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: "capacity achieving mimo noma iterative lmmse detection"
  Abstract: This paper considers a low-complexity iterative  linear minimum mean square error  (LMMSE) multiuser detector for the  multiple-input and multiple-output  system with  nonorthogonal multiple access  (MIMO-NOMA), where multiple single-antenna users simultaneously communicate with a multiple-antenna base station (BS). While LMMSE being a linear detector has a low complexity, it has suboptimal performance in multiuser detection scenario due to the mismatch between LMMSE detection and multiuser decoding. Therefore, in this paper, we provide the matching conditions between the detector and decoders for MIMO-NOMA, which are then used to derive the achievable rate of the iterative detection. We prove that a matched iterative LMMSE detector can achieve the optimal capacity of symmetric MIMO-NOMA with any number of users, the optimal sum capacity of asymmetric MIMO-NOMA with any number of users, all the maximal extreme points in the capacity region of asymmetric MIMO-NOMA with any number of users, and all points in the capacity region of two-user and three-user asymmetric MIMO-NOMA systems. In addition, a kind of practical low-complexity error-correcting multiuser code, called irregular repeat-accumulate code, is designed to match the LMMSE detector. Numerical results shows that the bit error rate performance of the proposed iterative LMMSE detection outperforms the state-of-art methods and is within 0.8 dB from the associated capacity limit.

Connected through hyperedge HE-1 (induced by source paper "capacity optimality of amp in coded systems"):
  with members:
    - "a unified framework of state evolution for message passing algorithms"
    - "optimal data detection in large mimo"
    - "near gaussian multiple access channel capacity detection and decoding"
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "mutual information and optimality of approximate message passing in random linear estimation"
    - "compressive phase retrieval via generalized approximate message passing"
    - "compressed sensing via universal denoising and approximate message passing"

Connected through hyperedge HE-2 (induced by source paper "a new insight into gamp and amp"):
  with members:
    - "capacity optimality of amp in coded systems"
    - "a unified bayesian inference framework for generalized linear models"
    - "bilinear adaptive generalized vector approximate message passing"
    - "gaussian message passing for overloaded massive mimo noma"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "beam on graph simultaneous channel estimation for mmwave mimo systems with multiple users"
    - "rigorous dynamics of expectation propagation based signal recovery from unitarily invariant measurements"
    - "hybrid approximate message passing"

Connected through hyperedge HE-3 (induced by source paper "codebook based max min energy efficient resource allocation for uplink mmwave mimo noma systems"):
  with members:
    - "energy efficient power allocation in uplink mmwave massive mimo with noma"
    - "rate splitting multiple access for downlink communication systems bridging generalizing and outperforming sdma and noma"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "non orthogonal multiple access in large scale heterogeneous networks"
    - "energy efficient power allocation in millimeter wave massive mimo with non orthogonal multiple access"
    - "resource allocation for downlink noma systems key techniques and open issues"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"
    - "an overview of signal processing techniques for millimeter wave mimo systems"

Connected through hyperedge HE-4 (induced by source paper "a survey of noma current status and open research challenges"):
  with members:
    - "noma an information theoretic perspective"
    - "fast harq over finite blocklength codes a technique for low latency reliable communication"
    - "on the performance of noma with hybrid arq"
    - "cooperative harq assisted noma scheme in large scale d2d networks"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "dynamic user clustering and power allocation for uplink and downlink non orthogonal multiple access noma systems"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "on block coherence of frames"

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)