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: "spatio temporal waveform design for multiuser massive mimo downlink with 1 bit receivers"
  Abstract: Internet-of-Things (IoT) refers to a high-density network of low-cost, low-bitrate terminals and sensors where low energy consumption is also one central feature. As the power budget of classical receiver chains is dominated by the high-resolution analog-to-digital converters (ADCs), there is a growing interest toward deploying receiver architectures with reduced bit or even 1-bit ADCs. In this paper, we study waveform design, optimization, and detection aspects of multiuser massive MIMO downlink, where user terminals adopt very simple 1-bit ADCs with oversampling. In order to achieve spectral efficiency higher than 1 bit/s/Hz per real dimension, and per receiver antenna, we propose a two-stage precoding structure, namely, a novel quantization precoder followed by maximum-ratio transmission or zero-forcing-type spatial channel precoder which jointly form the multiuser multiantenna transmit waveform. The quantization precoder outputs are designed and optimized, under appropriate transmitter and receiver filter bandwidth constraints, to provide controlled intersymbol interference enabling the input symbols to be uniquely detected from 1-bit quantized observations with a low-complexity symbol detector in the absence of noise. An additional optimization constraint is also imposed in the quantization precoder design to increase the robustness against noise and residual interuser interference (IUI). The purpose of the spatial channel precoder, in turn, is to suppress the IUI and provide high beamforming gains such that good symbol error rates can be achieved in the presence of noise and interference. Extensive numerical evaluations illustrate that the proposed spatio-temporal precoder-based multiantenna waveform design can facilitate good multiuser link performance, despite the extremely simple 1-bit ADCs in the receivers, hence being one possible enabling technology for the future low-complexity IoT networks.

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"
    - "one bit sphere decoding for uplink massive mimo systems with one bit adcs"
    - "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-2 (induced by source paper "bandlimited communication with one bit quantization and oversampling transceiver design and performance evaluation"):
  with members:
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "spectral efficient communications employing 1 bit quantization and oversampling at the receiver"
    - "a general framework for transmission with transceiver distortion and some applications"
    - "at low snr asymmetric quantizers are better"
    - "increased capacity per unit cost by oversampling"

Connected through hyperedge HE-3 (induced by source paper "zero crossing precoding with maximum distance to the decision threshold for channels with 1 bit quantization and oversampling"):
  with members:
    - "quantized constant envelope precoding with psk and qam signaling"
    - "branch and bound precoding for multiuser mimo systems with 1 bit quantization"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "energy and spectral efficiency of very large multiuser mimo systems"

Connected through hyperedge HE-4 (induced by source paper "optimal discrete spatial compression for beamspace massive mimo signals"):
  with members:
    - "a real time millimeter wave phased array mimo channel sounder"
    - "branch and bound precoding for multiuser mimo systems with 1 bit quantization"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "cost effective millimeter wave communications with lens antenna array"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "quantized precoding for massive mu mimo"
    - "hybrid beamforming for massive mimo a survey"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"

Connected through hyperedge HE-5 (induced by source paper "symbol level and multicast precoding for multiuser multiantenna downlink a survey classification and challenges"):
  with members:
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "an overview on resource allocation techniques for multi user mimo systems"
    - "joint beamforming and broadcasting in massive mimo"
    - "coordinate update algorithms for robust power loading for the mu miso downlink with outage constraints"
    - "energy efficient symbol level precoding in multiuser miso based on relaxed detection region"
    - "robust transmission in downlink multiuser miso systems a rate splitting approach"
    - "adaptive pilot clustering in heterogeneous massive mimo networks"
    - "a rate splitting strategy for max min fair multigroup multicasting"

Connected through hyperedge HE-6 (induced by source paper "performance analysis of mixed adc massive mimo systems over rician fading channels"):
  with members:
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "mixed adc massive mimo"
    - "mixed adc massive mimo uplink in frequency selective channels"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "distributed spatial multiplexing systems with hardware impairments and imperfect channel estimation under rank 1 rician fading channels"
    - "mixed adc massive mimo detectors performance analysis and design optimization"
    - "achievable rate of rician large scale mimo channels with transceiver hardware impairments"

Connected through hyperedge HE-7 (induced by source paper "full duplex massive mimo relaying systems with low resolution adcs"):
  with members:
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "joint source relay design for full duplex mimo af relay systems"
    - "how much training is needed in one bit massive mimo systems at low snr"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "mixed adc massive mimo"
    - "mixed adc massive mimo uplink in frequency selective channels"
    - "minimum ber precoding in 1 bit massive mimo systems"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"

Connected through hyperedge HE-8 (induced by source paper "branch and bound precoding for multiuser mimo systems with 1 bit quantization"):
  with members:
    - "minimum ber precoding in 1 bit massive mimo systems"
    - "quantized precoding for massive mu mimo"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"

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)