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 "performance evaluation and optimization of lpwa iot networks a stochastic geometry approach"):
  Abstract: Leveraging grant-free radio access for enabling lowpower wide-area (LPWA) Internet of Things (IoT) connectivity has attracted lots of attention in recent years. Regarding lack of research on LPWA IoT networks, this work is devoted to reliability modeling, battery-lifetime analysis, and operation-control of such networks. We derive the interplay amongst density of the access points, communication bandwidth, volume of traffic from heterogeneous sources, and quality of service (QoS) in communications. The presented analytical framework comprises modeling of interference from heterogeneous sources with correlated deployment locations and time-frequency asynchronous radio-resource usage patterns. The derived expressions represent the operation regions and rates in which, energy and cost resources of devices and the access network, respectively, could be traded to achieve a given level of QoS in communications. For example, our expressions indicate the expected increase in QoS by increasing number of transmitted replicas, transmit power, density of the access points, and communication bandwidth. Our results further shed light on scalability of such networks and figure out the bounds up to which, scaling resources can compensate the increase in traffic volume and QoS demand. Finally, we present an energy-optimized operation control policy for IoT devices. The simulation results confirm tightness of the derived analytical expressions, and indicate usefulness of them in planning and operation control of IoT networks.

Includes members:
  Member "optimized resource provisioning and operation control for low power wide area iot networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "self organized low power iot networks a distributed learning approach")
  Member "grant free radio access for short packet communications over 5g networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "space diversity based grant free random access for critical and non critical iot services")
  Member "poisson cluster process bridging the gap between ppp and 3gpp hetnet models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "grant free radio access iot networks scalability analysis in coexistence scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "space diversity based grant free random access for critical and non critical iot services")
  Member "network lifetime maximization for cellular based m2m networks":
    also connected through other hyperedges:
      (none)
  Member "non orthogonal multiple access noma in cellular uplink and downlink challenges and enabling techniques":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the performance of non orthogonal multiple access in the finite blocklength regime")
  Member "e 2 mac energy efficient medium access for massive m2m communications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "grant free radio access iot networks scalability analysis in coexistence scenarios")
  Member "2d time frequency interference modelling using stochastic geometry for performance evaluation in low power wide area networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal secure two layer iot network design")

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)