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: "coexistence of urllc and embb services in the c ran uplink an information theoretic study"
  Abstract: The performance of orthogonal and non-orthogonal multiple access is studied for the multiplexing of enhanced Mobile BroadBand (eMBB) and Ultra-Reliable Low-Latency Communications (URLLC) users in the uplink of a multi-cell Cloud Radio Access Network (C-RAN) architecture. While eMBB users can operate over long codewords spread in time and frequency, URLLC users' transmissions are random and localized in time due to their low-latency requirements. These requirements also call for decoding of their packets to be carried out at the edge nodes (ENs), whereas eMBB traffic can leverage the interference management capabilities of centralized decoding at the cloud. Using information-theoretic arguments, the performance trade-offs between eMBB and URLLC traffic types are investigated in terms of rate for the former, and rate, access latency, and reliability for the latter. The analysis includes non-orthogonal multiple access (NOMA) with different decoding architectures, such as puncturing and successive interference cancellation (SIC). The study sheds light into effective design choices as a function of inter-cell interference, signal-to-noise ratio levels, and fronthaul capacity constraints.

Connected through hyperedge HE-1 (induced by source paper "intelligent resource slicing for embb and urllc coexistence in 5g and beyond a deep reinforcement learning based approach"):
  with members:
    - "extreme urllc vision challenges and key enablers"
    - "coexistence mechanism between embb and urllc in 5g wireless networks"
    - "embb urllc resource slicing a risk sensitive approach"
    - "ultra reliable and low latency vehicular transmission an extreme value theory approach"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "urllc embb slicing to support vr multimodal perceptions over wireless cellular systems"

Connected through hyperedge HE-2 (induced by source paper "coexistence mechanism between embb and urllc in 5g wireless networks"):
  with members:
    - "embb urllc resource slicing a risk sensitive approach"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "network slicing for service oriented networks under resource constraints"
    - "joint scheduling of urllc and embb traffic in 5g wireless networks"
    - "resource scheduling for mixed traffic types with scalable tti in dynamic tdd systems"
    - "the dispersion of nearest neighbor decoding for additive non gaussian channels"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-3 (induced by source paper "multiplexing gain region of sectorized cellular networks with mixed delay constraints"):
  with members:
    - "resource allocation for multi user downlink urllc ofdma systems"
    - "non orthogonal multiplexing of ultra reliable and broadband services in fog radio architectures"
    - "channels with cooperation links that may be absent"
    - "layered uplink transmission in clustered cellular networks"
    - "optimal dynamic resource allocation for multi antenna broadcasting with heterogeneous delay constrained traffic"

Connected through hyperedge HE-4 (induced by source paper "non orthogonal network slicing for embb service in a multi uav aided network"):
  with members:
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "network slicing based 5g and future mobile networks mobility resource management and challenges"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"

Connected through hyperedge HE-5 (induced by source paper "non orthogonal multiplexing of ultra reliable and broadband services in fog radio architectures"):
  with members:
    - "joint power and time allocation for noma mec offloading"
    - "mixed delay constraints in wyner s soft handoff network"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "cognitive non orthogonal multiple access with cooperative relaying a new wireless frontier for 5g spectrum sharing"
    - "non orthogonal embb urllc radio access for cloud radio access networks with analog fronthauling"
    - "joint scheduling of urllc and embb traffic in 5g wireless networks"
    - "fronthaul compression and precoding design for c rans over ergodic fading channels"
    - "fog computing based radio access networks issues and challenges"

Connected through hyperedge HE-6 (induced by source paper "non orthogonal embb urllc radio access for cloud radio access networks with analog fronthauling"):
  with members:
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "network slicing based 5g and future mobile networks mobility resource management and challenges"
    - "on the transport capability of lan cables in all analog mimo roc fronthaul"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "joint scheduling of urllc and embb traffic in 5g wireless networks"
    - "non orthogonal multiple access in multi cell networks theory performance and practical challenges"
    - "the dispersion of nearest neighbor decoding for additive non gaussian channels"
    - "ordered tomlinson harashima precoding in g fast downstream"

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)