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 "on the optimality of treating interference as noise for k user parallel gaussian interference networks"):
  Abstract: It has been shown recently by Geng et al. that in a $K$ user Gaussian interference network, if for each user the desired signal strength is no less than the sum of the strengths of the strongest interference from this user and the strongest interference to this user (all signal strengths measured in dB scale), then power control and treating interference as noise (TIN) is sufficient to achieve the entire generalized degrees of freedom (GDoF) region. Motivated by the intuition that the deterministic model of Avestimehr et al. (ADT deterministic model) is particularly suited for exploring the optimality of TIN, the results of Geng et al. are first re-visited under the ADT deterministic model, and are shown to directly translate between the Gaussian and deterministic settings. Next, we focus on the extension of these results to parallel interference networks, from a sum-capacity/sum-GDoF perspective. To this end, we interpret the explicit characterization of the sum-capacity/sum-GDoF of a TIN optimal network (without parallel channels) as a minimum weighted matching problem in combinatorial optimization, and obtain a simple characterization in terms of a partition of the interference network into vertex-disjoint cycles. Aided by insights from the cyclic partition, the sum-capacity optimality of TIN for $K$ user parallel interference networks is characterized for the ADT deterministic model, leading ultimately to corresponding GDoF results for the Gaussian setting. In both cases, subject to a mild invertibility condition the optimality of TIN is shown to extend to parallel networks in a separable fashion.

Includes members:
  Member "real interference alignment exploiting the potential of single antenna systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi antenna coded content delivery with caching a low complexity solution")
  Member "on the optimality of treating interference as noise":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimality of simple layered superposition coding in the 3 user miso bc with finite precision csit")
  Member "the ergodic capacity of phase fading interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on cooperation and interference in the weak interference regime full version with detailed proofs")
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "ergodic fading interference channels sum capacity and separability":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "interference regime enforcing rate maximization for non orthogonal multiple access noma")
  Member "interference alignment from degrees of freedom to constant gap capacity approximations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding")
  Member "the approximate capacity of the many to one and one to many gaussian interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "sum capacity and the unique separability of the parallel gaussian mac z bc network":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the synergistic benefits of alternating csit for the miso bc")

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)