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: "multi user detection in multibeam mobile satellite systems a fair performance evaluation"
  Abstract: Multi-User Detection (MUD) techniques are currently being examined as promising technologies for the next generation of broadband, interactive, multibeam, satellite communication (SatCom) systems. Results in the existing literature have shown that when full frequency and polarization reuse is employed and user signals are jointly processed at the gateway, more than threefold gains in terms of spectral efficiency over conventional systems can be obtained. However, the information theoretic results for the capacity of the multibeam satellite channel, are given under ideal assumptions, disregarding the implementation constraints of such an approach. Considering a real system implementation, the adoption of full resource reuse is bound to increase the payload complexity and power consumption. Since the novel techniques require extra payload resources, fairness issues in the comparison among the two approaches arise. The present contribution evaluates in a fair manner, the performance of the return link (RL) of a SatCom system serving mobile users that are jointly decoded at the receiver. More specifically, the achievable spectral efficiency of the assumed system is compared to a conventional system under the constraint of equal physical layer resource utilization. Furthermore, realistic link budgets for the RL of mobile SatComs are presented, thus allowing the comparison of the systems in terms of achievable throughput. Since the proposed systems operate under the same payload requirements as the conventional systems, the comparison can be regarded as fair. Finally, existing analytical formulas are also employed to provide closed form descriptions of the performance of clustered multibeam MUD, thus introducing insights on how the performance scales with respect to the system parameters.

Connected through hyperedge HE-1 (induced by source paper "multiuser detection in multibeam satellite systems theoretical analysis and practical schemes"):
  with members:
    - "on the application of multiuser detection in multibeam satellite systems"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-2 (induced by source paper "mmse performance analysis of generalized multibeam satellite channels"):
  with members:
    - "user scheduling for coordinated dual satellite systems with linear precoding"
    - "asymptotic performance of linear receivers in mimo fading channels"
    - "mutual information and minimum mean square error in gaussian 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)