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 order optimality of large scale underwater networks"):
  Abstract: Capacity scaling laws are analyzed in an underwater acoustic network with $n$ regularly located nodes on a square, in which both bandwidth and received signal power can be limited significantly. A narrow-band model is assumed where the carrier frequency is allowed to scale as a function of $n$. In the network, we characterize an attenuation parameter that depends on the frequency scaling as well as the transmission distance. Cut-set upper bounds on the throughput scaling are then derived in both extended and dense networks having unit node density and unit area, respectively. It is first analyzed that under extended networks, the upper bound is inversely proportional to the attenuation parameter, thus resulting in a highly power-limited network. Interestingly, it is seen that the upper bound for extended networks is intrinsically related to the attenuation parameter but not the spreading factor. On the other hand, in dense networks, we show that there exists either a bandwidth or power limitation, or both, according to the path-loss attenuation regimes, thus yielding the upper bound that has three fundamentally different operating regimes. Furthermore, we describe an achievable scheme based on the simple nearest-neighbor multi-hop (MH) transmission. We show that under extended networks, the MH scheme is order-optimal for all the operating regimes. An achievability result is also presented in dense networks, where the operating regimes that guarantee the order optimality are identified. It thus turns out that frequency scaling is instrumental towards achieving the order optimality in the regimes. Finally, these scaling results are extended to a random network realization. As a result, vital information for fundamental limits of a variety of underwater network scenarios is provided by showing capacity scaling laws.

Includes members:
  Member "improved capacity scaling in wireless networks with infrastructure":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the effects of subpacketization in content centric mobile networks")
  Member "linear capacity scaling in wireless networks beyond physical limits":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capacity scaling of cellular networks impact of bandwidth infrastructure density and number of antennas")
  Member "capacity scaling laws for underwater networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on capacity scaling of underwater networks an information theoretic perspective")
  Member "on capacity scaling in arbitrary wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "throughput scaling of covert communication over wireless adhoc networks")
  Member "information theoretic operating regimes of large wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "capacity scaling of cellular networks impact of bandwidth infrastructure density and number of antennas")
  Member "on the relationship between transmission power and capacity of an underwater acoustic communication channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on capacity scaling of underwater networks an information theoretic perspective")
  Member "underwater acoustic networks channel models and network coding based lower bound to transmission power for multicast":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on capacity scaling of underwater networks an information theoretic perspective")
  Member "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "wireless mesh networking with devices equipped with multi connectivity")

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)