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: "mixed adc dac multipair massive mimo relaying systems performance analysis and power optimization"
  Abstract: High power consumption and expensive hardware are two bottlenecks for practical massive multiple-input multiple-output (mMIMO) systems. One promising solution is to employ low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). In this paper, we consider a general multipair mMIMO relaying system with a mixed-ADC/DAC architecture, in which some antennas are connected to low-resolution ADCs/DACs, while the rest of the antennas are connected to high-resolution ADCs/DACs. Leveraging on the additive quantization noise model, both exact and approximate closed-form expressions for the achievable rate are derived. It is shown that the achievable rate can approach the unquantized one by using only 2-3 bits of resolutions. Moreover, a power scaling law is presented to reveal that the transmit power can be scaled down inversely proportional to the number of antennas at the relay. We further propose an efficient power allocation scheme by solving a complementary geometric programming problem. In addition, a trade-off between the achievable rate and power consumption for different numbers of low-resolution ADCs/DACs is investigated by deriving the energy efficiency. Our results reveal that the large antenna array can be exploited to enable the mixed-ADC/DAC architecture, which significantly reduces the power consumption and hardware cost for practical mMIMO systems.

Connected through hyperedge HE-1 (induced by source paper "multiple antenna technologies for beyond 5g"):
  with members:
    - "intelligent reflecting surface versus decode and forward how large surfaces are needed to beat relaying"
    - "robust trajectory and resource allocation design for secure uav aided communications"
    - "a new look at cell free massive mimo making it practical with dynamic cooperation"
    - "scalability aspects of cell free massive mimo"
    - "cascaded channel estimation for large intelligent metasurface assisted massive mimo"
    - "robust and secure wireless communications via intelligent reflecting surfaces"
    - "channel estimation for intelligent reflecting surface assisted multiuser communications framework algorithms and analysis"
    - "resource allocation for secure irs assisted multiuser miso systems"

Connected through hyperedge HE-2 (induced by source paper "energy efficient resource allocation for secure uav communication systems"):
  with members:
    - "power efficient deployment of uavs as relays"
    - "secrecy energy efficiency maximization for uav enabled mobile relaying"
    - "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"
    - "securing uav communications via joint trajectory and power control"
    - "energy minimization for wireless communication with rotary wing uav"
    - "a multi beam noma framework for hybrid mmwave systems"
    - "robust trajectory and transmit power design for secure uav communications"
    - "joint trajectory and resource allocation design for uav communication systems"

Connected through hyperedge HE-3 (induced by source paper "optimal multiuser loading in quantized massive mimo under spatially correlated channels"):
  with members:
    - "on performance of quantized transceiver in multiuser massive mimo downlinks"
    - "massive mimo downlink 1 bit precoding with linear programming for psk signaling"
    - "analysis of one bit quantized precoding for the multiuser massive mimo downlink"
    - "downlink achievable rate analysis in massive mimo systems with one bit dacs"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "quantized precoding for massive mu mimo"
    - "massive mimo for next generation wireless systems"
    - "massive mimo with 1 bit adc"

Connected through hyperedge HE-4 (induced by source paper "deep learning based channel estimation for massive mimo with mixed resolution adcs"):
  with members:
    - "hybrid precoding based millimeter wave massive mimo noma with simultaneous wireless information and power transfer"
    - "on low resolution adcs in practical 5g millimeter wave massive mimo systems"
    - "deep learning in physical layer communications"
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "power of deep learning for channel estimation and signal detection in ofdm systems"
    - "mixed adc massive mimo"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"
    - "uplink achievable rate for massive mimo systems with low resolution adc"

Connected through hyperedge HE-5 (induced by source paper "on the distribution of the ratio of products of fisher snedecor mathcal f random variables and its applications"):
  with members:
    - "multiple antenna technologies for beyond 5g"
    - "the alpha kappa mu shadowed fading distribution statistical characterization and applications"
    - "on the multivariate gamma gamma distribution with arbitrary correlation and applications in wireless communications"
    - "approximation to distribution of product of random variables using orthogonal polynomials for lognormal density"

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)