human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "wireless information and power transfer a dynamic power splitting approach"
  Abstract: Energy harvesting is a promising solution to prolong the operation time of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the flat-fading channel, where the receiver has no fixed power supplies and thus needs to replenish energy via WEH from the signals sent by the transmitter. We first consider a SISO (single-input single-output) system where the single-antenna receiver cannot decode information and harvest energy independently from the same signal received. Under this practical constraint, we propose a dynamic power splitting (DPS) scheme, where the received signal is split into two streams with adjustable power levels for information decoding and energy harvesting separately based on the instantaneous channel condition that is assumed to be known at the receiver. We derive the optimal power splitting rule at the receiver to achieve various trade-offs between the maximum ergodic capacity for information transfer and the maximum average harvested energy for power transfer, which are characterized by the boundary of a so-called "rate-energy (R-E)" region. Moreover, for the case when the channel state information is also known at the transmitter, we investigate the joint optimization of transmitter power control and receiver power splitting. The achievable R-E region by the proposed DPS scheme is also compared against that by the existing time switching scheme as well as a performance upper bound by ignoring the practical receiver constraint. Finally, we extend the result for optimal DPS to the SIMO (single-input multiple-output) system where the receiver is equipped with multiple antennas. In particular, we investigate a low-complexity power splitting scheme, namely antenna switching, which achieves the near-optimal rate-energy trade-offs as compared to the optimal DPS.

Connected through hyperedge HE-1 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks"):
  with members:
    - "sensitive and nonlinear far field rf energy harvesting in wireless communications"
    - "ergodic capacity analysis of wireless powered af relaying systems over alpha µ fading channels"
    - "joint relay selection and power allocation in large scale mimo systems with untrusted relays and passive eavesdroppers"
    - "error performance of wireless powered cognitive relay networks with interference alignment"
    - "minimizing outage probability by exploiting csi in wireless powered cooperative networks"
    - "wireless powered relays in cooperative communications time switching relaying protocols and throughput analysis"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"
    - "wireless information and power transfer in relay systems with multiple antennas and interference"

Connected through hyperedge HE-2 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot"):
  with members:
    - "fundamentals of wireless information and power transfer from rf energy harvester models to signal and system designs"
    - "modulation design for wireless information and power transfer with nonlinear energy harvester modeling"
    - "rate energy region in wireless information and power transfer new receiver architecture and practical modulation"
    - "spectral efficiency of multipair massive mimo two way relaying with hardware impairments"
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "on the feasibility of wireless energy transfer using massive antenna arrays"
    - "achievable rate of rician large scale mimo channels with transceiver hardware impairments"
    - "iterative dynamic water filling for fading multiple access channels with energy harvesting"

Connected through hyperedge HE-3 (induced by source paper "simultaneous energy harvesting and information transmission in a mimo full duplex system a machine learning based design"):
  with members:
    - "generalized coordinated multipoint gcomp enabled noma outage capacity and power allocation"
    - "spectral and energy efficiency of uplink d2d underlaid massive mimo cellular networks"
    - "compact full duplex mimo radios in d2d underlaid cellular networks from system design to prototype results"
    - "a general design framework for mimo wireless energy transfer with limited feedback"
    - "continuous control with deep reinforcement learning"
    - "deep reinforcement learning with double q learning"
    - "a survey on device to device communication in cellular networks"
    - "in band full duplex wireless challenges and opportunities"

Connected through hyperedge HE-4 (induced by source paper "random access based reliable uplink communication and power transfer using dynamic power splitting"):
  with members:
    - "joint uplink and downlink resource configuration for ultra reliable and low latency communications"
    - "ultra reliable cooperative short packet communications with wireless energy transfer"
    - "on the beneficial roles of fading and transmit diversity in wireless power transfer with nonlinear energy harvesting"
    - "integration of satellites in 5g through leo constellations"
    - "ultra reliable and low latency communication in mmwave enabled massive mimo networks"
    - "low power wide area networks an overview"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"
    - "joint transmit beamforming and receive power splitting for miso swipt systems"

Connected through hyperedge HE-5 (induced by source paper "energy efficiency of distributed antenna systems with wireless power transfer"):
  with members:
    - "energy efficient swipt in iot distributed antenna systems"
    - "wirelessly powered backscatter communications waveform design and snr energy tradeoff"
    - "fundamental green tradeoffs progresses challenges and impacts on 5g networks"
    - "power allocation for secure swipt systems with wireless powered cooperative jamming"
    - "wireless information and power transfer nonlinearity waveform design and rate energy tradeoff"
    - "artificial noise aided secrecy information and power transfer in ofdma systems"
    - "information and energy cooperation in ofdm relaying protocols and optimization"
    - "secure and green swipt in distributed antenna networks with limited backhaul capacity"

Connected through hyperedge HE-6 (induced by source paper "rate control for wireless powered communication network with reliability and delay constraints"):
  with members:
    - "statistical analysis of multiple antenna strategies for wireless energy transfer"
    - "spectral and energy efficient wireless powered iot networks noma or tdma"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "ultra reliable cooperative short packet communications with wireless energy transfer"
    - "wireless powered relaying with finite block length codes"
    - "arq with adaptive feedback for energy harvesting receivers"
    - "wirelessly powered communication networks with short packets"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"

Connected through hyperedge HE-7 (induced by source paper "deep learning for distributed optimization applications to wireless resource management"):
  with members:
    - "learning optimal resource allocations in wireless systems"
    - "machine learning in the air"
    - "learning to optimize training deep neural networks for interference management"
    - "end to end deep learning of optical fiber communications"
    - "deep learning framework for wireless systems applications to optical wireless communications"
    - "an introduction to deep learning for the physical layer"
    - "optnet differentiable optimization as a layer in neural networks"
    - "the expressive power of neural networks a view from the width"

Connected through hyperedge HE-8 (induced by source paper "throughput maximization in two hop df multiple relay network with simultaneous wireless information and power transfer"):
  with members:
    - "sensitive and nonlinear far field rf energy harvesting in wireless communications"
    - "robust resource allocation for mimo wireless powered communication networks based on a non linear eh model"
    - "training based swipt optimal power splitting at the receiver"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"
    - "information and energy cooperation in ofdm relaying protocols and optimization"
    - "joint power splitting and antenna selection in energy harvesting relay channels"
    - "wireless information and energy transfer for two hop non regenerative mimo ofdm relay networks"
    - "wireless networks with rf energy harvesting a contemporary survey"

Question: Please tell me which class the center node 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)