalizes and extends previous results by Baccelli, El Gamal, and Tse on Gaussian interference channels with point-to-point Gaussian random codebooks and shows that the Cover-van der Meulen inner bound with no common auxiliary random variable on the capacity region of the broadcast channel can be improved to include the superposition coding inner bound simply by using simultaneous nonunique decoding. The key to proving the main result is to show that after a maximal set of messages has been recovered, the remaining signal at each receiver is distributed essentially independently and identically.

Includes members:
  Member "interference networks with point to point codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "increasing the throughput of an unlicensed wireless network through retransmissions")
  Member "interference decoding for deterministic channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "performance of multi cell massive mimo systems with interference decoding")

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)