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: "joint channel estimation decoding with frequency selective channels and few bit adcs"
  Abstract: We propose a fast and near-optimal approach to joint channel-estimation, equalization, and decoding of coded single-carrier (SC) transmissions over frequency-selective channels with few-bit analog-to-digital converters (ADCs). Our approach leverages parametric bilinear generalized approximate message passing to reduce the implementation complexity of joint channel estimation and (soft) symbol decoding to that of a few fast Fourier transforms. Furthermore, it learns and exploits sparsity in the channel impulse response. This paper is motivated by millimeter-wave systems with bandwidths on the order of Gsamples/sec, where few-bit ADCs, SC transmissions, and fast processing all lead to significant reductions in power consumption and implementation cost. We numerically demonstrate our approach using signals and channels generated according to the IEEE 802.11ad wireless local area network standard, in the case that the receiver uses analog beamforming and a single ADC.

Connected through hyperedge HE-1 (induced by source paper "reliable ofdm transmission with ultra low resolution adc"):
  with members:
    - "low complexity multiuser qam detection for uplink 1 bit massive mimo"
    - "a general framework for low resolution receivers for mimo channels"
    - "uplink multiuser massive mimo systems with low resolution adcs a coding theoretic approach"
    - "bayesian optimal data detector for mmwave ofdm system with low resolution adc"
    - "generalized expectation consistent signal recovery for nonlinear measurements"
    - "denoising based turbo compressed sensing"
    - "channel estimation and data equalization in frequency selective mimo systems with one bit quantization"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"

Connected through hyperedge HE-2 (induced by source paper "soft output detection methods for sparse millimeter wave mimo systems with low precision adcs"):
  with members:
    - "on low resolution adcs in practical 5g millimeter wave massive mimo systems"
    - "bayesian optimal data detector for hybrid mmwave mimo ofdm systems with low resolution adcs"
    - "one bit sphere decoding for uplink massive mimo systems with one bit adcs"
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "bayesian optimal data detector for mmwave ofdm system with low resolution adc"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"

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)