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 "massive connectivity with massive mimo part i device activity detection and channel estimation"):
  Abstract: This two-part paper considers an uplink massive device communication scenario in which a large number of devices are connected to a base station (BS), but user traffic is sporadic so that in any given coherence interval, only a subset of users is active. The objective is to quantify the cost of active user detection and channel estimation and to characterize the overall achievable rate of a grant-free two-phase access scheme in which device activity detection and channel estimation are performed jointly using pilot sequences in the first phase and data is transmitted in the second phase. In order to accommodate a large number of simultaneously transmitting devices, this paper studies an asymptotic regime where the BS is equipped with a massive number of antennas. The main contributions of Part I of this paper are as follows. First, we note that as a consequence of having a large pool of potentially active devices but limited coherence time, the pilot sequences cannot all be orthogonal. However, despite the nonorthogonality, this paper shows that in the asymptotic massive multiple-input multiple-output regime, both the missed device detection and the false alarm probabilities for activity detection can always be made to go to zero by utilizing compressed sensing techniques that exploit sparsity in the user activity pattern. Part II of this paper further characterizes the achievable rates using the proposed scheme and quantifies the cost of using nonorthogonal pilot sequences for channel estimation in achievable rates.

Includes members:
  Member "sparse activity detection for massive connectivity":
    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 "massive connectivity with massive mimo part ii achievable rate characterization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "faster activity and data detection in massive random access a multi armed bandit approach")
  Member "a random access protocol for pilot allocation in crowded massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "massive mimo asymptotics for ray based propagation channels")
  Member "capacity of gaussian many access channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "unsourced multiuser sparse regression codes achieve the symmetric mac capacity")
  Member "massive machine type communications in 5g physical and mac layer solutions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "compressive random access using a common overloaded control channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "random access for massive machine type communications")
  Member "sparse signal processing concepts for efficient 5g system design":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "faster activity and data detection in massive random access a multi armed bandit approach")
  Member "massive mimo for next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")

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)