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 "accuracy of range based cooperative localization in wireless sensor networks a lower bound analysis"):
  Abstract: Accurate location information is essential for many wireless sensor network (WSN) applications. A location-aware WSN generally includes two types of nodes: sensors whose locations to be determined and anchors whose locations are known a priori. For range-based localization, sensors' locations are deduced from anchor-to-sensor and sensor-to-sensor range measurements. Localization accuracy depends on the network parameters such as network connectivity and size. This paper provides a generalized theory that quantitatively characterizes such relation between network parameters and localization accuracy. We use the average degree as a connectivity metric and use geometric dilution of precision (DOP), equivalent to the Cramer-Rao bound, to quantify localization accuracy. We prove a novel lower bound on expectation of average geometric DOP (LB-E-AGDOP) and derives a closed-form formula that relates LB-E-AGDOP to only three parameters: average anchor degree, average sensor degree, and number of sensor nodes. The formula shows that localization accuracy is approximately inversely proportional to the average degree, and a higher ratio of average anchor degree to average sensor degree yields better localization accuracy. Furthermore, the paper demonstrates a strong connection between LB-E-AGDOP and the best achievable accuracy. Finally, we validate the theory via numerical simulations with three different random graph models.

Includes members:
  Member "cramer rao bounds for joint rss doa based primary user localization in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "peregrine network localization and navigation with scalable inference and efficient operation")
  Member "fundamental limits of wideband localization part ii cooperative networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "peregrine network localization and navigation with scalable inference and efficient operation")

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)