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: "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
  Abstract: In this paper, we study the optimal secondary-link beamforming pattern that balances between the SU's throughput and the interference it causes to PUs in MIMO cognitive radio networks. In particular, we aim to maximize the throughput of the SU, while keeping the interference temperature at the primary receivers below a certain threshold. #R##N#Unlike traditional MIMO systems, SUs may not have the luxury of knowing the channel state information (CSI) on the links to PUs. This presents a key challenge for a secondary transmitter to steer interference away from primary receivers. In this paper, we consider three scenarios, namely when the secondary transmitter has complete, partial, or no knowledge about the channels to the primary receivers. In particular, when complete CSI is not available, the interference-temperature constraints are to be satisfied with high probability, thus resulting in chance constraints that are typically hard to deal with. Our contribution is fourfold. First, by analyzing the distributional characteristics of MIMO channels, we propose a unified homogeneous QCQP formulation that can be applied to all three scenarios. The homogeneous QCQP formulation, though non-convex, is amenable to semidefinite programming (SDP) relaxation methods. Secondly, we show that the SDP relaxation admits no gap when the number of primary links is no larger than two. Thirdly, we propose a randomized polynomial-time algorithm for constructing a near-optimal solution to the QCQP problem when there are more than two primary links. Finally, we show that when the secondary transmitter has no CSI on the links to primary receivers, the optimal solution to the QCQP problem can be found by a simple matrix eigenvalue-eigenvector computation, which can be done much more efficiently than solving the QCQP directly.

Connected through hyperedge HE-1 (induced by source paper "algorithm hardware co optimization of the memristor based framework for solving socp and homogeneous qcqp problems"):
  with members:
    - "large scale convex optimization for dense wireless cooperative networks"

Connected through hyperedge HE-2 (induced by source paper "reel bf design achieving the sdp bound for downlink beamforming with arbitrary shaping constraints"):
  with members:
    - "rank two beamforming and power allocation in multicasting relay networks"
    - "general rank multiuser downlink beamforming with shaping constraints using real valued ostbc"
    - "optimal multiuser transmit beamforming a difficult problem with a simple solution structure"
    - "multiuser miso beamforming for simultaneous wireless information and power transfer"
    - "physical layer multicasting by stochastic transmit beamforming and alamouti space time coding"
    - "spatially selective artificial noise aided transmit optimization for miso multi eves secrecy rate maximization"
    - "throughput maximization for the gaussian relay channel with energy harvesting constraints"
    - "outage constrained robust transmit optimization for multiuser miso downlinks tractable approximations by conic optimization"

Connected through hyperedge HE-3 (induced by source paper "a memristor based optimization framework for ai applications"):
  with members:
    - "algorithm hardware co optimization of the memristor based framework for solving socp and homogeneous qcqp problems"
    - "group scissor scaling neuromorphic computing design to large neural networks"
    - "a survey of neuromorphic computing and neural networks in hardware"
    - "training a probabilistic graphical model with resistive switching electronic synapses"
    - "optimization with sparsity inducing penalties"
    - "subspace pursuit for compressive sensing signal reconstruction"

Connected through hyperedge HE-4 (induced by source paper "distributed energy efficient cross layer optimization for multihop mimo cognitive radio networks with primary user rate protection"):
  with members:
    - "database assisted distributed spectrum sharing"
    - "outage constrained robust transmit optimization for multiuser miso downlinks tractable approximations by conic optimization"
    - "dynamic resource allocation in cognitive radio networks"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"
    - "cognitive mimo radio"

Connected through hyperedge HE-5 (induced by source paper "semidefinite relaxation and approximation analysis of a beamformed alamouti scheme for relay beamforming networks"):
  with members:
    - "some proof derivations and further simulation results for semidefinite relaxation and approximation analysis of a beamformed alamouti scheme for relay beamforming networks"
    - "rank two beamforming and power allocation in multicasting relay networks"
    - "multicast multigroup beamforming for per antenna power constrained large scale arrays"
    - "a stochastic beamformed amplify and forward scheme in a multigroup multicast mimo relay network with per antenna power constraints"
    - "physical layer multicasting by stochastic transmit beamforming and alamouti space time coding"
    - "group sparse beamforming for green cloud ran"
    - "mimo broadcasting for simultaneous wireless information and power transfer"

Connected through hyperedge HE-6 (induced by source paper "fifty years of mimo detection the road to large scale mimos"):
  with members:
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "an esprit based approach for 2 d localization of incoherently distributed sources in massive mimo systems"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "approximate bayesian probabilistic data association aided iterative detection for mimo systems using arbitrary m ary modulation"
    - "channel hardening exploiting message passing chemp receiver in large scale mimo systems"
    - "five disruptive technology directions for 5g"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-7 (induced by source paper "generic multiuser coordinated beamforming for underlay spectrum sharing"):
  with members:
    - "decomposition by partial linearization parallel optimization of multi agent systems"
    - "transmit designs for the mimo broadcast channel with statistical csi"
    - "achieving global optimality for weighted sum rate maximization in the k user gaussian interference channel with multiple antennas"
    - "mimo broadcasting for simultaneous wireless information and power transfer"
    - "on gaussian mimo bc mac duality with multiple transmit covariance constraints"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"

Connected through hyperedge HE-8 (induced by source paper "general rank multiuser downlink beamforming with shaping constraints using real valued ostbc"):
  with members:
    - "physical layer multicasting by stochastic transmit beamforming and alamouti space time coding"
    - "cognitive beamforming for multiple secondary data streams with individual snr constraints"
    - "optimal energy allocation for wireless communications with energy harvesting constraints"
    - "femtocell networks a survey"

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.NI(Networking and Internet Architecture)