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: "capacity of sparse multipath channels in the ultra wideband regime"
  Abstract: This paper studies the ergodic capacity of time-and frequency-selective multipath fading channels in the ultrawide-band (UWB) regime when training signals are used for channel estimation at the receiver. Motivated by recent measurement results on UWB channels, we propose a model for sparse multipath channels. A key implication of sparsity is that the independent degrees of freedom in the channel scale sublinearly with the signal space dimension (product of signaling duration and bandwidth). Sparsity is captured by the number of resolvable paths in delay and Doppler. Our analysis is based on a training and communication scheme that employs signaling over orthogonal short-time Fourier (STF) basis functions. STF signaling naturally relates sparsity in delay-Doppler to coherence in time and frequency. We study the impact of multipath sparsity on two fundamental metrics of spectral efficiency in the wideband/low-SNR limit introduced by Verdu: first- and second-order optimality conditions. Recent results by Zheng et al. have underscored the large gap in spectral efficiency between coherent and noncoherent extremes and the importance of channel learning in bridging the gap. Building on these results, our results lead to the following implications of multipath sparsity: (1) the coherence requirements are shared in both time and frequency, thereby significantly relaxing the required scaling in coherence time with SNR; (2) sparse multipath channels are asymptotically coherent - for a given but large bandwidth, the channel can be learned perfectly and the coherence requirements for first- and second-order optimality met through sufficiently large signaling duration; and (3) the requirement of peaky signals in attaining capacity is eliminated or relaxed in sparse environments.

Connected through hyperedge HE-1 (induced by source paper "capacity scaling in a non coherent wideband massive simo block fading channel"):
  with members:
    - "massive mimo has unlimited capacity"
    - "unified capacity limit of non coherent wideband fading channels"
    - "how much spectrum is too much in millimeter wave wireless access"
    - "massive mimo ten myths and one critical question"
    - "energy based modulation for noncoherent massive simo systems"
    - "massive mimo for maximal spectral efficiency how many users and pilots should be allocated"
    - "low snr capacity of noncoherent fading channels"

Connected through hyperedge HE-2 (induced by source paper "noisy beam alignment techniques for reciprocal mimo channels"):
  with members:
    - "subspace estimation and decomposition for large millimeter wave mimo systems"
    - "beamforming tradeoffs for initial ue discovery in millimeter wave mimo systems"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "training sequence design for feedback assisted hybrid beamforming in massive mimo systems"
    - "what will 5g be"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "spatially sparse precoding in millimeter wave mimo systems"

Connected through hyperedge HE-3 (induced by source paper "spectrum sharing in mmwave cellular networks via cell association coordination and beamforming"):
  with members:
    - "downlink and uplink cell association with traditional macrocells and millimeter wave small cells"
    - "on the accuracy of interference models in wireless communications"
    - "distributed association and relaying with fairness in millimeter wave networks"
    - "spectrum pooling in mmwave networks opportunities challenges and enablers"
    - "towards an appropriate receiver beamforming scheme for millimeter wave communication a power consumption based comparison"
    - "hybrid spectrum access for mmwave networks"
    - "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"

Connected through hyperedge HE-4 (induced by source paper "hybrid analog digital channel estimation and beamforming training throughput tradeoff"):
  with members:
    - "on the number of rf chains and phase shifters and scheduling design with hybrid analog digital beamforming"
    - "low rank spatial channel estimation for millimeter wave cellular systems"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "low complexity polynomial channel estimation in large scale mimo with arbitrary statistics"
    - "low complexity hybrid precoding in massive multiuser mimo systems"
    - "millimeter wave channel modeling and cellular capacity evaluation"

Connected through hyperedge HE-5 (induced by source paper "multichannel group sparsity methods for compressive channel estimation in doubly selective multicarrier mimo systems extended version"):
  with members:
    - "compressed sensing off the grid"
    - "near oracle performance of greedy block sparse estimation techniques from noisy measurements"
    - "a message passing receiver for bicm ofdm over unknown clustered sparse channels"
    - "block sparse signals uncertainty relations and efficient recovery"
    - "model based compressive sensing"
    - "compressive estimation of doubly selective channels in multicarrier systems leakage effects and sparsity enhancing processing"
    - "average case analysis of multichannel sparse recovery using convex relaxation"

Connected through hyperedge HE-6 (induced by source paper "massive mimo with optimal power and training duration allocation"):
  with members:
    - "massive mimo for next generation wireless systems"
    - "effects of channel aging in massive mimo systems"
    - "a coordinated approach to channel estimation in large scale multiple antenna systems"
    - "energy and spectral efficiency of very large multiuser mimo systems"

Connected through hyperedge HE-7 (induced by source paper "on the capacity of multiple access and broadcast fading channels with full channel state information at low snr"):
  with members:
    - "energy efficiency in the low snr regime under queueing constraints and channel uncertainty"
    - "on the low snr capacity of phase shift keying with hard decision detection"
    - "noncoherent rician fading channel part ii spectral efficiency in the low power regime"

Connected through hyperedge HE-8 (induced by source paper "secret key generation from sparse wireless channels ergodic capacity and secrecy outage"):
  with members:
    - "key generation using external source excitation capacity reliability and secrecy exponent"
    - "secret key agreement with channel state information at the transmitter"
    - "exponential decreasing rate of leaked information in universal random privacy amplification"
    - "secrecy outage capacity of fading channels"
    - "information theoretically secret key generation for fading wireless channels"
    - "on the throughput of secure hybrid arq protocols for gaussian block fading channels"
    - "necessary and sufficient conditions for sparsity pattern recovery"

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)