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 "random access for massive machine type communications"):
  Abstract: The thesis is dedicated to studying methods to improve the efficiency of random access schemes and to facilitate their deployment in machine-type communications (MTC). First, a joint user activity identification and channel estimation scheme is designed for grant-free random access systems. We propose a decentralized transmission control and design a compressed sensing (CS)-based user identification and channel estimation scheme. We analyze the packet delay and throughput of the proposed scheme. We also optimize the transmission control scheme to maximize the system throughput. Second, a random access scheme, i.e., the coded slotted ALOHA (CSA) scheme, is designed for erasure channels to improve the system throughput. By deriving the extrinsic information transfer (EXIT) functions and optimizing their convergence behavior, we design the code probability distributions for CSA schemes with repetition codes and maximum distance separable (MDS) codes to maximize the expected traffic load, under packet erasure and slot erasure channels. We derive the asymptotic throughput of CSA schemes over the erasure channels for an infinite frame length, which is verified to well approximate the throughput for a practical frame length. Third, an efficient data decoding algorithm for the CSA scheme is proposed to further improve the system efficiency. We present a low-complexity physical-layer network coding (PNC) method to obtain linear combinations of collided packets and design an enhanced message-level successive interference cancellation (SIC) algorithm to exploit the linear combinations of collided packets. We propose an analytical framework and derive the system throughput for the proposed scheme. The CSA scheme is further optimized to maximize the system throughput and energy efficiency.

Includes members:
  Member "beamwidth control for noma in hybrid mmwave communication systems":
    also connected through other hyperedges:
      (none)
  Member "design of non orthogonal beamspace multiple access for cellular internet of things":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a dimension reduction based joint activity detection and channel estimation algorithm for massive access")
  Member "on the performance gain of noma over oma in uplink single cell systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the performance gain of noma over oma in uplink communication systems")
  Member "multi beam noma for hybrid mmwave systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "joint pilot and payload power control for uplink mimo noma with mrc sic receivers":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey of rate optimal power domain noma schemes for enabling technologies of future wireless networks")
  Member "reliability based windowed decoding for spatially coupled ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "enhanced quasi maximum likelihood decoding of short ldpc codes based on saturation")
  Member "short packet downlink transmission with non orthogonal multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "robust urllc packet scheduling of ofdm systems")
  Member "a multi beam noma framework for hybrid mmwave systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "interplay between noma and other emerging technologies a survey")

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)