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 "impact of underlaid multi antenna d2d on cellular downlink in massive mimo systems"):
  Abstract: In this paper, we consider a massive multiple-input multiple-output (MIMO) downlink system underlaid with a network of multi-antenna D2D user equipments (UEs). Each D2D transmitter (Tx) uses all its antennas to beamform information towards its desired D2D receiver, which uses only a single antenna for reception. While beamforming at the D2D Tx reduces D2D interference to the neighbouring cellular UEs (CUEs), the cellular-to-D2D interference is also negligible due to highly directional beamforming at the massive MIMO base station. For the above proposed system, we analyze the average per-user spectral efficiency (SE) of CUEs ($R^{c,d}$) as a function of the D2D area spectral efficiency (ASE). Our analysis reveals that for a fixed D2D ASE ($R_0^{(d)}$) and fixed number of D2D antennas ($N$), with increasing density of D2D Txs ($\lambda$), $R^{c,d}$ increases (for sufficiently large $\lambda$) and approaches a fundamental limit $R_{\infty}^{c,d}$ as $\lambda \to \infty$. Also, $R_{\infty}^{c,d}$ depends on $R_{0}^{(d)}$ and $N$, only through the ratio $\frac{R_{0}^{(d)}}{N-1}$, i.e, for a given fundamental limit $R_{\infty}^{c,d}$, the D2D ASE can be approximately doubled with every doubling in $N$.

Includes members:
  Member "energy efficiency and sum rate when massive mimo meets device to device communication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint power and resource allocation of d2d communication with low resolution adc")
  Member "the interplay between massive mimo and underlaid d2d networking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint optimization of signal design and resource allocation in wireless d2d edge computing")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "power control for d2d underlaid cellular networks modeling algorithms and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")
  Member "modeling heterogeneous network interference using poisson point processes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards reliable uav swarm communication in d2d enhanced cellular network")
  Member "energy and spectral efficiency of very large multiuser mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "a tractable approach to coverage and rate in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")

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)