human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "device activity and embedded information bit detection using amp in massive mimo"
  Abstract: Future cellular networks will support a massive number of devices as a result of emerging technologies such as Internet-of-Things and sensor networks. Enhanced by machine type communication (MTC), low-power low-complex devices in the order of billions are projected to receive service from cellular networks. Contrary to traditional networks which are designed to handle human driven traffic, future networks must cope with MTC based systems that exhibit sparse traffic properties, operate with small packets and contain a large number of devices. Such a system requires smarter control signaling schemes for efficient use of system resources. In this work, we consider a grant-free random access cellular network and propose an approach which jointly detects user activity and single information bit per packet. The proposed approach is inspired by the approximate message passing (AMP) and demonstrates a superior performance compared to the original AMP approach. Furthermore, the numerical analysis reveals that the performance of the proposed approach scales with number of devices, which makes it suitable for user detection in cellular networks with massive number of devices.

Connected through hyperedge HE-1 (induced by source paper "on throughput of compressive random access for one short message delivery in iot"):
  with members:
    - "massive mimo has unlimited capacity"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "random pilot and data access in massive mimo for machine type communications"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "massive mimo for wireless sensing with a coherent multiple access channel"
    - "asynchronous code division random access using convex optimization"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-2 (induced by source paper "random access for massive machine type communications"):
  with members:
    - "beamwidth control for noma in hybrid mmwave communication systems"
    - "design of non orthogonal beamspace multiple access for cellular internet of things"
    - "on the performance gain of noma over oma in uplink single cell systems"
    - "multi beam noma for hybrid mmwave systems"
    - "joint pilot and payload power control for uplink mimo noma with mrc sic receivers"
    - "reliability based windowed decoding for spatially coupled ldpc codes"
    - "short packet downlink transmission with non orthogonal multiple access"
    - "a multi beam noma framework for hybrid mmwave systems"

Connected through hyperedge HE-3 (induced by source paper "non bayesian activity detection large scale fading coefficient estimation and unsourced random access with a massive mimo receiver"):
  with members:
    - "improved scaling law for activity detection in massive mimo systems"
    - "on the fly large scale channel gain estimation for massive antenna array base stations"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "on the restricted isometry of the columnwise khatri rao product"
    - "sparse activity detection for massive connectivity"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"

Connected through hyperedge HE-4 (induced by source paper "sparcs for unsourced random access"):
  with members:
    - "massive mimo unsourced random access"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "sparse signal processing for grant free massive iot connectivity"
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "on or many access channels"
    - "state evolution for approximate message passing with non separable functions"
    - "mutual information and optimality of approximate message passing in random linear estimation"

Connected through hyperedge HE-5 (induced by source paper "multi cell sparse activity detection for massive random access massive mimo versus cooperative mimo"):
  with members:
    - "sparse activity detection for massive connectivity"
    - "a new scaling law for activity detection in massive mimo systems"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "a random access protocol for pilot allocation in crowded massive mimo systems"
    - "user activity detection in massive random access compressed sensing vs coded slotted aloha"
    - "random access in c ran for user activity detection with limited capacity fronthaul"
    - "capacity of gaussian many access channels"
    - "massive mimo ten myths and one critical question"

Connected through hyperedge HE-6 (induced by source paper "grant free massive random access with a massive mimo receiver"):
  with members:
    - "phase transition analysis for covariance based massive random access with massive mimo"
    - "non bayesian activity detection large scale fading coefficient estimation and unsourced random access with a massive mimo receiver"
    - "on the restricted isometry property of centered self khatri rao products"
    - "polar coding and random spreading for unsourced multiple access"
    - "an enhanced decoding algorithm for coded compressed sensing"
    - "improved scaling law for activity detection in massive mimo systems"
    - "on the fly large scale channel gain estimation for massive antenna array base stations"
    - "on the restricted isometry of the columnwise khatri rao product"

Connected through hyperedge HE-7 (induced by source paper "massive mimo unsourced random access"):
  with members:
    - "improved scaling law for activity detection in massive mimo systems"
    - "on the fly large scale channel gain estimation for massive antenna array base stations"
    - "sparse activity detection for massive connectivity"
    - "sparse signal processing for grant free massive iot connectivity"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "robust nonnegative sparse recovery and the nullspace property of 0 1 measurements"
    - "long range communications in unlicensed bands the rising stars in the iot and smart city scenarios"
    - "belief propagation for joint sparse recovery"

Connected through hyperedge HE-8 (induced by source paper "grant free massive mtc enabled massive mimo a compressive sensing approach"):
  with members:
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "a novel receiver design with joint coherent and non coherent processing"
    - "user activity detection in massive random access compressed sensing vs coded slotted aloha"
    - "random pilot and data access in massive mimo for machine type communications"
    - "random access protocols for massive mimo"
    - "compressive sensing based multiuser detector for the large scale sm mimo uplink"
    - "design and performance analysis of noncoherent detection systems with massive receiver arrays"
    - "massive machine type communications in 5g physical and mac layer solutions"

Question: Please tell me which class the center node 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)