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: "heterogeneous networks with power domain noma coverage throughput and power allocation analysis"
  Abstract: In a heterogeneous cellular network (HetNet), consider that a base station in the HetNet is able to simultaneously schedule and serve $K$ users in the downlink by performing the power-domain non-orthogonal multiple access (NOMA) scheme. This paper aims at the preliminary study on the downlink coverage and throughput performances of the HetNet with the \textit{non-cooperative} and the (proposed) \textit{cooperative} NOMA schemes. First, the coverage probability and link throughput of $K$ users in each cell are studied and their accurate expressions are derived for the non-cooperative NOMA scheme in which no BSs are coordinated to jointly transmit the NOMA signals for a particular user. We show that the coverage and link throughput can be largely reduced if transmit power allocations among the $K$ users do not satisfy the constraint derived. Next, we analyze the coverage and link throughput of $K$ users for the cooperative NOMA scheme in which the void BSs without users are coordinated to enhance the farthest NOMA user in a cell. The derived accurate results show that cooperative NOMA can significantly improve the coverage and link throughput of all users. Finally, we show that there exist optimal power allocation schemes that maximize the average cell coverage and throughput under some derived power allocation constraints and numerical results validate our analytical findings.

Connected through hyperedge HE-1 (induced by source paper "a survey of rate optimal power domain noma schemes for enabling technologies of future wireless networks"):
  with members:
    - "generalized coordinated multipoint gcomp enabled noma outage capacity and power allocation"
    - "what role can noma play in massive mimo"
    - "uav data collection over noma backscatter networks uav altitude and trajectory optimization"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "when full duplex wireless meets non orthogonal multiple access opportunities and challenges"
    - "on optimizing vlc networks for downlink multi user transmission a survey"
    - "beam design and user scheduling for nonorthogonal multiple access with multiple antennas based on pareto optimality"
    - "spatial modulation assisted multi antenna non orthogonal multiple access"

Connected through hyperedge HE-2 (induced by source paper "ultra reliable and low latency communications using proactive multi cell association"):
  with members:
    - "wireless channel dynamics and robustness for ultra reliable low latency communications"
    - "resource allocation and harq optimization for urllc traffic in 5g wireless networks"
    - "reliable transmission of short packets through queues and noisy channels under latency and peak age violation guarantees"
    - "energy latency tradeoff in ultra reliable low latency communication with retransmissions"
    - "joint uplink and downlink resource configuration for ultra reliable and low latency communications"
    - "a statistical learning approach to ultra reliable low latency communication"
    - "cross layer optimization for ultra reliable and low latency radio access networks"
    - "fundamentals of the downlink green coverage and energy efficiency in heterogeneous networks"

Connected through hyperedge HE-3 (induced by source paper "fast uplink grant for noma a federated learning based approach"):
  with members:
    - "distributed layered grant free non orthogonal multiple access for massive mtc"
    - "a traffic model for machine type communications using spatial point processes"
    - "dynamic user clustering and power allocation for uplink and downlink non orthogonal multiple access noma systems"

Connected through hyperedge HE-4 (induced by source paper "meta distribution of the sir in large scale uplink and downlink noma networks"):
  with members:
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "non orthogonal multiple access in large scale heterogeneous 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"
    - "modeling and performance analysis of clustered device to device networks"
    - "the meta distribution of the sir in poisson bipolar and cellular networks"
    - "fairness for non orthogonal multiple access in 5g systems"

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)