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: "design of learning based mimo cognitive radio systems"
  Abstract: This paper addresses the design issues of the multi-antenna-based cognitive radio (CR) system that is able to operate concurrently with the licensed primary radio (PR) system. We propose a practical CR transmission strategy consisting of three major stages: environment learning, channel training, and data transmission. In the environment learning stage, the CR transceivers both listen to the PR transmission and apply blind algorithms to estimate the spaces that are orthogonal to the channels from the PR. Assuming time-division duplex (TDD) based transmission for the PR, cognitive beamforming is then designed and applied at CR transceivers to restrict the interference to/from the PR during the subsequent channel training and data transmission stages. In the channel training stage, the CR transmitter sends training signals to the CR receiver, which applies the linear-minimum-mean-square-error (LMMSE) based estimator to estimate the effective channel. Considering imperfect estimations in both learning and training stages, we derive a lower bound on the ergodic capacity achievable for the CR in the data transmission stage. From this capacity lower bound, we observe a general learning/training/throughput tradeoff associated with the proposed scheme, pertinent to transmit power allocation between training and transmission stages, as well as time allocation among learning, training, and transmission stages. We characterize the aforementioned tradeoff by optimizing the associated power and time allocation to maximize the CR ergodic capacity.

Connected through hyperedge HE-1 (induced by source paper "primary channel gain estimation for spectrum sharing in cognitive radio networks"):
  with members:
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"
    - "on active learning and supervised transmission of spectrum sharing based cognitive radios by exploiting hidden primary radio feedback"
    - "cognitive beamforming made practical effective interference channel and learning throughput tradeoff"

Connected through hyperedge HE-2 (induced by source paper "semi coherent detection and performance analysis for ambient backscatter system"):
  with members:
    - "inter technology backscatter towards internet connectivity for implanted devices"

Connected through hyperedge HE-3 (induced by source paper "on effects of imperfect channel state information on null space based cognitive mimo communication"):
  with members:
    - "blind null space learning for mimo underlay cognitive radio networks"

Connected through hyperedge HE-4 (induced by source paper "performance analysis of cognitive radio systems with imperfect channel sensing and estimation"):
  with members:
    - "performance analysis of cognitive radio systems under qos constraints and channel uncertainty"
    - "optimal multiband joint detection for spectrum sensing in cognitive radio networks"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"
    - "effective capacity analysis of cognitive radio channels for quality of service provisioning"
    - "on peak versus average interference power constraints for protecting primary users in cognitive radio networks"
    - "capacity results for block stationary gaussian fading channels with a peak power constraint"

Connected through hyperedge HE-5 (induced by source paper "cognitive internet of things a new paradigm beyond connection"):
  with members:
    - "context aware computing for the internet of things a survey"
    - "sensing as a service and big data"
    - "dynamic anomalography tracking network anomalies via sparsity and low rank"
    - "low rank matrix recovery from errors and erasures"
    - "robust principal component analysis"

Connected through hyperedge HE-6 (induced by source paper "on the throughput and energy efficiency of cognitive mimo transmissions"):
  with members:
    - "cognitive radio transmission under qos constraints and interference limitations"
    - "performance analysis of cognitive radio systems under qos constraints and channel uncertainty"
    - "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
    - "from spectrum pooling to space pooling opportunistic interference alignment in mimo cognitive networks"
    - "mimo wireless communications under statistical queueing constraints"
    - "effective capacity analysis of cognitive radio channels for quality of service provisioning"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"
    - "cognitive mimo radio"

Connected through hyperedge HE-7 (induced by source paper "adaptive mode selection in multiuser miso cognitive networks with limited cooperation and feedback"):
  with members:
    - "interference aware resource control in multi antenna cognitive ad hoc networks with heterogeneous delay constraints"
    - "censored truncated sequential spectrum sensing for cognitive radio networks"
    - "multi mode transmission for the mimo broadcast channel with imperfect channel state information"
    - "price based resource allocation for spectrum sharing femtocell networks a stackelberg game approach"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"
    - "on peak versus average interference power constraints for protecting primary users in cognitive radio networks"
    - "investigation on multiuser diversity in spectrum sharing based cognitive radio networks"
    - "mimo broadcast channels with finite rate feedback"

Connected through hyperedge HE-8 (induced by source paper "the one bit null space learning algorithm and its convergence"):
  with members:
    - "interference mitigation for cognitive radio mimo systems based on practical precoding"
    - "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
    - "on active learning and supervised transmission of spectrum sharing based cognitive radios by exploiting hidden primary radio feedback"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"
    - "cognitive mimo radio"
    - "cognitive beamforming made practical effective interference channel and learning throughput tradeoff"

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)