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: "large scale fading decoding in cellular massive mimo systems with spatially correlated channels"
  Abstract: Massive multiple-input–multiple-output (MIMO) systems can suffer from coherent intercell interference due to the phenomenon of pilot contamination. This paper investigates a two-layer decoding method that mitigates both coherent and non-coherent interference in multi-cell Massive MIMO. To this end, each base station (BS) first estimates the channels to intra-cell users using either minimum mean-squared error (MMSE) or element-wise MMSE estimation based on uplink pilots. The estimates are used for local decoding on each BS followed by a second decoding layer where the BSs cooperate to mitigate inter-cell interference. An uplink achievable spectral efficiency (SE) expression is computed for arbitrary two-layer decoding schemes. A closed form expression is then obtained for correlated Rayleigh fading, maximum-ratio combining, and the proposed large-scale fading decoding (LSFD) in the second layer. We also formulate a sum SE maximization problem with both the data power and LSFD vectors as optimization variables. Since this is an NP-hard problem, we develop a low-complexity algorithm based on the weighted MMSE approach to obtain a local optimum. The numerical results show that both data power control and LSFD improve the sum SE performance over single-layer decoding multi-cell Massive MIMO systems.

Connected through hyperedge HE-1 (induced by source paper "performance of multi cell massive mimo systems with interference decoding"):
  with members:
    - "massive mimo has unlimited capacity"
    - "gaussian multiple access via compute and forward"
    - "uplink interference reduction in large scale antenna systems"
    - "joint power allocation and user association optimization for massive mimo systems"
    - "robust pilot decontamination based on joint angle and power domain discrimination"
    - "optimal achievable rates for interference networks with random codes"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-2 (induced by source paper "large scale fading precoding for maximizing the product of sinrs"):
  with members:
    - "joint user selection power allocation and precoding design with imperfect csit for multi cell mu mimo downlink systems"
    - "scalability aspects of cell free massive mimo"
    - "massive mimo with spatially correlated rician fading channels"
    - "optimized power control for massive mimo with underlaid d2d communications"
    - "performance of cell free massive mimo with rician fading and phase shifts"
    - "uplink massive mimo for channels with spatial correlation"
    - "a bilinear equalizer for massive mimo systems"
    - "massive mimo has unlimited capacity"

Connected through hyperedge HE-3 (induced by source paper "power control in cellular massive mimo with varying user activity a deep learning solution"):
  with members:
    - "sum spectral efficiency maximization in massive mimo systems benefits from deep learning"
    - "optimized power control for massive mimo with underlaid d2d communications"
    - "joint transmit and circuit power minimization in massive mimo with downlink sinr constraints when to turn on massive mimo"
    - "learning to optimize training deep neural networks for interference management"
    - "model aided wireless artificial intelligence embedding expert knowledge in deep neural networks towards wireless systems optimization"
    - "residual dense network for image super resolution"
    - "an introduction to deep learning for the physical layer"
    - "uplink interference reduction in large scale antenna systems"

Connected through hyperedge HE-4 (induced by source paper "making cell free massive mimo competitive with mmse processing and centralized implementation"):
  with members:
    - "ubiquitous cell free massive mimo communications"
    - "few bit csi acquisition for centralized cell free massive mimo with spatial correlation"
    - "can massive mimo support uplink intensive applications"
    - "on the performance of backhaul constrained cell free massive mimo with linear receivers"
    - "massive mimo has unlimited capacity"
    - "performance of cell free massive mimo systems with mmse and lsfd receivers"
    - "on the total energy efficiency of cell free massive mimo"
    - "uplink interference reduction in large scale antenna systems"

Connected through hyperedge HE-5 (induced by source paper "dynamic resource allocation in co located and cell free massive mimo"):
  with members:
    - "dynamic scheduling and power control in uplink massive mimo with random data arrivals"
    - "ubiquitous cell free massive mimo communications"
    - "making cell free massive mimo competitive with mmse processing and centralized implementation"
    - "dynamic power control for packets with deadlines"
    - "performance of cell free massive mimo systems with mmse and lsfd receivers"
    - "optimal pilot and payload power control in single cell massive mimo systems"
    - "channel hardening and favorable propagation in cell free massive mimo with stochastic geometry"
    - "ultra reliable and low latency communication in mmwave enabled massive mimo networks"

Connected through hyperedge HE-6 (induced by source paper "channel correlation diversity in mu mimo systems analysis and measurements"):
  with members:
    - "two layer decoding in cellular massive mimo systems with spatial channel correlation"
    - "uplink massive mimo for channels with spatial correlation"
    - "capacity scaling of massive mimo in strong spatial correlation regimes"
    - "massive mimo has unlimited capacity"
    - "massive mimo performance evaluation based on measured propagation data"
    - "on the matrix inversion approximation based on neumann series in massive mimo systems"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "linear precoding based on polynomial expansion large scale multi cell mimo systems"

Connected through hyperedge HE-7 (induced by source paper "average sep optimal precoding for correlated massive mimo with zf detection an asymptotic analysis"):
  with members:
    - "massive mimo has unlimited capacity"
    - "performance analysis for massive mimo downlink with low complexity approximate zero forcing precoding"
    - "joint pilot design and uplink power allocation in multi cell massive mimo systems"
    - "the world s first real time testbed for massive mimo design implementation and validation"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "pilot beam pattern design for channel estimation in massive mimo systems"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-8 (induced by source paper "sum spectral efficiency maximization in massive mimo systems benefits from deep learning"):
  with members:
    - "learning to optimize training deep neural networks for interference management"
    - "model aided wireless artificial intelligence embedding expert knowledge in deep neural networks towards wireless systems optimization"
    - "residual dense network for image super resolution"
    - "optimal pilot and payload power control in single cell massive mimo systems"
    - "densely connected convolutional networks"
    - "deep residual learning for image recognition"
    - "adam a method for stochastic optimization"
    - "matconvnet convolutional neural networks for matlab"

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)