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: "a comparison study of coupled and decoupled uplink heterogeneous cellular networks"
  Abstract: The evolution of mobile cellular networks has brought great changes of network architecture. For example, heterogeneous cellular network (HetNet) and Ultra dense network (UDN) have been proposed as promising techniques for 5G systems. Dense deployment of base stations (BSs) allows a mobile user to be able to access multiple BSs. Meanwhile the unbalance between UL and DL in HetNets, such as different received SINR threshold and traffic load, etc., becomes increasingly obvious. All these factors naturally inspire us to consider decoupling of uplink and downlink in radio access network. An interesting question is that whether the decoupled uplink (UL) /downlink (DL) access (DUDA) mode outperforms traditional coupled uplink (UL)/downlink (DL) access (CUDA) mode or not, and how big is the performance difference in terms of system rate, spectrum efficiency (SE) and energy efficiency (EE), etc. in HetNets. In this paper, we aim at thoroughly comparing the performance of the two modes based on stochastic geometry theory. In our analytical model, we take into account dynamic transmit power control in UL communication. Specifically, we employ fractional power control (FPC) to model a location-dependent channel state. Numerical results reveals that DUDA mode significantly outperforms CUDA mode in system rate, SE and EE in HetNets. In addition, DUDA mode improves load balance and potential fairness for both different type BSs and associated UEs.

Connected through hyperedge HE-1 (induced by source paper "downlink and uplink decoupling in two tier heterogeneous networks with multi antenna base stations"):
  with members:
    - "why to decouple the uplink and downlink in cellular networks and how to do it"
    - "analysis of the decoupled access for downlink and uplink in wireless heterogeneous networks"
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"
    - "joint rate and sinr coverage analysis for decoupled uplink downlink biased cell associations in hetnets"
    - "analysis and optimization of inter tier interference coordination in downlink multi antenna hetnets with offloading"
    - "capacity analysis of decoupled downlink and uplink access in 5g heterogeneous systems"
    - "downlink and uplink decoupling a disruptive architectural design for 5g networks"
    - "throughput and energy efficiency analysis of small cell networks with multi antenna base stations"

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.NI(Networking and Internet Architecture)