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 massive mimo precoding via a minimum symbol error probability design"
  Abstract: Massive multiple-input multiple-output (MIMO) has the potential to substantially improve the spectral efficiency, robustness and coverage of mobile networks. However, such potential is limited by hardware cost and power consumption associated with a large number of RF chains. Recently, one-bit quantization is proposed to address this issue by replacing high-resolution digital-to-analog converters (DACs) with one-bit DACs, thereby simplifying the RF chains. Despite low system cost, advanced signal processing techniques are needed to compensate for quantization distortions caused by low resolution DACs. In this paper, a symbol-error-rate (SER)-based one-bit precoding scheme is proposed to minimize the detection error probability of all users under one-bit constraints. The problem is recast as a continuous optimization problem with a biconvex objective. By applying the block coordinate descent (BCD) method and the FISTA method, we develop an efficient iterative algorithm to obtain a one-bit precoding solution. Simulation results demonstrate its superiority over state-of-the-art algorithms in terms of bit error rate performance in high-order modulation cases.

Connected through hyperedge HE-1 (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"
    - "directional frame timing synchronization in wideband millimeter wave systems with low resolution adcs"
    - "one bit sphere decoding for uplink massive mimo systems with one bit 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-2 (induced by source paper "neural network optimized 1 bit precoding for massive mu mimo"):
  with members:
    - "a deep learning framework for optimization of miso downlink beamforming"
    - "multilevel mimo detection with deep learning"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "trainable projected gradient detector for massive overloaded mimo channels data driven tuning approach"
    - "a model driven deep learning network for mimo detection"
    - "amp inspired deep networks for sparse linear inverse problems"
    - "1 bit massive mu mimo precoding in vlsi"
    - "quantized precoding for multi antenna downlink channels with magiq"

Connected through hyperedge HE-3 (induced by source paper "a framework for one bit and constant envelope precoding over multiuser massive miso channels"):
  with members:
    - "minimum symbol error rate based constant envelope precoding for multiuser massive miso downlink"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "multiuser one bit massive mimo precoding under mpsk signaling"
    - "mse optimal 1 bit precoding for multiuser mimo via branch and bound"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "accelerated gradient descent escapes saddle points faster than gradient descent"
    - "nonlinear precoding for phase quantized constant envelope massive mu mimo ofdm"
    - "massive mimo downlink 1 bit precoding with linear programming for psk signaling"

Connected through hyperedge HE-4 (induced by source paper "multiuser one bit massive mimo precoding under mpsk signaling"):
  with members:
    - "nonlinear precoding for phase quantized constant envelope massive mu mimo ofdm"
    - "massive mimo downlink 1 bit precoding with linear programming for psk signaling"
    - "quantized precoding for massive mu mimo"
    - "exploiting known interference as green signal power for downlink beamforming optimization"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "quantized massive mu mimo ofdm uplink"
    - "massive mimo with 1 bit adc"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-5 (induced by source paper "minimum symbol error rate based constant envelope precoding for multiuser massive miso downlink"):
  with members:
    - "an efficient manifold algorithm for constructive interference based constant envelope precoding"
    - "constant envelope precoding for mimo systems"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "per antenna constant envelope precoding for large multi user mimo systems"

Connected through hyperedge HE-6 (induced by source paper "linear precoding with low resolution dacs for massive mu mimo ofdm downlink"):
  with members:
    - "a framework for one bit and constant envelope precoding over multiuser massive miso channels"
    - "mse optimal 1 bit precoding for multiuser mimo via branch and bound"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "can hardware distortion correlation be neglected when analyzing uplink se in massive mimo"
    - "out of band radiation from antenna arrays clarified"
    - "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"

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)