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 "miso in ultra dense networks balancing the tradeoff between user and system performance"):
  Abstract: With over-deployed network infrastructures, network densification is shown to hinder the improvement of user experience and system performance. In this paper, we adopt multi-antenna techniques to overcome the bottleneck and investigate the performance of single-user beamforming, an effective method to enhance desired signal power, in small cell networks from the perspective of user coverage probability (CP) and network spatial throughput (ST). Pessimistically, it is proved that, even when multi-antenna techniques are applied, both CP and ST would be degraded and even asymptotically diminish to zero with the increasing base station (BS) density. Moreover, the results also reveal that the increase of ST is at the expense of the degradation of CP. Therefore, to balance the tradeoff between user and system performance, we further study the critical density, under which ST could be maximized under the CP constraint. Accordingly, the impact of key system parameters on critical density is quantified via the derived closed-form expression. Especially, the critical density is shown to be inversely proportional to the square of antenna height difference between BSs and users. Meanwhile, single-user beamforming, albeit incapable of improving CP and ST scaling laws, is shown to significantly increase the critical density, compared to the single-antenna regime.

Includes members:
  Member "the major and minor factors in the performance analysis of ultra dense networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stochastic geometry analysis of ultra dense networks impact of antenna height and performance limits")
  Member "effect of densification on cellular network performance with bounded pathloss model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hetnets coverage modeling and analysis over fox s mathcal h fading channels")
  Member "performance impact of base station antenna heights in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "fronthauling for 5g lte u ultra dense cloud small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint fronthaul multicast and cooperative beamforming for cache enabled cloud based small cell networks an mds codes aided approach")
  Member "performance impact of los and nlos transmissions in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mobility in the sky performance and mobility analysis for cellular connected uavs")
  Member "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "sinr and throughput scaling in ultradense urban cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sum rate maximization of multicell miso networks with limited information exchange")
  Member "downlink cellular network analysis with multi slope path loss models":
    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)