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: "on ergodic sum capacity of fading cognitive multiple access and broadcast channels"
  Abstract: This paper studies the information-theoretic limits of a secondary or cognitive radio (CR) network under spectrum sharing with an existing primary radio network. In particular, the fading cognitive multiple-access channel (C-MAC) is first studied, where multiple secondary users transmit to the secondary base station (BS) under both individual transmit-power constraints and a set of interference-power constraints each applied at one of the primary receivers. This paper considers the long-term (LT) or the short-term (ST) transmit-power constraint over the fading states at each secondary transmitter, combined with the LT or ST interference-power constraint at each primary receiver. In each case, the optimal power allocation scheme is derived for the secondary users to achieve the ergodic sum capacity of the fading C-MAC, as well as the conditions for the optimality of the dynamic time-division multiple-access (D-TDMA) scheme in the secondary network. The fading cognitive broadcast channel (C-BC) that models the downlink transmission in the secondary network is then studied under the LT/ST transmit-power constraint at the secondary BS jointly with the LT/ST interference-power constraint at each of the primary receivers. It is shown that D-TDMA is indeed optimal for achieving the ergodic sum capacity of the fading C-BC for all combinations of transmit-power and interference-power constraints.

Connected through hyperedge HE-1 (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-2 (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"
    - "inference from randomized transmissions by many backscatter sensors"
    - "over the air function computation in sensor networks"

Connected through hyperedge HE-3 (induced by source paper "optimal power control for over the air computation in fading channels"):
  with members:
    - "broadband analog aggregation for low latency federated edge learning extended version"
    - "federated learning via over the air computation"
    - "reduced dimension design of mimo over the air computing for data aggregation in clustered iot networks"
    - "blind over the air computation and data fusion via provable wirtinger flow"
    - "over the air function computation in sensor networks"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"
    - "compute and forward harnessing interference through structured codes"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-4 (induced by source paper "improper gaussian signaling for multiple access channels in underlay cognitive radio"):
  with members:
    - "rate region boundary of the siso z interference channel with improper signaling"
    - "improper gaussian signaling in full duplex relay channels with residual self interference"
    - "underlay spectrum sharing techniques with in band full duplex systems using improper gaussian signaling"
    - "benefits of improper signaling for underlay cognitive radio"
    - "improper signaling for symbol error rate minimization in k user interference channel"
    - "optimized transmission with improper gaussian signaling in the k user miso interference channel"
    - "transmit optimization with improper gaussian signaling for interference channels"
    - "interference alignment with asymmetric complex signaling settling the host madsen nosratinia conjecture"

Connected through hyperedge HE-5 (induced by source paper "spectral efficiency of ofdma cognitive radios under imperfect cross link knowledge"):
  with members:
    - "optimal bandwidth and power allocation for sum ergodic capacity under fading channels in cognitive radio networks"

Connected through hyperedge HE-6 (induced by source paper "spectral efficiency of multi user adaptive cognitive radio networks"):
  with members:
    - "optimal bandwidth and power allocation for sum ergodic capacity under fading channels in cognitive radio networks"

Connected through hyperedge HE-7 (induced by source paper "sensing throughput optimization in fading cognitive multiple access channels with energy harvesting secondary transmitters"):
  with members:
    - "optimum transmission policies for battery limited energy harvesting nodes"
    - "information theoretic analysis of an energy harvesting communication system"

Connected through hyperedge HE-8 (induced by source paper "cognitive wireless powered network spectrum sharing models and throughput maximization"):
  with members:
    - "wireless powered communication opportunities and challenges"
    - "throughput optimization for massive mimo systems powered by wireless energy transfer"
    - "collaborative wireless energy and information transfer in interference channel"
    - "multiuser mimo wireless energy transfer with coexisting opportunistic communication"
    - "spatial throughput maximization of wireless powered communication networks"
    - "harvest then cooperate wireless powered cooperative communications"
    - "user cooperation in wireless powered communication networks"
    - "optimal resource allocation in full duplex wireless powered communication network"

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)