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 "joint active user detection and channel estimation in massive access systems exploiting reed muller sequences"):
  Abstract: The requirements to support massive connectivity and low latency in massive machine type communications bring a huge challenge in the design of its random access procedure, which usually calls for efficient joint active user detection and channel estimation. In this paper, we exploit the vast sequence space and the beneficial nested structure of the length-2#N# m#N# second-order Reed-Muller (RM) sequences for designing an efficient RA scheme, which is capable of reliably detecting multiple active users from the set of unknown potential users with a size as large as 2#N# m(m-1)/2#N# while simultaneously estimating their channel state information as well. Explicitly, at the transmitter, each user is mapped to a specially designed RM sequence, which facilitates reliable joint sequence detection and channel estimation based on a single transmission event. To elaborate, as a first step, at the receiver, we exploit the elegant nested structure of the RM sequences using a layer-by-layer RM detection algorithm for the single-user (single-sequence) scenario. Then, an iterative RM detection and channel estimation algorithm is conceived for the multi-user (multi-sequence) scenario. As a benefit of the information exchange between the RM sequence detector and channel estimator, a compelling performance versus complexity trade-off is struck, as evidenced both by our analytical and numerical results.

Includes members:
  Member "reed muller sequences for 5g grant free massive access":
    also connected through other hyperedges:
      (none)
  Member "massive connectivity with massive mimo part i device activity detection and channel estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "faster activity and data detection in massive random access a multi armed bandit approach")
  Member "compressive random access using a common overloaded control channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "random access for massive machine type communications")
  Member "random access for machine type communication based on bloom filtering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic binary countdown for massive iot random access in dense 5g networks")
  Member "code expanded random access for machine type communications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a probabilistic approach to model sic based rach mechanism for massive machine type communications in cellular networks")
  Member "reed muller sensing matrices and the lasso":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "kerdock codes determine unitary 2 designs")

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)