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: "downlink non orthogonal multiple access noma in poisson networks"
  Abstract: A network model is considered where Poisson distributed base stations transmit to $N$ power-domain non-orthogonal multiple access (NOMA) users (UEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA UEs and consider two different ordering techniques for the NOMA UEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical UE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate $\mathcal{R}_{\rm tot}$, for general $N$, constrained to: 1) a minimum rate $\mathcal{T}$ for each UE, 2) identical rates for all UEs. We show the existence of: 1) an optimum $N$ that maximizes the constrained $\mathcal{R}_{\rm tot}$ given a set of network parameters, 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters $N$, the constraints, and the ordering technique to balance the $\mathcal{R}_{\rm tot}$ and fairness requirements. We also show that interference-aware UE clustering can significantly improve performance.

Connected through hyperedge HE-1 (induced by source paper "exploiting noma for uav communications in large scale cellular networks"):
  with members:
    - "exploiting noma for multi beam uav communication in cellular uplink"
    - "user association and resource allocation in unified non orthogonal multiple access enabled heterogeneous ultra dense networks"
    - "connectivity and blockage effects in millimeter wave air to everything networks"
    - "uav aided offloading for cellular hotspot"
    - "modeling and analysis of two way relay non orthogonal multiple access systems"
    - "energy minimization for wireless communication with rotary wing uav"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "multiple antenna aided noma in uav networks a stochastic geometry approach"

Connected through hyperedge HE-2 (induced by source paper "downlink analysis of noma enabled cellular networks with 3gpp inspired user ranking"):
  with members:
    - "downlink analysis for the typical cell in poisson cellular networks"
    - "noma in the uplink delay analysis with imperfect csi and finite length coding"
    - "meta distribution of downlink non orthogonal multiple access noma in poisson networks"
    - "stochastic geometry based uplink analysis of massive mimo systems with fractional pilot reuse"
    - "accuracy of distance based ranking of users in the analysis of noma systems"
    - "non orthogonal multiple access in large scale heterogeneous networks"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"

Connected through hyperedge HE-3 (induced by source paper "on clustering and channel disparity in non orthogonal multiple access noma"):
  with members:
    - "meta distribution of downlink non orthogonal multiple access noma in poisson networks"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "fairness for non orthogonal multiple access in 5g systems"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"

Connected through hyperedge HE-4 (induced by source paper "accuracy of distance based ranking of users in the analysis of noma systems"):
  with members:
    - "system level modeling and optimization of the energy efficiency in cellular networks a stochastic geometry framework"
    - "cooperative harq assisted noma scheme in large scale d2d networks"
    - "the meta distribution of the sir for cellular networks with power control"
    - "user point processes in cellular networks"
    - "energy efficiency of distributed signal processing in wireless networks a cross layer analysis"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "downlink capacity and base station density in cellular networks"

Connected through hyperedge HE-5 (induced by source paper "meta distribution of downlink non orthogonal multiple access noma in poisson networks"):
  with members:
    - "asymptotics and approximation of the sir distribution in general cellular networks"
    - "the meta distribution of the sir in poisson bipolar and cellular networks"

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)