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 efficient sensing and communication of parallel gaussian sources"
  Abstract: Energy efficiency is a key requirement in the design of wireless sensor networks. While most theoretical studies only account for the energy requirements of communication, the sensing process, which includes measurements and compression, can also consume comparable energy. In this paper, the problem of sensing and communicating parallel sources is studied by accounting for the cost of both communication and sensing. In the first formulation of the problem, the sensor has a separate energy budget for sensing and a rate budget for communication, while, in the second, it has a single energy budget for both tasks. Assuming that sources with larger variances have lower sensing costs, the optimal allocation of sensing energy and rate that minimizes the overall distortion is derived for the first problem. Moreover, structural results on the solution of the second problem are derived under the assumption that the sources with larger variances are transmitted on channels with lower noise. Closed-form solutions are also obtained for the case where the energy budget is sufficiently large. For an arbitrary order on the variances and costs, the optimal solution to the first problem is also obtained numerically and compared with several suboptimal strategies.

Connected through hyperedge HE-1 (induced by source paper "gaussian message passing for overloaded massive mimo noma"):
  with members:
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "mu mimo mac protocols for wireless local area networks a survey"
    - "capacity achieving iterative lmmse detection for mimo noma systems"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "adaptive damping and mean removal for the generalized approximate message passing algorithm"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "s amp for non linear observation models"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-2 (induced by source paper "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"):
  with members:
    - "low complexity near optimal signal detection for uplink large scale mimo systems"
    - "large system analysis of cognitive radio network via partially projected regularized zero forcing precoding"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "par aware large scale multi user mimo ofdm downlink"
    - "energy and spectral efficiency of very large multiuser mimo systems"
    - "fixing convergence of gaussian belief propagation"
    - "gaussian belief propagation theory and application"

Connected through hyperedge HE-3 (induced by source paper "source channel coding under energy delay and buffer constraints"):
  with members:
    - "energy harvesting broadband communication systems with processing energy cost"
    - "energy neutral source channel coding with battery and memory size constraints"
    - "throughput optimal policies for energy harvesting wireless transmitters with non ideal circuit power"
    - "throughput maximization for an energy harvesting communication system with processing cost"
    - "energy management policies for energy neutral source channel coding"
    - "optimal energy allocation for wireless communications with energy harvesting constraints"
    - "a general framework for the optimization of energy harvesting communication systems with battery imperfections"
    - "transmission with energy harvesting nodes in fading wireless channels optimal policies"

Connected through hyperedge HE-4 (induced by source paper "energy management and cross layer optimization for wireless sensor network powered by heterogeneous energy sources"):
  with members:
    - "dynamic compression transmission for energy harvesting multihop networks with correlated sources"
    - "throughput maximization in wireless powered communication networks"
    - "optimal power allocation for energy harvesting and power grid coexisting wireless communication systems"
    - "decentralized delay optimal control for interference networks with limited renewable energy storage"
    - "energy management policies for energy neutral source channel coding"
    - "optimal power cost management using stored energy in data centers"
    - "transmission with energy harvesting nodes in fading wireless channels optimal policies"
    - "optimum transmission policies for battery limited energy harvesting nodes"

Connected through hyperedge HE-5 (induced by source paper "lossy computing of correlated sources with fractional sampling"):
  with members:
    - "compression with actions"
    - "cascade multiterminal source coding"

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)