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: "a mixed adc receiver architecture for massive mimo systems"
  Abstract: Motivated by the demand for energy-efficient communication solutions in the next generation cellular network, a mixed-ADC receiver architecture for massive multiple input multiple output (MIMO) systems is proposed, which differs from previous works in that herein one-bit analog-to-digital converters (ADCs) partially replace the conventionally assumed high-resolution ADCs. The information-theoretic tool of generalized mutual information (GMI) is exploited to analyze the achievable data rates of the proposed system architecture and an array of analytical results of engineering interest are obtained. For deterministic single input multiple output (SIMO) channels, a closed-form expression of the GMI is derived, based on which the linear combiner is optimized. Then, the asymptotic behaviors of the GMI in both low and high SNR regimes are explored, and the analytical results suggest a plausible ADC assignment scheme. Finally, the analytical framework is applied to the multi-user access scenario, and the corresponding numerical results demonstrate that the mixed system architecture with a relatively small number of high-resolution ADCs is able to achieve a large fraction of the channel capacity without output quantization.

Connected through hyperedge HE-1 (induced by source paper "mixed adc massive mimo uplink in frequency selective channels"):
  with members:
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "massive mimo with low resolution adcs"
    - "mixed adc massive mimo"
    - "mixed adc massive mimo detectors performance analysis and design optimization"
    - "one bit massive mimo channel estimation and high order modulations"
    - "asymptotic analysis of su mimo channels with transmitter noise and mismatched joint decoding"

Connected through hyperedge HE-2 (induced by source paper "analysis of one bit quantized precoding for the multiuser massive mimo downlink"):
  with members:
    - "nonlinear 1 bit precoding for massive mu mimo with higher order modulation"
    - "mixed adc massive mimo"
    - "minimum ber precoding in 1 bit massive mimo systems"
    - "channel estimation and uplink achievable rates in one bit massive mimo systems"
    - "quantized precoding for massive mu mimo"
    - "mmse precoder for massive mimo using 1 bit quantization"
    - "one bit massive mimo channel estimation and high order modulations"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"

Connected through hyperedge HE-3 (induced by source paper "spectral efficiency of mixed adc receivers for massive mimo systems"):
  with members:
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "mixed adc massive mimo detectors performance analysis and design optimization"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "a general framework for transmission with transceiver distortion and some applications"

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)