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: "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments"
  Abstract: Today's heterogeneous networks comprised of mostly macrocells and indoor small cells will not be able to meet the upcoming traffic demands. Indeed, it is forecasted that at least a    $100\times$   network capacity increase will be required to meet the traffic demands in 2020. As a result, vendors and operators are now looking at using every tool at hand to improve network capacity. In this epic campaign, three paradigms are noteworthy, i.e., network densification, the use of higher frequency bands and spectral efficiency enhancement techniques. This paper aims at bringing further common understanding and analysing the potential gains and limitations of these three paradigms, together with the impact of idle mode capabilities at the small cells as well as the user equipment density and distribution in outdoor scenarios. Special attention is paid to network densification and its implications when transiting to ultra-dense small cell deployments. Simulation results show that comparing to the baseline case with an average inter site distance of 200 m and a 100 MHz bandwidth, network densification with an average inter site distance of 35 m can increase the average UE throughput by    $7.56\times$  , while the use of the 10 GHz band with a 500 MHz bandwidth can further increase the network capacity up to    $5\times$  , resulting in an average of 1.27 Gbps per UE. The use of beamforming with up to 4 antennas per small cell BS lacks behind with average throughput gains around 30% and cell-edge throughput gains of up to    $2\times$  . Considering an extreme densification, an average inter site distance of 5 m can increase the average and cell-edge UE throughput by    $18\times$   and    $48\times$  , respectively. Our study also shows how network densification reduces multi-user diversity, and thus proportional fair alike schedulers start losing their advantages with respect to round robin ones. The energy efficiency of these ultra-dense small cell deployments is also analysed, indicating the benefits of energy harvesting approaches to make these deployments more energy-efficient. Finally, the top ten challenges to be addressed to bring ultra-dense small cell deployments to reality are also discussed.

Connected through hyperedge HE-1 (induced by source paper "game theory for multi access edge computing survey use cases and future trends"):
  with members:
    - "non cooperative game theory based rate adaptation for dynamic video streaming over http"
    - "fog computing a taxonomy survey and future directions"
    - "optimal pricing for a peer to peer sharing platform under network externalities"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "a survey on mobile edge computing the communication perspective"
    - "sustainable incentives for mobile crowdsensing"
    - "multi agent reinforcement learning in sequential social dilemmas"
    - "mobile edge computing a survey on architecture and computation offloading"

Connected through hyperedge HE-2 (induced by source paper "blockchain for 5g and beyond networks a state of the art survey"):
  with members:
    - "ekiden a platform for confidentiality preserving trustworthy and performant smart contracts"
    - "a key 6g challenge and opportunity connecting the remaining 4 billions a survey on rural connectivity"
    - "on safeguarding privacy and security in the framework of federated learning"
    - "a survey on consensus mechanisms and mining strategy management in blockchain networks"
    - "trustsas a trustworthy spectrum access system for the 3 5 ghz cbrs band"
    - "blockchain enabled authentication handover with efficient privacy protection in sdn based 5g networks"
    - "6g wireless communication systems applications requirements technologies challenges and research directions"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"

Connected through hyperedge HE-3 (induced by source paper "capacity and outage analysis of a dual hop decode and forward relay aided noma scheme"):
  with members:
    - "modeling and analysis of two way relay non orthogonal multiple access systems"
    - "non orthogonal multiple access for cooperative communications challenges opportunities and trends"
    - "performance analysis of a hybrid downlink uplink cooperative noma scheme"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "on the performance of noma based cooperative relaying systems over rician fading channels"
    - "outage performance for cooperative noma transmission with an af relay"
    - "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 "integrated access and backhaul in 5g mmwave networks potentials and challenges"):
  with members:
    - "a tutorial on beam management for 3gpp nr at mmwave frequencies"
    - "end to end simulation of 5g mmwave networks"
    - "end to end simulation of integrated access and backhaul at mmwaves"
    - "distributed path selection strategies for integrated access and backhaul at mmwaves"
    - "network function virtualization state of the art and research challenges"
    - "wireless backhaul networks capacity bound scalability analysis and design guidelines"
    - "millimeter wave cellular wireless networks potentials and challenges"

Connected through hyperedge HE-5 (induced by source paper "intelligent scheduling and power control for multimedia transmission in 5g comp systems a dynamic bargaining game"):
  with members:
    - "power and channel allocation for non orthogonal multiple access in 5g systems tractability and computation"
    - "fundamental limits of cooperation"

Connected through hyperedge HE-6 (induced by source paper "energy sustainable paradigms and methods for future mobile networks a survey"):
  with members:
    - "information exchange in randomly deployed dense wsns with wireless energy harvesting capabilities"
    - "a stochastic geometry based demand response management framework for cellular networks powered by smart grid"
    - "fog computing based radio access networks issues and challenges"
    - "a hybrid energy sharing framework for green cellular networks"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "green networking in cellular hetnets a unified radio resource management framework with base station on off switching"
    - "online ski rental for on off scheduling of energy harvesting base stations"
    - "dynamic clustering and on off strategies for wireless small cell networks"

Connected through hyperedge HE-7 (induced by source paper "a brief history on the theoretical analysis of dense small cell wireless networks"):
  with members:
    - "optimal base station antenna downtilt in downlink cellular networks"
    - "sinr and throughput of dense cellular networks with stretched exponential path loss"
    - "ultra dense networks is there a limit to spatial spectrum reuse"
    - "wireless powered dense cellular networks how many small cells do we need"
    - "inter operator base station coordination in spectrum shared millimeter wave cellular networks"
    - "downlink cellular network analysis with los nlos propagation and elevated base stations"
    - "performance impact of base station antenna heights in dense cellular networks"
    - "modeling infrastructure sharing in mmwave networks with shared spectrum licenses"

Connected through hyperedge HE-8 (induced by source paper "5g massive mimo architectures self backhauled small cells versus direct access"):
  with members:
    - "performance analysis for practical unmanned aerial vehicle networks with los nlos transmissions"
    - "performance of massive mimo self backhauling for ultra dense small cell deployments"
    - "performance of dynamic and static tdd in self backhauled millimeter wave cellular networks"
    - "uplink sounding reference signal coordination to combat pilot contamination in 5g massive mimo"
    - "joint backhaul access analysis of full duplex self backhauling heterogeneous networks"
    - "analysis of massive mimo enabled downlink wireless backhauling for full duplex small cells"
    - "the new frontier in ran heterogeneity multi tier drone cells"
    - "performance impact of los and nlos transmissions in dense 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.NI(Networking and Internet Architecture)