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 "on the throughput maximization in dencentralized wireless networks"):
  Abstract: A distributed single-hop wireless network with K links is considered, where the links are partitioned into M clusters each operating in an orthogonal subchannel with bandwidth W . We consider a general shadow-fading model, described with parameters (; $), where denotes the probability of shadowing and $ represents the average power of the cross-link channels. The main goal of this paper is to maximize the network throughput. This is achieved by: i) proposing a distributed and non-iterative power allocation strategy, where the objective function for each user is to maximize its best estimate (based on its local information, i.e., direct channel gain) of the average network throughput, and ii) choosing the optimum value for 1 M K. We analyze the throughput of the network in terms of M and (; $) in the asymptotic case of K ! 1. It is proved that when the number of links is large, the optimum power allocation strategy for each user is the threshold-based on-off power scheme (i.e., links with a direct channel gain above certain threshold transmit at full power and the rest remain silent). Under the on-off power scheme, it is demonstrated that the maximum achievable network throughput for every value of 1 M K, 0 < 1 and $ 1 is achieved at M = 1.

Includes members:
  Member "on capacity scaling in arbitrary wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "throughput scaling of covert communication over wireless adhoc networks")
  Member "bandwidth partitioning in decentralized wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reliability and local delay in wireless networks does bandwidth partitioning help")
  Member "fractional power control for decentralized wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stability and metastability of traffic dynamics in uplink random access networks")
  Member "throughput scaling laws for wireless networks with fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hierarchical radio resource optimization for heterogeneous networks with enhanced inter cell interference coordination eicic")

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.IT(Information Theory)