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 "calculation of the performance of communication systems from measured oscillator phase noise"):
  Abstract: Oscillator phase noise (PN) is one of the major problems that affect the performance of communication systems. In this paper, a direct connection between oscillator measurements, in terms of measured single-side band PN spectrum, and the optimal communication system performance, in terms of the resulting error vector magnitude (EVM) due to PN, is mathematically derived and analyzed. First, a statistical model of the PN, considering the effect of white and colored noise sources, is derived. Then, we utilize this model to derive the modified Bayesian Cramer-Rao bound on PN estimation, and use it to find an EVM bound for the system performance. Based on our analysis, it is found that the influence from different noise regions strongly depends on the communication bandwidth, i.e., the symbol rate. For high symbol rate communication systems, cumulative PN that appears near carrier is of relatively low importance compared to the white PN far from carrier. Our results also show that 1/f 3 noise is more predictable compared to 1/f 2 noise and in a fair comparison it affects the performance less.

Includes members:
  Member "multi sample receivers increase information rates for wiener phase noise channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "models and information rates for wiener phase noise channels")
  Member "effect of synchronizing coordinated base stations on phase noise estimation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the capacity of the wiener phase noise channel bounds and capacity achieving distributions")
  Member "estimation of phase noise in oscillators with colored noise sources":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal reference signal design for phase noise compensation in multi carrier massive mimo systems")
  Member "soft metrics and their performance analysis for optimal data detection in the presence of strong oscillator phase noise":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analysis and design of secure massive mimo systems in the presence of hardware impairments")
  Member "on wiener phase noise channels at high signal to noise ratio":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "models and information rates for wiener phase noise channels")

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)