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 "sub optimality of treating interference as noise in the cellular uplink with weak interference"):
  Abstract: Despite the simplicity of the scheme of treating interference as noise (TIN), it was shown to be sum-capacity optimal in the Gaussian interference channel (IC) with very-weak (noisy) interference. In this paper, the 2-user IC is altered by introducing an additional transmitter that wants to communicate with one of the receivers of the IC. The resulting network thus consists of a point-to-point channel interfering with a multiple access channel (MAC) and is denoted PIMAC. The sum-capacity of the PIMAC is studied with main focus on the optimality of TIN. It turns out that TIN in its naive variant, where all transmitters are active and both receivers use TIN for decoding, is not the best choice for the PIMAC. In fact, a scheme that combines both time division multiple access and TIN (TDMA-TIN) strictly outperforms the naive-TIN scheme. Furthermore, it is shown that in some regimes, TDMA-TIN achieves the sum-capacity for the deterministic PIMAC and the sum-capacity within a constant gap for the Gaussian PIMAC. Additionally, it is shown that, even for very-weak interference, there are some regimes where a combination of interference alignment with power control and treating interference as noise at the receiver side outperforms TDMA-TIN. As a consequence, on the one hand treating interference as noise in a cellular uplink is approximately optimal in certain regimes. On the other hand those regimes cannot be simply described by the strength of interference.

Includes members:
  Member "on the optimality of treating interference as noise general message sets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards an extremal network theory robust gdof gain of transmitter cooperation over tin")
  Member "extended generalized dof optimality regime of treating interference as noise in the x channel":
    also connected through other hyperedges:
      (none)
  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 "achievable and crystallized rate regions of the interference channel with interference as noise":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "treating interference as noise in cellular networks a stochastic geometry approach")
  Member "the deterministic sum capacity of a multiple access channel interfering with a point to point link":
    also connected through other hyperedges:
      (none)
  Member "interference alignment and neutralization in a cognitive 3 user mac interference channel degrees of freedom":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the efficiency of widely linear precoding and symbol extension in cellular uplink")
  Member "sub optimality of treating interference as noise in the cellular uplink":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a stochastic beamformed amplify and forward scheme in a multigroup multicast mimo relay network with per antenna power constraints")
  Member "rate region frontiers for n user interference channel with interference as noise":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "full duplex radio for uplink downlink wireless access with spatially random nodes")

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)