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 "random access based reliable uplink communication and power transfer using dynamic power splitting"):
  Abstract: Large communication networks, e.g. Internet of Things (IoT), are known to be vulnerable to co-channel interference. One possibility to address this issue is the use of orthogonal multiple access (OMA) techniques. However, due to a potentially very long duty cycle, OMA is not well suited for such schemes. Instead, random medium access (RMA) appears more promising. An RMA scheme is based on transmission of short data packets with random scheduling, which is typically unknown to the receiver. The received signal, which consists of the overlapping packets, can be used for energy harvesting and powering of a relay device. Such an energy harvesting relay may utilize the energy for further information processing and uplink transmission. In this paper, we address the design of a simultaneous information and power transfer scheme based on randomly scheduled packet transmissions and reliable symbol detection. We formulate a prediction problem with the goal to maximize the harvested power for an RMA scenario. In order to solve this problem, we propose a new prediction method, which shows a significant performance improvement compared to the straightforward baseline scheme. Furthermore, we investigate the complexity of the proposed method and its vulnerability to imperfect channel state information.

Includes members:
  Member "joint uplink and downlink resource configuration for ultra reliable and low latency communications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scheduling observers over a shared channel with hard delivery deadlines")
  Member "ultra reliable cooperative short packet communications with wireless energy transfer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rate control for wireless powered communication network with reliability and delay constraints")
  Member "on the beneficial roles of fading and transmit diversity in wireless power transfer with nonlinear energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "integration of satellites in 5g through leo constellations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "leo small satellite constellations for 5g and beyond 5g communications")
  Member "ultra reliable and low latency communication in mmwave enabled massive mimo networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "analyzing the tradeoffs in using millimeter wave directional links for high data rate tactile internet applications")
  Member "low power wide area networks an overview":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "spectrum sharing for massive access in ultra narrowband iot systems")
  Member "practical non linear energy harvesting model and resource allocation for swipt systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "joint transmit beamforming and receive power splitting for miso swipt systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "an energy efficient controller for wirelessly powered communication 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)