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: "joint optimization of power and data transfer in multiuser mimo systems"
  Abstract: We present an approach to solve the nonconvex optimization problem that arises when designing the transmit covariance matrices in multiuser multiple-input multiple-output (MIMO) broadcast networks implementing simultaneous wireless information and power transfer (SWIPT). The MIMO SWIPT problem is formulated as a general multi-objective optimization problem, in which data rates and harvested powers are optimized simultaneously. Two different approaches are applied to reformulate the (nonconvex) multi-objective problem. In the first approach, the transmitter can control the specific amount of power to be harvested by power transfer whereas in the second approach the transmitter can only control the proportion of power to be harvested among the different harvesting users. The computational complexity will also be different, with higher computational resources required in the first approach. In order to solve the resulting formulations, we propose to use the majorization-minimization (MM) approach. The idea behind this approach is to obtain a convex function that approximates the nonconvex objective and, then, solve a series of convex subproblems that will converge to a locally optimal solution of the general nonconvex multi-objective problem. The solution obtained from the MM approach is compared to the classical block-diagonalization (BD) strategy, typically used to solve the nonconvex multiuser MIMO network by forcing no interference among users. Simulation results show that the proposed approach improves over the BD approach both the system sum rate and the power harvested by users. Additionally, the computational times needed for convergence of the proposed methods are much lower than the ones required for classical gradient-based approaches.

Connected through hyperedge HE-1 (induced by source paper "optimal precoder designs for sum utility maximization in swipt enabled multi user mimo cognitive radio networks"):
  with members:
    - "wireless powered communication opportunities and challenges"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"
    - "throughput optimization for massive mimo systems powered by wireless energy transfer"
    - "mimo broadcasting for simultaneous wireless information and power transfer weighted mmse approaches"
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "multiuser miso beamforming for simultaneous wireless information and power transfer"
    - "mimo broadcasting for simultaneous wireless information and power transfer"
    - "dynamic resource allocation in cognitive radio networks"

Connected through hyperedge HE-2 (induced by source paper "robust energy efficient beamforming in misome swipt systems with proportional secrecy rate"):
  with members:
    - "robust secrecy energy efficient beamforming in misome swipt systems with proportional fairness"
    - "rf based energy harvesting in decode and forward relaying systems ergodic and outage capacities"
    - "secure beamforming in full duplex swipt systems with loopback self interference cancellation"
    - "large scale multiantenna multisine wireless power transfer"
    - "dynamic cross layer beamforming in hybrid powered communication systems with harvest use trade strategy"
    - "robust resource allocation for mimo wireless powered communication networks based on a non linear eh model"
    - "network densification in 5g from the short range communications perspective"
    - "wireless information and power transfer nonlinearity waveform design and rate energy tradeoff"

Connected through hyperedge HE-3 (induced by source paper "decentralized robust transceiver designs for miso swipt interference channel"):
  with members:
    - "reel bf design achieving the sdp bound for downlink beamforming with arbitrary shaping constraints"
    - "robust transceiver design for miso interference channel with energy harvesting"
    - "communications and signals design for wireless power transmission"
    - "joint transceiver design algorithms for multiuser miso relay systems with energy harvesting"
    - "energy harvesting wireless communications a review of recent advances"
    - "robust beamforming for secure communication in systems with wireless information and power transfer"
    - "simultaneous wireless information and power transfer in modern communication systems"
    - "wireless networks with rf energy harvesting a contemporary survey"

Connected through hyperedge HE-4 (induced by source paper "jointly optimal spatial channel assignment and power allocation for mimo swipt systems"):
  with members:
    - "harvested power maximization in qos constrained mimo swipt with generic rf harvesting model"
    - "joint antenna selection and spatial switching for energy efficient mimo swipt system"
    - "hybrid beamforming for massive mimo a survey"
    - "spatial domain simultaneous information and power transfer for mimo channels"
    - "simultaneous wireless information and power transfer in modern communication systems"
    - "mimo broadcasting for simultaneous wireless information and power transfer"

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)