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: "inference from randomized transmissions by many backscatter sensors"
  Abstract: Attaining the vision of Smart Cities requires the deployment of an enormous number of sensors for monitoring various conditions of the environment. Backscatter-sensors have emerged to be a promising solution due to the uninterruptible energy supply and relative simple hardwares. On the other hand, backscatter-sensors with limited signal-processing capabilities are unable to support conventional algorithms for multiple-access and channel-training. Thus, the key challenge in designing backscatter-sensor networks is to enable readers to accurately detect sensing-values given simple ALOHA random access, primitive transmission schemes, and no knowledge of channel-states. We tackle this challenge by proposing the novel framework of backscatter sensing featuring random-encoding at sensors and statistical-inference at readers. Specifically, assuming the on/off keying for backscatter transmissions, the practical random-encoding scheme causes the on/off transmission of a sensor to follow a distribution parameterized by the sensing values. Facilitated by the scheme, statistical-inference algorithms are designed to enable a reader to infer sensing-values from randomized transmissions by multiple sensors. The specific design procedure involves the construction of Bayesian networks, namely deriving conditional distributions for relating unknown parameters and variables to signals observed by the reader. Then based on the Bayesian networks and the well-known expectation-maximization principle, inference algorithms are derived to recover sensing-values.

Connected through hyperedge HE-1 (induced by source paper "over the air computation systems optimization analysis and scaling laws"):
  with members:
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "wireless networked control systems with coding free data transmission for industrial iot"
    - "wireless federated distillation for distributed edge learning with heterogeneous data"
    - "optimal power control for over the air computation in fading channels"
    - "exploiting the superposition property of wireless communication for max consensus problems in multi agent systems"
    - "towards an intelligent edge wireless communication meets machine learning"
    - "over the air function computation in sensor networks"
    - "optimal power allocation for parameter tracking in a distributed amplify and forward sensor network"

Connected through hyperedge HE-2 (induced by source paper "sum throughput maximization in multi tag backscattering to multiantenna reader"):
  with members:
    - "optimal channel estimation for reciprocity based backscattering with a full duplex mimo reader"
    - "cooperative ambient backscatter communications for green internet of things"
    - "fractional programming for communication systems part i power control and beamforming"
    - "retrodirective large antenna energy beamforming in backscatter multi user networks"
    - "transmit precoding and receive power splitting for harvested power maximization in mimo swipt systems"
    - "max min sinr in large scale single cell mu mimo asymptotic analysis and low complexity transceivers"
    - "throughput optimization for massive mimo systems powered by wireless energy transfer"
    - "multi antenna wireless energy transfer for backscatter communication systems"

Connected through hyperedge HE-3 (induced by source paper "multi tag backscattering to mimo reader channel estimation and throughput fairness"):
  with members:
    - "sum throughput maximization in multi tag backscattering to multiantenna reader"
    - "optimal channel estimation for reciprocity based backscattering with a full duplex mimo reader"
    - "multiuser wirelessly powered backscatter communications nonlinearity waveform design and sinr energy tradeoff"
    - "retrodirective large antenna energy beamforming in backscatter multi user networks"
    - "backscatter multiplicative multiple access systems fundamental limits and practical design"
    - "ambient backscatter communications a contemporary survey"
    - "throughput optimization for massive mimo systems powered by wireless energy transfer"
    - "multi antenna wireless energy transfer for backscatter communication systems"

Connected through hyperedge HE-4 (induced by source paper "backscatter data collection with unmanned ground vehicle mobility management and power allocation"):
  with members:
    - "energy constrained uav trajectory design for ground node localization"
    - "resource allocation for solar powered uav communication systems"
    - "aerial anchors positioning for reliable rss based outdoor localization in urban environments"
    - "wirelessly powered backscatter communications waveform design and snr energy tradeoff"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "multistatic scatter radio sensor networks for extended coverage"
    - "full duplex backscatter interference networks based on time hopping spread spectrum"

Connected through hyperedge HE-5 (induced by source paper "joint communication and motion energy minimization in ugv backscatter communication"):
  with members:
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "multistatic scatter radio sensor networks for extended coverage"
    - "multipair two way relay network with harvest then transmit users resolving pairwise uplink downlink coupling"
    - "on the efficiency of far field wireless power transfer"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-6 (induced by source paper "joint frequency and phase modulation for backscatter tag assisted vehicular positioning"):
  with members:
    - "netscatter enabling large scale backscatter networks"
    - "ambient backscatter communications a contemporary survey"
    - "millimeter wave vehicular communication to support massive automotive sensing"
    - "wirelessly powered backscatter communication networks modeling coverage and capacity"

Connected through hyperedge HE-7 (induced by source paper "reduced dimension design of mimo over the air computing for data aggregation in clustered iot networks"):
  with members:
    - "broadband analog aggregation for low latency federated edge learning extended version"
    - "wirelessly powered data aggregation for iot via over the air functional computation beamforming and power control"
    - "blind over the air computation and data fusion via provable wirtinger flow"
    - "hybrid beamforming via the kronecker decomposition for the millimeter wave massive mimo systems"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "communication efficient learning of deep networks from decentralized data"
    - "over the air function computation in sensor networks"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-8 (induced by source paper "wirelessly powered data aggregation for iot via over the air functional computation beamforming and power control"):
  with members:
    - "over the air function computation in sensor networks"
    - "communications and signals design for wireless power transmission"
    - "resource allocation in wireless powered relay networks a bargaining game approach"
    - "wireless powered communication opportunities and challenges"
    - "throughput optimization for massive mimo systems powered by wireless energy transfer"
    - "energy harvesting for physical layer security in ofdma networks"
    - "simultaneous wireless information and power transfer under different csi acquisition schemes"
    - "cutting last wires for mobile communication by microwave power transfer"

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)