human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "utility maximization for single station user association in downlink cellular networks"):
  Abstract: We study network utility maximization (NUM) in the context of cellular single station association (SSA) policies, which assigns each mobile user (MU) to a single base station (BS). We measure an SSA policy in terms of the induced \alpha-proportional fairness utility of each user's downlink rate, summed over all users. The general SSA NUM problem involves choosing an optimal association from MUs to BSs as well as an optimal allocation of BS resources to associated MUs. Finding an exact solution to such centralized user association problems is well-known to be NP-hard. Our contributions are as follows: i) we give an explicit solution for the optimal BS allocation for a given SSA, which establishes SSA NUM as a purely combinatiorial problem; ii) we establish the integrality gap for the association problem to be one, and prove the relaxation to be a non-convex optimization problem; iii) we provide both centralized and distributed greedy algorithms for SSA, both with and without the exchange of instantaneous rate information between users and stations. Our numerical results illustrate performance gains of three classes of solutions: i) SSA solutions obtained by greedy rounding of multi-station associations (a centralized convex program), ii) our centralized and distributed greedy algorithms with/without rate information exchanged, and iii) simple association heuristics.

Includes members:
  Member "delay minimizing user association in cellular networks via hierarchically well separated trees":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal user association for massive mimo empowered ultra dense wireless networks")
  Member "joint downlink base station association and power control for max min fairness computation and complexity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "max min fairness user scheduling and power allocation in full duplex ofdma systems")
  Member "distributed pricing based user association for downlink heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reinforcement learning based vehicle cell association algorithm for highly mobile millimeter wave communication")
  Member "offloading in heterogeneous networks modeling analysis and design insights":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "heterogeneous cellular networks with flexible cell association a comprehensive downlink sinr analysis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stochastic geometry analysis of sojourn time in multi tier cellular networks")
  Member "user association for load balancing in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coexistence mechanism between embb and urllc in 5g wireless networks")

Question: Please tell me which class the source paper 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)