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: "uplink performance analysis of dense cellular networks with los and nlos transmissions"
  Abstract: In this paper, we analyse the coverage probability and the area spectral efficiency (ASE) for the uplink (UL) of dense small cell networks (SCNs) considering a practical path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions. Compared with the existing work, we adopt the following novel approaches in our study: (i) we assume a practical user association strategy (UAS) based on the smallest path loss, or equivalently the strongest received signal strength; (ii) we model the positions of both base stations (BSs) and the user equipments (UEs) as two independent Homogeneous Poisson point processes (HPPPs); and (iii) the correlation of BSs' and UEs' positions is considered, thus making our analytical results more accurate. The performance impact of LoS and NLoS transmissions on the ASE for the UL of dense SCNs is shown to be significant, both quantitatively and qualitatively, compared with existing work that does not differentiate LoS and NLoS transmissions. In particular, existing work predicted that a larger UL power compensation factor would always result in a better ASE in the practical range of BS density, i.e., 10^1-10^3 BSs/km^2. However, our results show that a smaller UL power compensation factor can greatly boost the ASE in the UL of dense SCNs, i.e., 10^2-10^3 BSs/km^2, while a larger UL power compensation factor is more suitable for sparse SCNs, i.e., 10^1-10^2 BSs/km^2.

Connected through hyperedge HE-1 (induced by source paper "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges"):
  with members:
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "supporting uav cellular communications through massive mimo"
    - "uav aided offloading for cellular hotspot"
    - "the essential guide to realizing 5g connected uavs with massive mimo"
    - "performance analysis for practical unmanned aerial vehicle networks with los nlos transmissions"
    - "promises and caveats of uplink iot ultra dense networks"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"

Connected through hyperedge HE-2 (induced by source paper "promises and caveats of uplink iot ultra dense networks"):
  with members:
    - "performance impact of base station antenna heights in dense cellular networks"
    - "on the fundamental characteristics of ultra dense small cell networks"
    - "microscopic analysis of the uplink interference in fdma small cell networks"
    - "performance impact of idle mode capability on dense small cell networks"
    - "performance impact of idle mode capability on dense small cell networks with los and nlos transmissions"
    - "performance impact of los and nlos transmissions in dense cellular networks"
    - "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments"
    - "downlink cellular network analysis with multi slope path loss models"

Connected through hyperedge HE-3 (induced by source paper "the major and minor factors in the performance analysis of ultra dense networks"):
  with members:
    - "study on the idle mode capability with los and nlos transmissions"
    - "microscopic analysis of the uplink interference in fdma small cell networks"
    - "nearest neighbour distance distribution in hard core point processes"
    - "throughput and coverage for a mixed full and half duplex small cell network"
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"
    - "what is the true value of dynamic tdd a mac layer perspective"
    - "please lower small cell antenna heights in 5g"
    - "performance impact of los and nlos transmissions in dense cellular networks"

Connected through hyperedge HE-4 (induced by source paper "directional antennas for interference management in full duplex cellular networks"):
  with members:
    - "a primer on cellular network analysis using stochastic geometry"
    - "throughput and coverage for a mixed full and half duplex small cell network"
    - "passive loop interference suppression in large scale full duplex cellular networks"
    - "full duplex radio for uplink downlink transmission with spatial randomness"
    - "full duplex mimo small cell networks performance analysis"
    - "throughput analysis for full duplex wireless networks with imperfect self interference cancellation"
    - "exploiting known interference as green signal power for downlink beamforming optimization"
    - "in band alpha duplex scheme for cellular networks a stochastic geometry approach"

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.IT(Information Theory)