human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "the enigma of cdma revisited"):
  Abstract: In this paper, we explore the mystery of synchronous CDMA as applied to wireless and optical communication systems under very general settings for the user symbols and the signature matrix entries. The channel is modeled with real/complex additive noise of arbitrary distribution. Two problems are addressed. The first problem concerns whether overloaded error free codes exist in the absence of additive noise under these general settings, and if so whether there are any practical optimum decoding algorithms. The second one is about the bounds for the sum channel capacity when user data and signature codes employ any real or complex alphabets (finite or infinite). In response to the first problem, we have developed practical Maximum Likelihood (ML) decoding algorithms for overloaded CDMA systems for a large class of alphabets. In response to the second problem, a general theorem has been developed in which the sum capacity lower bounds with respect to the number of users and spreading gain and Signal-to-Noise Ratio (SNR) can be derived as special cases for a given CDMA system. To show the power and utility of the main theorem, a number of sum capacity bounds for special cases are simulated. An important conclusion of this paper is that the lower and upper bounds of the sum capacity for small/medium size CDMA systems depend on both the input and the signature symbols; this is contrary to the asymptotic results for large scale systems reported in the literature (also confirmed in this paper) where the signature symbols and statistics disappear in the asymptotic sum capacity. Moreover, these questions are investigated for the case when not all users are active. Furthermore, upper and asymptotic bounds are derived and numerically evaluated and compared to other derivations.

Includes members:
  Member "applications of lindeberg principle in communications and statistical learning":
    also connected through other hyperedges:
      (none)
  Member "new bounds for binary and ternary overloaded cdma":
    also connected through other hyperedges:
      (none)
  Member "bounds on the sum capacity of synchronous binary cdma channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spectral efficiency of random time hopping cdma")
  Member "tight bounds on the capacity of binary input random cdma systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal errors and phase transitions in high dimensional generalized linear models")
  Member "errorless codes for over loaded cdma with active user detection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "new bounds for binary and ternary overloaded cdma")
  Member "a new method for constructing large size wbe codes with low complexity ml decoder":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a class of errorless codes for over loaded synchronous wireless and optical cdma systems")
  Member "analysis of belief propagation for non linear problems the example of cdma or how to prove tanaka s formula":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "understanding phase transitions via mutual information and mmse")
  Member "randomly spread cdma asymptotics via statistical physics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "unsourced multiuser sparse regression codes achieve the symmetric mac capacity")

Question: Please tell me which class the source paper 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)