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 multiple unicast in wireless networks a polymatroidal approach"):
  Abstract: A classical result in undirected wireline networks is the near optimality of routing (flow) for multiple-unicast traffic (multiple sources communicating independent messages to multiple destinations): the min cut upper bound is within a logarithmic factor of the number of sources of the max flow. In this paper we "extend" the wireline result to the wireless context. #R##N#Our main result is the approximate optimality of a simple layering principle: {\em local physical-layer schemes combined with global routing}. We use the {\em reciprocity} of the wireless channel critically in this result. Our formal result is in the context of channel models for which "good" local schemes, that achieve the cut-set bound, exist (such as Gaussian MAC and broadcast channels, broadcast erasure networks, fast fading Gaussian networks). #R##N#Layered architectures, common in the engineering-design of wireless networks, can have near-optimal performance if the {\em locality} over which physical-layer schemes should operate is carefully designed. Feedback is shown to play a critical role in enabling the separation between the physical and the network layers. The key technical idea is the modeling of a wireless network by an undirected "polymatroidal" network, for which we establish a max-flow min-cut approximation theorem.

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 "multiuser broadcast erasure channel with feedback capacity and algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "benefits of coding on age of information in broadcast networks")
  Member "degrees of freedom of interference channels with comp transmission and reception":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "degrees of freedom of cache aided wireless cellular networks")
  Member "multicommodity flows and cuts in polymatroidal networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "online energy harvesting problem over an arbitrary directed acyclic graph network")
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "computation alignment capacity approximation without noise accumulation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "expanding the compute and forward framework unequal powers signal levels and multiple linear combinations")
  Member "the degrees of freedom of the 2 hop 2 user interference channel with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "space time interference alignment and degrees of freedom regions for the miso broadcast channel with periodic csi feedback")
  Member "a digital interface for gaussian relay and interference networks lifting codes from the discrete superposition model":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the optimality of treating interference as noise general message sets")

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)