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: "one bit sphere decoding for uplink massive mimo systems with one bit adcs"
  Abstract: This paper presents a low-complexity near-maximum-likelihood-detection (near-MLD) algorithm called one-bit-sphere-decoding for an uplink massive multiple-input multiple-output (MIMO) system with one-bit analog-to-digital converters (ADCs). The idea of the proposed algorithm is to estimate the transmitted symbol vector sent by uplink users (a codeword vector) by searching over a sphere, which contains a collection of codeword vectors close to the received signal vector at the base station in terms of a weighted Hamming distance. To reduce the computational complexity for the construction of the sphere, the proposed algorithm divides the received signal vector into multiple sub-vectors each with reduced dimension. Then, it generates multiple spheres in parallel, where each sphere is centered at the sub-vector and contains a list of sub-codeword vectors. The detection performance of the proposed algorithm is also analyzed by characterizing the probability that the proposed algorithm performs worse than the MLD. The analysis shows how the dimension of each sphere and the size of the sub-codeword list are related to the performance-complexity tradeoff achieved by the proposed algorithm. Simulation results demonstrate that the proposed algorithm achieves near-MLD performance, while reducing the computational complexity compared to the existing MLD method.

Connected through hyperedge HE-1 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo"):
  with members:
    - "one bit sigma delta mimo precoding"
    - "a framework for one bit and constant envelope precoding over multiuser massive miso channels"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "1 bit massive mu mimo precoding in vlsi"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "branch and bound precoding for multiuser mimo systems with 1 bit quantization"

Connected through hyperedge HE-2 (induced by source paper "massive mu mimo ofdm uplink with direct rf sampling and 1 bit adcs"):
  with members:
    - "timing and frequency synchronization for 1 bit massive mu mimo ofdm downlink"
    - "massive mu mimo ofdm uplink with hardware impairments modeling and analysis"
    - "one bit massive mimo precoding via a minimum symbol error probability design"
    - "directional frame timing synchronization in wideband millimeter wave systems with low resolution adcs"
    - "performance analysis for time of arrival estimation with oversampled low complexity 1 bit a d conversion"
    - "quantized precoding for multi antenna downlink channels with magiq"
    - "nonlinear precoding for phase quantized constant envelope massive mu mimo ofdm"
    - "on out of band emissions of quantized precoding in massive mu mimo ofdm"

Connected through hyperedge HE-3 (induced by source paper "one bit sigma delta mimo precoding"):
  with members:
    - "symbol level precoding is symbol perturbed zf when energy efficiency is sought"
    - "a framework for one bit and constant envelope precoding over multiuser massive miso channels"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "multiuser one bit massive mimo precoding under mpsk signaling"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "1 bit massive mu mimo precoding in vlsi"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"

Connected through hyperedge HE-4 (induced by source paper "supervised learning for multi hop mu mimo communications with one bit transceivers"):
  with members:
    - "one bit ofdm receivers via deep learning"
    - "ofdm autoencoder for end to end learning of communications systems"
    - "multipair massive mimo relaying systems with one bit adc s and dac s"
    - "an introduction to deep learning for the physical layer"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "detection algorithms for communication systems using deep learning"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"
    - "quantized massive mu mimo ofdm uplink"

Connected through hyperedge HE-5 (induced by source paper "slnr based precoding for one bit quantized massive mimo in mmwave communications"):
  with members:
    - "optimal multiuser loading in quantized massive mimo under spatially correlated channels"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "overview of millimeter wave communications for fifth generation 5g wireless networks with a focus on propagation models"
    - "analysis of one bit quantized precoding for the multiuser massive mimo downlink"
    - "quantized precoding for massive mu mimo"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-6 (induced by source paper "soft output detection methods for sparse millimeter wave mimo systems with low precision adcs"):
  with members:
    - "joint channel estimation decoding with frequency selective channels and few bit adcs"
    - "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"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "a supervised learning detector for multihop distributed reception systems"):
  with members:
    - "robust and efficient distributed compression for cloud radio access networks"
    - "compute and forward strategies for cooperative distributed antenna systems"
    - "wireless network information flow a deterministic approach"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-8 (induced by source paper "successive cancellation soft output detector for uplink mu mimo systems with one bit adcs"):
  with members:
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "massive mimo for next generation wireless systems"
    - "joint spatial division and multiplexing for mm wave channels"
    - "list decoding of polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

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)