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 "lower bound on the localization error in infinite networks with random sensor locations"):
  Abstract: We present novel lower bounds on the mean square error (MSE) of the location estimation of an emitting source via a network where the sensors are deployed randomly. The sensor locations are modeled as a homogenous Poisson point process. In contrast to previous bounds that are a function of the specific locations of all the sensors, we present Cramer–Rao bound (CRB) type bounds on the expected mean square error; that is, we first derive the CRB on the MSE as a function of the sensors’ location, and then take expectation with respect to the distribution of the sensors’ location. Thus, these bounds are not a function of a particular sensor configuration, but rather of the sensor statistics. Hence, these novel bounds can be evaluated prior to sensor deployment and provide insights into design issues such as the necessary sensor density, the effect of the channel model, the effect of the signal power, and others. The derived bounds are simple to evaluate and provide a good prediction of the actual network performance. Numerical results show that the novel bounds give a good approximation even in other deployment scenarios such as a square or a triangular grid.

Includes members:
  Member "on localization of a non cooperative target with non coherent binary detectors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the existence of an mvu estimator for target localization with censored noise free binary detectors")
  Member "an overview of the transmission capacity of wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "outage local throughput and capacity of random wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "modeling analysis and mitigation of dynamic botnet formation in wireless iot networks")
  Member "transmission capacity of ad hoc networks with spatial diversity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular 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.IT(Information Theory)