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 "area spectral efficiency and sinr scaling laws in multi antenna cellular networks"):
  Abstract: We study the scaling laws of the signal-to-interference-plus-noise ratio (SINR) and area spectral efficiency (ASE) in multi-antenna cellular networks, where the number of antennas scales with the base station (BS) spatial density $\lambda$. We start with the MISO case having $N_t(\lambda)$ transmit antennas and a single receive antenna and prove that the average SINR scales as $\frac{N_t(\lambda)}{\lambda}$ and the average ASE scales as $\lambda\log\left(1+\frac{N_t(\lambda)}{\lambda}\right)$. For the MIMO case with single-stream eigenbeamforming and $N_r(\lambda) \leq N_t(\lambda)$ receive antennas, we prove that the scaling laws of the conditional SINR and ASE are exactly the same as the MISO case, i.e. not dependent on $N_r(\lambda)$. We also show that coordinated beamforming amongst $K\leq N_t(\lambda)$ neighboring BSs does not improve the scaling laws regardless of $K$. From a system design perspective, our results suggest that deploying multi-antenna BSs can help maintain the per-user throughput and the linear increase in the ASE with BS density, while the number of antennas at the user equipment and the use of BS cooperation do not matter much.

Includes members:
  Member "scaling laws of dense multi antenna cellular networks":
    also connected through other hyperedges:
      (none)
  Member "sinr and throughput of dense cellular networks with stretched exponential path loss":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scaling laws of dense multi antenna cellular networks")
  Member "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scaling laws of dense multi antenna cellular networks")
  Member "performance limits of network densification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "scaling laws of dense multi antenna cellular networks")
  Member "modeling and analysis of cellular networks using stochastic geometry a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exploiting randomly located blockages for large scale deployment of intelligent surfaces")
  Member "performance impact of base station antenna heights in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "scaling laws of dense multi antenna cellular networks")
  Member "a primer on cellular network analysis using stochastic geometry":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dynamic tdd interference analysis in macro cell and small cell deployments")
  Member "scaling laws for ergodic spectral efficiency in mimo poisson networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "ergodic spectral efficiency in mimo 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)