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 "multi layer interference alignment and gdof of the k user asymmetric interference channel"):
  Abstract: In wireless networks, link strengths are often affected by some topological factors such as propagation path loss, shadowing and inter-cell interference. Thus, different users in the network might experience different link strengths. In this work we consider a K-user asymmetric interference channel, where the channel gains of the links connected to Receiver k are scaled with P^{\alpha_k /2}}, k=1,2,...,K, for 0< \alpha_1 \leq \alpha_2 \leq \cdots \leq \alpha_K \leq 1. For this setting, we show that the optimal sum generalized degrees-of-freedom (GDoF) is characterized as dsum = (\sum_{k=1}^K \alpha_k + \alpha_K -\alpha_{K-1})/2, which matches the existing result dsum= K/2 when \alpha_1 = \alpha_2 = ... = \alpha_K =1. The achievability is based on multi-layer interference alignment, where different interference alignment sub-schemes are designed in different layers associated with specific power levels, and successive decoding is applied at the receivers. While the converse for the symmetric case only requires bounding the sum degrees-of-freedom (DoF) for selected two users, the converse for this asymmetric case involves bounding the weighted sum GDoF for selected J+2 users, with corresponding weights (2^{J}, 2^{J-1}, ... , 2^{2}, 2^{1}), a geometric sequence with common ratio 2, for the first J users and with corresponding weights (1, 1) for the last two users, for J \in {1,2, ... , \lceil\log (K/2)\rceil }.

Includes members:
  Member "gdof of interference channel with limited cooperation under finite precision csit":
    also connected through other hyperedges:
      (none)
  Member "secure communication over interference channel to jam or not to jam":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adding common randomness can remove the secrecy constraints in communication networks")
  Member "optimal secure gdof of symmetric gaussian wiretap channel with a helper":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adding common randomness can remove the secrecy constraints in communication networks")
  Member "k user symmetric m times n mimo interference channel under finite precision csit a gdof perspective":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards an extremal network theory robust gdof gain of transmitter cooperation over tin")
  Member "the generalized degrees of freedom region of the mimo z interference channel with delayed csit":
    also connected through other hyperedges:
      (none)
  Member "optimality of treating interference as noise a combinatorial perspective":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimality of treating inter cell interference as noise under finite precision csit")
  Member "real interference alignment exploiting the potential of single antenna systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi antenna coded content delivery with caching a low complexity solution")
  Member "on the vector broadcast channel with alternating csit a topological perspective":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "achieving full dof in heterogeneous parallel broadcast channels with outdated csit")

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)