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 "strong interference alignment"):
  Abstract: Interference alignment (IA) adjusts signaling scheme such that all interfering signals are squeezed in interference subspace. IA mostly achieves its performance via infinite extension of the channel, which is a major challenge for IA in practical systems. In this paper, we make part of interference very strong and achieve perfect IA within limited number of channel extensions. A single-hop $3$ user single antenna interference channel (IFC) is considered and it is shown that only one of the interfering signal streams needs to be strong so that perfect IA is feasible.

Includes members:
  Member "channel aided interference alignment":
    also connected through other hyperedges:
      (none)
  Member "opportunistic interference alignment for mimo interfering multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi stream opportunistic network decoupling relay selection and interference management")
  Member "the approximate sum capacity of the symmetric gaussian k user interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "private information retrieval over gaussian mac")
  Member "ergodic fading interference channels sum capacity and separability":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "interference regime enforcing rate maximization for non orthogonal multiple access noma")
  Member "ergodic interference alignment":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the interference channel revisited aligning interference by adjusting receive antenna separation")
  Member "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "vector gaussian successive refinement with degraded side information")
  Member "capacity bounds for the gaussian interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "vector gaussian successive refinement with degraded side information")
  Member "capacity of symmetric k user gaussian very strong interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "approximate capacity of a class of partially connected interference channels")

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)