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: "distributed optimization for coordinated beamforming in multicell multigroup multicast systems power minimization and sinr balancing"
  Abstract: This paper considers coordinated multicast beamforming in a multicell multigroup multiple-input single-output system. Each base station (BS) serves multiple groups of users by forming a single beam with common information per group. We propose centralized and distributed beamforming algorithms for two different optimization targets. The first objective is to minimize the total transmission power of all the BSs while guaranteeing the user-specific minimum quality-of-service targets. The semidefinite relaxation (SDR) method is used to approximate the nonconvex multicast problem as a semidefinite program (SDP), which is solvable via centralized processing. Subsequently, two alternative distributed methods are proposed. The first approach turns the SDP into a two-level optimization via primal decomposition. At the higher level, intercell interference powers are optimized for fixed beamformers, whereas the lower level locally optimizes the beamformers by minimizing BS-specific transmit powers for the given intercell interference constraints. The second distributed solution is enabled via an alternating direction method of multipliers, where the intercell interference optimization is divided into a local and a global optimization by forcing the equality via consistency constraints. We further propose a centralized and a simple distributed beamforming design for the signal-to-interference-plus-noise ratio (SINR) balancing problem in which the minimum SINR among the users is maximized with given per-BS power constraints. This problem is solved via the bisection method as a series of SDP feasibility problems. The simulation results show the superiority of the proposed coordinated beamforming algorithms over traditional noncoordinated transmission schemes, and illustrate the fast convergence of the distributed methods.

Connected through hyperedge HE-1 (induced by source paper "cloud edge coordinated processing low latency multicasting transmission"):
  with members:
    - "hybrid precoder design for cache enabled millimeter wave radio access networks"
    - "two level transmission scheme for cache enabled fog radio access networks"
    - "iteratively linearized reweighted alternating direction method of multipliers for a class of nonconvex problems"
    - "content placement in cache enabled sub 6 ghz and millimeter wave multi antenna dense small cell networks"
    - "air ground integrated vehicular network slicing with content pushing and caching"
    - "fog aided wireless networks for content delivery fundamental latency tradeoffs"
    - "random caching based cooperative transmission in heterogeneous wireless networks"
    - "cache enabled physical layer security for video streaming in backhaul limited cellular networks"

Connected through hyperedge HE-2 (induced by source paper "non orthogonal unicast and broadcast transmission via joint beamforming and ldm in cellular networks"):
  with members:
    - "rate splitting for multi antenna non orthogonal unicast and multicast transmission spectral and energy efficiency analysis"
    - "joint beamforming and broadcasting in massive mimo"
    - "admm based fast algorithm for multi group multicast beamforming in large scale wireless systems"
    - "celltv on the benefit of tv distribution over cellular networks a case study"
    - "coordinated multicast beamforming in multicell networks"
    - "distributed robust multicell coordinated beamforming with imperfect csi an admm approach"
    - "robust linear precoder design for multi cell downlink transmission"

Connected through hyperedge HE-3 (induced by source paper "two level transmission scheme for cache enabled fog radio access networks"):
  with members:
    - "fog aided wireless networks for content delivery fundamental latency tradeoffs"
    - "cache enabled physical layer security for video streaming in backhaul limited cellular networks"
    - "fronthaul compression and precoding design for c rans over ergodic fading channels"
    - "distributed optimization of hierarchical small cell networks a gnep framework"
    - "collaborative mobile edge computing in 5g networks new paradigms scenarios and challenges"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "massive mimo ten myths and one critical question"

Connected through hyperedge HE-4 (induced by source paper "efficient global optimal resource allocation in non orthogonal interference networks"):
  with members:
    - "optimization of weighted individual energy efficiencies in interference networks"
    - "energy efficient beam coordination strategies with rate dependent processing power"
    - "energy efficient power control a look at 5g wireless technologies"
    - "optimal achievable rates for interference networks with random codes"
    - "resource allocation for energy efficient 3 way relay channels"
    - "instantaneous relaying for the 3 way relay channel with circular message exchanges"
    - "wireless information and power transfer energy efficiency optimization in ofdma systems"
    - "robust monotonic optimization framework for multicell miso systems"

Connected through hyperedge HE-5 (induced by source paper "energy efficient multicell multigroup multicasting with joint beamforming and antenna selection"):
  with members:
    - "energy efficient joint unicast and multicast beamforming with multi antenna user terminals"
    - "energy efficient beam coordination strategies with rate dependent processing power"
    - "conic quadratic formulations for wireless communications design"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "multicast multigroup precoding and user scheduling for frame based satellite communications"
    - "weighted fair multicast multigroup beamforming under per antenna power constraints"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"
    - "coordinated multicast beamforming in multicell networks"

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)