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: "power bandwidth tradeoff in dense multi antenna relay networks"
  Abstract: We consider a dense fading multi-user network with multiple active multi-antenna source-destination pair terminals communicating simultaneously through a large common set of K multi-antenna relay terminals in the full spatial multiplexing mode. We use Shannon-theoretic tools to analyze the tradeoff between energy efficiency and spectral efficiency (known as the power-bandwidth tradeoff) in meaningful asymptotic regimes of signal-to-noise ratio (SNR) and network size. We design linear distributed multi-antenna relay beamforming (LDMRB) schemes that exploit the spatial signature of multi-user interference and characterize their power-bandwidth tradeoff under a system-wide power constraint on source and relay transmissions. The impact of multiple users, multiple relays and multiple antennas on the key performance measures of the high and low SNR regimes is investigated in order to shed new light on the possible reduction in power and bandwidth requirements through the usage of such practical relay cooperation techniques. Our results indicate that point-to-point coded multi-user networks supported by distributed relay beamforming techniques yield enhanced energy efficiency and spectral efficiency, and with appropriate signaling and sufficient antenna degrees of freedom, can achieve asymptotically optimal power-bandwidth tradeoff with the best possible (i.e., as in the cutset bound) energy scaling of K-1 and the best possible spectral efficiency slope at any SNR for large number of relay terminals. Furthermore, our results help to identify the role of interference cancellation capability at the relay terminals on realizing the optimal power- bandwidth tradeoff; and show how relaying schemes that do not attempt to mitigate multi-user interference, despite their optimal capacity scaling performance, could yield a poor power- bandwidth tradeoff.

Connected through hyperedge HE-1 (induced by source paper "collaborative broadcast in o log log n rounds"):
  with members:
    - "on capacity scaling in arbitrary wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-2 (induced by source paper "interference cancellation at the relay for multi user wireless cooperative networks"):
  with members:
    - "multi user transmissions for relay networks with linear complexity"
    - "performance analysis of multiple antenna multi user detection"

Connected through hyperedge HE-3 (induced by source paper "multisource transmission for wireless relay networks with linear complexity"):
  with members:
    - "interference cancellation at the relay for multi user wireless cooperative networks"
    - "performance analysis of multiple antenna multi user detection"

Connected through hyperedge HE-4 (induced by source paper "distributed beamforming in wireless multiuser relay interference networks with quantized feedback"):
  with members:
    - "distributed scalar quantization for computing high resolution analysis and extensions"
    - "relay selection and performance analysis in multiple user networks"
    - "interference alignment with limited feedback"
    - "combining beamforming and space time coding using noisy quantized feedback"
    - "grassmannian beamforming for mimo amplify and forward relaying"
    - "network beamforming using relays with perfect channel information"
    - "a simple cooperative diversity method based on network path selection"
    - "mimo broadcast channels with finite rate feedback"

Connected through hyperedge HE-5 (induced by source paper "power bandwidth tradeoff in multiuser relay channels with opportunistic scheduling"):
  with members:
    - "multihop diversity in wideband ofdm systems the impact of spatial reuse and frequency selectivity"
    - "opportunistic relay selection with limited feedback"
    - "opportunism in multiuser relay channels scheduling routing and spectrum reuse"
    - "cooperative relay broadcast channels"
    - "high snr analysis of mimo broadcast channels"

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)