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: "analysis of cell load coupling for lte network planning and optimization"
  Abstract: System-centric modeling and analysis are of key significance in planning and optimizing cellular networks. In this paper, we provide a mathematical analysis of performance modeling for LTE networks. The system model characterizes the coupling relation between the cell load factors, taking into account non-uniform traffic demand and interference between the cells with arbitrary network topology. Solving the model enables a network-wide performance evaluation in resource consumption. We develop and prove both sufficient and necessary conditions for the feasibility of the load-coupling system, and provide results related to computational aspects for numerically approaching the solution. The theoretical findings are accompanied with experimental results to instructively illustrate the application in optimizing LTE network configuration.

Connected through hyperedge HE-1 (induced by source paper "a note on decoding order in optimizing multi cell noma"):
  with members:
    - "a robust machine learning method for cell load approximation in wireless networks"
    - "a framework for optimizing multi cell noma delivering demand with less resource"
    - "resource optimization with load coupling in multi cell noma"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"
    - "energy aware wireless relay selection in load coupled ofdma cellular networks"
    - "load optimization with user association in cooperative and load coupled lte networks"
    - "dynamic user clustering and power allocation for uplink and downlink non orthogonal multiple access noma systems"
    - "elementary properties of positive concave mappings with applications to network planning and optimization"

Connected through hyperedge HE-2 (induced by source paper "multi tenant cross slice resource orchestration a deep reinforcement learning approach"):
  with members:
    - "low complexity distributed radio access network slicing algorithms and experimental results"
    - "distributed resource allocation for network slicing over licensed and unlicensed bands"
    - "dynamic network slicing for scalable fog computing systems with energy harvesting"
    - "performance optimization in mobile edge computing via deep reinforcement learning"
    - "network slicing for 5g with sdn nfv concepts architectures and challenges"
    - "a survey on mobile edge computing the communication perspective"
    - "near optimal behavior via approximate state abstraction"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"

Connected through hyperedge HE-3 (induced by source paper "statistical learning of geometric characteristics of wireless networks"):
  with members:
    - "a robust machine learning method for cell load approximation in wireless networks"
    - "super resolution with deep convolutional sufficient statistics"
    - "how user throughput depends on the traffic demand in large cellular networks"

Connected through hyperedge HE-4 (induced by source paper "load based on off scheduling for energy efficient delay tolerant 5g networks"):
  with members:
    - "ultra dense small cell networks turning density into energy efficiency"
    - "throughput and energy efficiency analysis of small cell networks with multi antenna base stations"

Connected through hyperedge HE-5 (induced by source paper "resource optimization with load coupling in multi cell noma"):
  with members:
    - "a robust machine learning method for cell load approximation in wireless networks"
    - "a framework for optimizing multi cell noma delivering demand with less resource"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"
    - "energy aware wireless relay selection in load coupled ofdma cellular networks"
    - "sub channel assignment power allocation and user scheduling for non orthogonal multiple access networks"
    - "load optimization with user association in cooperative and load coupled lte networks"
    - "elementary properties of positive concave mappings with applications to network planning and optimization"
    - "power and channel allocation for non orthogonal multiple access in 5g systems tractability and computation"

Connected through hyperedge HE-6 (induced by source paper "power control for multi cell networks with non orthogonal multiple access"):
  with members:
    - "resource optimization in multi cell noma"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "sub channel assignment power allocation and user scheduling for non orthogonal multiple access networks"
    - "energy efficient transmission design in non orthogonal multiple access"
    - "load optimization with user association in cooperative and load coupled lte networks"
    - "a minorization maximization method for optimizing sum rate in the downlink of non orthogonal multiple access systems"
    - "power and channel allocation for non orthogonal multiple access in 5g systems tractability and computation"
    - "non orthogonal multiple access in multi cell networks theory performance and practical challenges"

Connected through hyperedge HE-7 (induced by source paper "resource optimization in multi cell noma"):
  with members:
    - "a framework for optimizing multi cell noma delivering demand with less resource"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"
    - "energy aware wireless relay selection in load coupled ofdma cellular networks"
    - "load optimization with user association in cooperative and load coupled lte networks"
    - "elementary properties of positive concave mappings with applications to network planning and optimization"
    - "energy efficiency of distributed signal processing in wireless networks a cross layer analysis"
    - "non orthogonal multiple access in multi cell networks theory performance and practical challenges"
    - "power and load coupling in cellular networks for energy optimization"

Connected through hyperedge HE-8 (induced by source paper "user centric performance optimization with remote radio head cooperation in c ran"):
  with members:
    - "joint precoding and rrh selection for user centric green mimo c ran"
    - "load balancing via joint transmission in heterogeneous lte modeling and computation"
    - "joint comp cell selection and resource allocation with fronthaul constrained c ran"
    - "load optimization with user association in cooperative and load coupled lte networks"
    - "dynamic joint uplink and downlink optimization for uplink and downlink decoupling enabled 5g heterogeneous networks"
    - "green ofdma resource allocation in cache enabled cran"
    - "cooperative interference mitigation and handover management for heterogeneous cloud small cell networks"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access 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)