human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "combining adaptive coding and modulation with hierarchical modulation in satcom systems"
  Abstract: We investigate the design of a broadcast system in order to maximise the throughput. This task is usually challenging due to the channel variability. Forty years ago, Cover introduced and compared two schemes: time sharing and superposition coding. Even if the second scheme was proved to be optimal for some channels, modern satellite communications systems such as DVB-SH and DVB-S2 mainly rely on time sharing strategy to optimize the throughput. They consider hierarchical modulation, a practical implementation of superposition coding, but only for unequal error protection or backward compatibility purposes. We propose in this article to combine time sharing and hierarchical modulation together and show how this scheme can improve the performance in terms of available rate. We introduce the hierarchical 16-APSK to boost the performance of the DVB-S2 standard. We also evaluate various strategies to group the receivers in pairs when using hierarchical modulation. Finally, we show in a realistic use case based on DVB-S2 that the combined scheme can provide throughput gains greater than 10% compared to the best time sharing strategy.

Connected through hyperedge HE-1 (induced by source paper "64 apsk constellation and mapping optimization for satellite broadcasting using genetic algorithms"):
  with members:
    - "on the genetic optimization of apsk constellations for satellite broadcasting"
    - "random access in dvb rcs2 design and dynamic control for congestion avoidance"
    - "a hierarchical modulation for upgrading digital broadcast systems"
    - "constellation design for transmission over nonlinear satellite channels"
    - "providing local content in a hybrid single frequency network using hierarchical modulation"

Connected through hyperedge HE-2 (induced by source paper "on optimizing hierarchical modulation in awgn channel"):
  with members:
    - "a hierarchical modulation for upgrading digital broadcast systems"

Connected through hyperedge HE-3 (induced by source paper "optimal dvb s2 spectral efficiency with hierarchical modulation"):
  with members:
    - "quasi optimal grouping for broadcast systems with hierarchical modulation"

Connected through hyperedge HE-4 (induced by source paper "quasi optimal grouping for broadcast systems with hierarchical modulation"):
  with members:
    - "dvb s2 spectrum efficiency improvement with hierarchical modulation"

Connected through hyperedge HE-5 (induced by source paper "dvb s2 spectrum efficiency improvement with hierarchical modulation"):
  with members:
    - "a hierarchical modulation for upgrading digital broadcast systems"
    - "generic approach for hierarchical modulation performance analysis application to dvb sh"
    - "providing local content in a hybrid single frequency network using hierarchical modulation"

Question: Please tell me which class the center node 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.NI(Networking and Internet Architecture)