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 "energy efficiency of generalized spatial modulation aided massive mimo systems"):
  Abstract: One of focuses in green communication studies is the energy efficiency (EE) of massive multiple-input multiple-output (MIMO) systems. Although the massive MIMO technology can improve the spectral efficiency (SE) of cellular networks by configuring a large number of antennas at base stations (BSs), the energy consumption of radio frequency (RF) chains increases dramatically. The increment of energy consumption is caused by the increase of RF chain number to match the antenna number in massive MIMO communication systems. To overcome this problem, a generalized spatial modulation (GSM) solution is presented to simultaneously reduce the number of RF chains and maintain the SE of massive MIMO communication systems. A EE model is proposed to estimate the transmission and computation power of massive MIMO communication systems with GSM. Simulation results demonstrate that the EE of massive MIMO communication systems with GSM outperforms the massive MIMO communication systems without GSM. Besides, the computation power consumed by massive MIMO communication systems with GSM is effectively reduced.

Includes members:
  Member "machine learning inspired energy efficient hybrid precoding for mmwave massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hybrid precoding based millimeter wave massive mimo noma with simultaneous wireless information and power transfer")
  Member "energy efficiency challenges of 5g small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "neural networks in hybrid precoding for millimeter wave massive mimo systems")
  Member "spatial spectrum and energy efficiency of random cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "user mobility evaluation for 5g small cell networks based on individual mobility model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "5g ultra dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "5g wireless backhaul networks challenges and research advances":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "impact of transceiver power consumption on the energy efficiency of zero forcing detector in massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multiple antenna technologies for beyond 5g")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")

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.NI(Networking and Internet Architecture)