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 "exact performance analysis of partial relay selection based on shadowing side information over generalized composite fading channels"):
  Abstract: Relay technology has recently gained great interest in millimeter wave (60 GHz or above) radio frequencies as a promising transmission technique improving the quality of service, providing high data rate, and extending the coverage area without additional transmit power in deeply shadowed fading environments. The performance of relay-based systems considerably depends on which relay selection protocols (RSPs) are used. These RSPs are typically using the channel side information (CSI). Specifically, the relay terminal (RT) is chosen among all available RTs by a central entity (CE) which receives all RTs' CSI via feedback channels. However, in the millimeter wave radio frequencies, the rate of the CSI variation is much higher than that of the CSI variation in 6 GHz frequencies under the same mobility conditions, which evidently results in a serious problem causing that the CSI at the CE is inaccurate for the RSP since the feedback channels have a backhaul / transmission delay. However and fortunately, the shadowing side information (SSI) varies very slowly in comparison to the rate of the CSI variation. In this context, we propose in this paper a partial-RSP in dual-hop amplify-and-forward relaying system, which utilize only the SSI of the RTs instead of their CSI. Then for the performance analysis, we obtain an exact average unified performance (AUP) of the proposed SSI-based partial-RSP for a variety shadowed fading environments. In particular, we offer a generic AUP expression whose special cases include the average bit error probability (ABEP) analysis for binary modulation schemes, the ergodic capacity analysis and the moments-generating function (MGF)-based characterization. The correctness of our newly theoretical results is validated with some selected numerical examples in an extended generalized-K fading environment.

Includes members:
  Member "a novel ergodic capacity analysis of diversity combining and multihop transmission systems over generalized composite fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the asymptotic analysis of the high order statistics of the channel capacity over generalized fading channels")
  Member "a novel unified expression for the capacity and bit error probability of wireless communication systems over generalized fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hetnets coverage modeling and analysis over fox s mathcal h fading channels")
  Member "a simple cooperative diversity method based on network path selection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynwalks global topology and recent changes awareness dynamic network embedding")

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)