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: "fractional programming for communication systems part ii uplink scheduling via matching"
  Abstract: This two-part paper develops novel methodologies for using fractional programming (FP) techniques to design and optimize communication systems. Part I of this paper proposes a new quadratic transform for FP and treats its application for continuous optimization problems. In this Part II of the paper, we study discrete problems, such as those involving user scheduling, which are considerably more difficult to solve. Unlike the continuous problems, discrete or mixed discrete-continuous problems normally cannot be recast as convex problems. In contrast to the common heuristic of relaxing the discrete variables, this work reformulates the original problem in an FP form amenable to distributed combinatorial optimization. The paper illustrates this methodology by tackling the important and challenging problem of uplink coordinated multicell user scheduling in wireless cellular systems. Uplink scheduling is more challenging than downlink scheduling, because uplink user scheduling decisions significantly affect the interference pattern in nearby cells. Furthermore, the discrete scheduling variable needs to be optimized jointly with continuous variables such as transmit power levels and beamformers. The main idea of the proposed FP approach is to decouple the interaction among the interfering links, thereby permitting a distributed and joint optimization of the discrete and continuous variables with provable convergence. The paper shows that the well-known weighted minimum mean-square-error (WMMSE) algorithm can also be derived from a particular use of FP; but our proposed FP-based method significantly outperforms WMMSE when discrete user scheduling variables are involved, both in term of run-time efficiency and optimizing results.

Connected through hyperedge HE-1 (induced by source paper "joint sparse beamforming and power control for large scale das with network assistant full duplex"):
  with members:
    - "performance of network assisted full duplex for cell free massive mimo"
    - "cross layer design for downlink multihop cloud radio access networks with network coding"
    - "analysis of massive mimo enabled downlink wireless backhauling for full duplex small cells"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "d2d enhanced heterogeneous cellular networks with dynamic tdd"
    - "compflex comp for in band wireless full duplex"
    - "on the spectral efficiency of full duplex small cell wireless systems"
    - "sparse beamforming and user centric clustering for downlink cloud radio access network"

Connected through hyperedge HE-2 (induced by source paper "joint beamforming design in multi cluster miso noma intelligent reflecting surface aided downlink communication networks"):
  with members:
    - "miso wireless communication systems via intelligent reflecting surfaces"
    - "secure wireless communication via intelligent reflecting surface"
    - "intelligent reflecting surface assisted non orthogonal multiple access"
    - "a simple design of irs noma transmission"
    - "enabling large intelligent surfaces with compressive sensing and deep learning"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "reconfigurable intelligent surfaces for energy efficiency in wireless communication"
    - "fairness for non orthogonal multiple access in 5g systems"

Connected through hyperedge HE-3 (induced by source paper "mixed timescale beamforming and power splitting for massive mimo aided swipt iot network"):
  with members:
    - "two timescale hybrid compression and forward for massive mimo aided c ran"
    - "on the ergodic rate lower bounds with applications to massive mimo"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"
    - "joint transmit beamforming and receive power splitting for miso swipt systems"
    - "mimo broadcasting for simultaneous wireless information and power transfer"

Connected through hyperedge HE-4 (induced by source paper "optimization of mimo device to device networks via matrix fractional programming a minorization maximization approach"):
  with members:
    - "a centralized metropolitan scale radio resource management scheme"
    - "fractional programming for communication systems part i power control and beamforming"
    - "optimality of treating interference as noise a combinatorial perspective"
    - "fast resource scheduling in hetnets with d2d support"
    - "traffic driven spectrum allocation in heterogeneous networks"
    - "distributed algorithms for spectrum allocation power control routing and congestion control in wireless networks"

Connected through hyperedge HE-5 (induced by source paper "coordinated scheduling and spectrum sharing via matrix fractional programming"):
  with members:
    - "a centralized metropolitan scale radio resource management scheme"
    - "fractional programming for communication systems part i power control and beamforming"
    - "optimality of treating interference as noise a combinatorial perspective"
    - "fast resource scheduling in hetnets with d2d support"
    - "distributed algorithms for spectrum allocation power control routing and congestion control in wireless networks"

Connected through hyperedge HE-6 (induced by source paper "fractional programming for communication systems part i power control and beamforming"):
  with members:
    - "energy efficient power control a look at 5g wireless technologies"
    - "achieving maximum energy efficiency in multi relay ofdma cellular networks a fractional programming approach"
    - "framework for link level energy efficiency optimization with informed transmitter"

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)