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 "tier aware resource allocation in ofdma macrocell small cell networks"):
  Abstract: We present a joint sub-channel and power allocation framework for downlink transmission in an orthogonal frequency-division multiple access (OFDMA)-based cellular network composed of a macrocell overlaid by small cells. In this framework, the resource allocation (RA) problems for both the macrocell and small cells are formulated as optimization problems. For the macrocell, we formulate an RA problem that is aware of the existence of the small cell tier. In this problem, the macrocell performs RA to satisfy the data rate requirements of macro user equipments (MUEs) while maximizing the tolerable interference from the small cell tier on its allocated sub-channels. Although the RA problem for the macrocell is shown to be a mixed integer nonlinear problem (MINLP), we prove that the macrocell can solve another alternate optimization problem that will yield the optimal solution with reduced complexity. For the small cells, following the same idea of tier-awareness, we formulate an optimization problem that accounts for both RA and admission control (AC) and aims at maximizing the number of admitted users while simultaneously minimizing the consumed bandwidth. Similar to the macrocell optimization problem, the small cell problem is shown to be an MINLP. We obtain a sub-optimal solution to the MINLP problem relying on convex relaxation. In addition, we employ the dual decomposition technique to have a distributed solution for the small cell tier. Numerical results confirm the performance gains of our proposed RA formulation for the macrocell over the traditional resource allocation based on minimizing the transmission power. Besides, it is shown that the formulation based on convex relaxation yields a similar behavior to the MINLP formulation. Also, the distributed solution converges to the same solution obtained by solving the corresponding convex optimization problem in a centralized fashion.

Includes members:
  Member "evolution toward 5g multi tier cellular wireless networks an interference management perspective":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on the security and the evolution of osmotic and catalytic computing for 5g networks")
  Member "joint power and admission control via linear programming deflation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint long term admission control and beamforming in green downlink networks offline and online approaches")
  Member "on the complexity of joint subcarrier and power allocation for multi user ofdma systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "harq cc enabled noma designs with outage probability constraints")
  Member "refim a practical interference management in heterogeneous wireless access networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "power efficient sampling time and resource allocation in cyber physical systems with industrial application")
  Member "price based resource allocation for spectrum sharing femtocell networks a stackelberg game approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint dynamic pricing and radio resource allocation framework for iot services")
  Member "joint bandwidth and power allocation with admission control in wireless multi user networks with and without relaying":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sample approximation based deflation approaches for chance sinr constrained joint power and admission control")
  Member "distributed and optimal reduced primal dual algorithm for uplink ofdm resource allocation":
    also connected through other hyperedges:
      (none)

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)