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: "bounds on the sum capacity of synchronous binary cdma channels"
  Abstract: In this paper, we obtain a family of lower bounds for the sum capacity of code-division multiple-access (CDMA) channels assuming binary inputs and binary signature codes in the presence of additive noise with an arbitrary distribution. The envelope of this family gives a relatively tight lower bound in terms of the number of users, spreading gain, and the noise distribution. The derivation methods for the noiseless and the noisy channels are different but when the noise variance goes to zero, the noisy channel bound approaches the noiseless case. The behavior of the lower bound shows that for small noise power, the number of users can be much more than the spreading gain without any significant loss of information (overloaded CDMA). A conjectured upper bound is also derived under the usual assumption that the users send out equally likely binary bits in the presence of additive noise with an arbitrary distribution. As the noise level increases, and/or, the ratio of the number of users and the spreading gain increases, the conjectured upper bound approaches the lower bound. We have also derived asymptotic limits of our bounds that can be compared to a formula that Tanaka obtained using techniques from statistical physics; his bound is close to that of our conjectured upper bound for large scale systems.

Connected through hyperedge HE-1 (induced by source paper "spectral efficiency of random time hopping cdma"):
  with members:
    - "what will 5g be"
    - "tight bounds on the capacity of binary input random cdma systems"
    - "sparsely spread cdma a statistical mechanics based analysis"
    - "analysis of belief propagation for non linear problems the example of cdma or how to prove tanaka s formula"
    - "randomly spread cdma asymptotics via statistical physics"
    - "channel uncertainty in ultra wideband communication systems"

Connected through hyperedge HE-2 (induced by source paper "capacity bounds of finite dimensional cdma systems with fading near far effects and power control"):
  with members:
    - "analysis of belief propagation for non linear problems the example of cdma or how to prove tanaka s formula"
    - "randomly spread cdma asymptotics via statistical physics"

Connected through hyperedge HE-3 (induced by source paper "the enigma of cdma revisited"):
  with members:
    - "applications of lindeberg principle in communications and statistical learning"
    - "new bounds for binary and ternary overloaded cdma"
    - "tight bounds on the capacity of binary input random cdma systems"
    - "errorless codes for over loaded cdma with active user detection"
    - "a new method for constructing large size wbe codes with low complexity ml decoder"
    - "analysis of belief propagation for non linear problems the example of cdma or how to prove tanaka s formula"
    - "randomly spread cdma asymptotics via statistical physics"

Connected through hyperedge HE-4 (induced by source paper "almost optimum signature matrices in binary input synchronous overloaded cdma"):
  with members:
    - "the enigma of cdma revisited"
    - "a class of errorless codes for over loaded synchronous wireless and optical cdma systems"

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)