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: "algorithms for joint phase estimation and decoding for mimo systems in the presence of phase noise"
  Abstract: In this work, we derive the maximum a posteriori (MAP) symbol detector for a multiple-input multiple-output system in the presence of Wiener phase noise due to noisy local oscillators. As in single-antenna systems, the computation of the optimal receiver is an infinite dimensional problem and is thus unimplementable in practice. In this purview, we propose three suboptimal, low-complexity algorithms for approximately implementing the MAP symbol detector, which involve joint phase noise estimation and data detection. Our first algorithm is obtained by means of the sum-product algorithm, where we use the multivariate Tikhonov canonical distribution approach. In our next algorithm, we derive an approximate MAP symbol detector based on the smoother-detector framework, wherein the detector is properly designed by incorporating the phase noise statistics from the smoother. The third algorithm is derived based on the variational Bayesian framework. By simulations, we evaluate the performance of the proposed algorithms for both uncoded and coded data transmissions, and we observe that the proposed techniques significantly outperform the other algorithms proposed in the literature.

Connected through hyperedge HE-1 (induced by source paper "ml detection in phase noise impaired simo channels with uplink training"):
  with members:
    - "optimal detection in training assisted simo systems with phase noise impairments"
    - "capacity of simo and miso phase noise channels with common separate oscillators"
    - "uplink performance of time reversal mrc in massive mimo systems subject to phase noise"
    - "distributed massive mimo in cellular networks impact of imperfect hardware and number of oscillators"
    - "massive mimo with non ideal arbitrary arrays hardware scaling laws and circuit aware design"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "calculation of the performance of communication systems from measured oscillator phase noise"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-2 (induced by source paper "receiver algorithm based on differential signaling for simo phase noise channels with common and separate oscillator configurations"):
  with members:
    - "capacity of simo and miso phase noise channels with common separate oscillators"
    - "on the impact of oscillator phase noise on the uplink performance in a massive mimo ofdm system"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "calculation of the performance of communication systems from measured oscillator phase noise"
    - "improving bandwidth efficiency in e band communication systems"
    - "oscillator phase noise and small scale channel fading in higher frequency bands"
    - "massive mimo for next generation wireless systems"
    - "effect of synchronizing coordinated base stations on phase noise estimation"

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)