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: "energy efficiency maximization for c rans discrete monotonic optimization penalty and ell _ 0 approximation methods"
  Abstract: We study downlink of multiantenna cloud radio access networks with finite-capacity fronthaul links. The aim is to propose joint designs of beamforming and remote radio head (RRH)-user association, subject to constraints on users’ quality-of-service, limited capacity of fronthaul links and transmit power, to maximize the system energy efficiency. To cope with the limited-capacity fronthaul we consider the problem of RRH-user association to select a subset of users that can be served by each RRH. Moreover, different to the conventional power consumption models, we take into account the dependence of the baseband signal processing power on the data rate, as well as the dynamics of the efficiency of power amplifiers. The considered problem leads to a mixed binary integer program which is difficult to solve. Our first contribution is to derive a globally optimal solution for the considered problem by customizing a discrete branch-reduce-and-bound approach. Since the global optimization method requires a high computational effort, we further propose two suboptimal solutions able to achieve the near optimal performance but with much reduced complexity. To this end, we transform the design problem into continuous (but inherently nonconvex) programs by two approaches: penalty and   $\ell _{0}$   -approximation methods. These resulting continuous nonconvex problems are then solved by the successive convex approximation framework. Numerical results are provided to evaluate the effectiveness of the proposed approaches.

Connected through hyperedge HE-1 (induced by source paper "joint power allocation and load balancing optimization for energy efficient cell free massive mimo networks"):
  with members:
    - "scalable cell free massive mimo systems"
    - "ubiquitous cell free massive mimo communications"
    - "a speculative study on 6g"
    - "optimal design of energy efficient cell free massive mimo joint power allocation and load balancing"
    - "making cell free massive mimo competitive with mmse processing and centralized implementation"
    - "downlink spectral efficiency of cell free massive mimo with full pilot zero forcing"
    - "distributed power control in downlink cellular massive mimo systems"
    - "on the total energy efficiency of cell free massive mimo"

Connected through hyperedge HE-2 (induced by source paper "joint design of fronthauling and hybrid beamforming for downlink c ran systems"):
  with members:
    - "channel diagonalization for cloud radio access"
    - "stochastic successive convex optimization for two timescale hybrid precoding in massive mimo"
    - "hybrid analog digital beamforming for massive mimo systems"
    - "multi user precoding and channel estimation for hybrid millimeter wave systems"
    - "hybrid precoding for massive mimo systems in cloud ran architecture with capacity limited fronthauls"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "subspace estimation and decomposition for large millimeter wave mimo systems"
    - "a generalized framework on beamformer design and csi acquisition for single carrier massive mimo systems in millimeter wave channels"

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)