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: "spectral efficiency of mixed adc receivers for massive mimo systems"
  Abstract: This paper investigated the uplink of multi-user massive multi-input multi-output (MIMO) systems with a mixed analog-to-digital converter (ADC) receiver architecture, in which some antennas are equipped with costly full-resolution ADCs and others with less expensive low-resolution ADCs. A closed-form approximation of the achievable spectral efficiency (SE) with the maximum-ratio combining (MRC) detector is derived. Based on this approximated result, the effects of the number of base station antennas, the transmit power, the proportion of full-resolution ADCs in the mixed-ADC structure, and the number of quantization bits of the low-resolution ADCs are revealed. Results showcase that the achievable SE increases with the number of BS antennas and quantization bits, and it converges to a saturated value in the high user power regime or the full ADC resolution case. Most important, this work efficiency verifies that for massive MIMO, the mixed-ADC receiver with a small fraction of full-resolution ADCs can have comparable SE performance with the receiver with all full-resolution ADCs but at a considerably lower hardware cost.

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 "spectral efficiency of mixed adc massive mimo"):
  with members:
    - "a comparison of hybrid beamforming and digital beamforming with low resolution adcs for multiple users and imperfect csi"
    - "spatial characteristics of distortion radiated from antenna arrays with transceiver nonlinearities"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "impact of spatial filtering on distortion from low noise amplifiers in massive mimo base stations"
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "mixed adc massive mimo"

Connected through hyperedge HE-3 (induced by source paper "mixed adc dac multipair massive mimo relaying systems performance analysis and power optimization"):
  with members:
    - "all technologies work together for good a glance to future mobile networks"
    - "on low resolution adcs in practical 5g millimeter wave massive mimo systems"
    - "spectral efficiency of mixed adc massive mimo"
    - "multipair massive mimo relaying systems with one bit adc s and dac s"
    - "on performance of quantized transceiver in multiuser massive mimo downlinks"
    - "the distributed mimo scenario can ideal adcs be replaced by low resolution adcs"
    - "spectral efficiency of multipair massive mimo two way relaying with hardware impairments"
    - "channel estimation and performance analysis of one bit massive mimo systems"

Connected through hyperedge HE-4 (induced by source paper "multipair massive mimo relaying systems with one bit adc s and dac s"):
  with members:
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "achievable uplink rates for massive mimo with coarse quantization"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "downlink achievable rate analysis in massive mimo systems with one bit dacs"
    - "adc bit allocation under a power constraint for mmwave massive mimo communication receivers"
    - "mixed adc massive mimo uplink in frequency selective channels"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"

Connected through hyperedge HE-5 (induced by source paper "deep learning for wireless physical layer opportunities and challenges"):
  with members:
    - "deep learning methods for improved decoding of linear codes"
    - "learning the mmse channel estimator"
    - "an introduction to deep learning for the physical layer"
    - "scaling deep learning based decoding of polar codes via partitioning"
    - "rnn decoding of linear block codes"
    - "detection algorithms for communication systems using deep learning"
    - "deep learning based mimo communications"
    - "power of deep learning for channel estimation and signal detection in ofdm systems"

Connected through hyperedge HE-6 (induced by source paper "low complexity and high resolution doa estimation for hybrid analog and digital massive mimo receive array"):
  with members:
    - "robust secure transmission of using main lobe integration based leakage beamforming in directional modulation mu mimo systems"
    - "a survey of multi objective optimization in wireless sensor networks metrics algorithms and open problems"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "energy efficient uav communication with trajectory optimization"
    - "artificial noise aided secure transmission with directional modulation based on random frequency diverse arrays"
    - "directional modulation via symbol level precoding a way to enhance security"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "spatially sparse precoding in millimeter wave mimo systems"

Connected through hyperedge HE-7 (induced by source paper "approximate random matrix models for generalized fading mimo channels"):
  with members:
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "massive mimo ten myths and one critical question"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "secrecy capacity analysis over kappa mu fading channels theory and applications"
    - "on some unifications arising from the mimo rician shadowed model"

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)