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 iterative lmmse detection for mimo noma systems"
  Abstract: This paper considers a iterative Linear Minimum Mean Square Error (LMMSE) detection for the uplink Multiuser Multiple-Input and Multiple-Output (MU-MIMO) systems with Non-Orthogonal Multiple Access (NOMA). The iterative LMMSE detection greatly reduces the system computational complexity by departing the overall processing into many low-complexity distributed calculations. However, it is generally considered to be sub-optimal and achieves relatively poor performance. In this paper, we firstly present the matching conditions and area theorems for the iterative detection of the MIMO-NOMA systems. Based on the proposed matching conditions and area theorems, the achievable rate region of the iterative LMMSE detection is analysed. We prove that by properly design the iterative LMMSE detection, it can achieve (i) the optimal sum capacity of MU-MIMO systems, (ii) all the maximal extreme points in the capacity region of MU-MIMO system, and (iii) the whole capacity region of two-user MIMO systems.

Connected through hyperedge HE-1 (induced by source paper "near capacity detection and decoding code design for dynamic user loads in gaussian multiple access channels"):
  with members:
    - "spatially coupled ldpc codes and the multiple access channel"
    - "wave like decoding of tail biting spatially coupled ldpc codes through iterative demapping"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-2 (induced by source paper "achievable rate region for iterative multi user detection via low cost gaussian approximation"):
  with members:
    - "near gaussian multiple access channel capacity detection and decoding"
    - "achievable rates of mimo systems with linear precoding and iterative lmmse detection"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-3 (induced by source paper "non orthogonal multiple access for 5g and beyond"):
  with members:
    - "downlink non orthogonal multiple access with limited feedback"
    - "optimal user scheduling and power allocation for millimeter wave noma systems"
    - "coordinated multi point comp transmission in downlink multi cell noma systems models and spectral efficiency performance"
    - "low complexity receiver for multi level polar coded modulation in non orthogonal multiple access"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "modulation and multiple access for 5g networks"
    - "robust beamforming techniques for non orthogonal multiple access systems with bounded channel uncertainties"

Connected through hyperedge HE-4 (induced by source paper "probabilistic mimo symbol detection with expectation consistency approximate inference"):
  with members:
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "spatially coupled ldpc codes constructed from protographs"
    - "optimality of large mimo detection via approximate message passing"
    - "fifty years of mimo detection the road to large scale mimos"
    - "spatially coupled sparse codes on graphs theory and practice"
    - "channel hardening exploiting message passing chemp receiver in large scale mimo systems"
    - "expectation propagation for approximate bayesian inference"

Connected through hyperedge HE-5 (induced by source paper "gaussian message passing for overloaded massive mimo noma"):
  with members:
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "mu mimo mac protocols for wireless local area networks a survey"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "adaptive damping and mean removal for the generalized approximate message passing algorithm"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "s amp for non linear observation models"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "energy efficient sensing and communication of parallel gaussian sources"

Connected through hyperedge HE-6 (induced by source paper "on the performance of noma based cooperative relaying systems over rician fading channels"):
  with members:
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "cooperative non orthogonal multiple access with simultaneous wireless information and power transfer"
    - "on the capacity of decode and forward relaying over rician fading channels"
    - "five disruptive technology directions for 5g"

Connected through hyperedge HE-7 (induced by source paper "gaussian message passing iterative detection for mimo noma systems with massive access"):
  with members:
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "achievable rates of mimo systems with linear precoding and iterative lmmse detection"
    - "belief propagation based multi user detection"

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)