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: "channel assignment with access contention resolution for cognitive radio networks"
  Abstract: In this paper, we consider the channel assignment problem for cognitive radio networks with hardware-constrained secondary users (SUs). In particular, we assume that SUs exploit spectrum holes on a set of channels where each SU can use at most one available channel for communication. We present the optimal brute-force search algorithm to solve the corresponding nonlinear integer optimization problem and analyze its complexity. Because the optimal solution has exponential complexity with the numbers of channels and SUs, we develop two low-complexity channel assignment algorithms that can efficiently utilize the spectrum holes. In the first algorithm, SUs are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm that can improve the throughput performance compared with its nonoverlapping channel assignment counterpart. Moreover, we design a distributed medium access control (MAC) protocol for access contention resolution and integrate it into the overlapping channel assignment algorithm. We then analyze the saturation throughput and the complexity of the proposed channel assignment algorithms. We also present several potential extensions, including the development of greedy channel assignment algorithms under the max-min fairness criterion and throughput analysis, considering sensing errors. Finally, numerical results are presented to validate the developed theoretical results and illustrate the performance gains due to the proposed channel assignment algorithms.

Connected through hyperedge HE-1 (induced by source paper "location privacy in cognitive radio networks a survey"):
  with members:
    - "preserving the location privacy of secondary users in cooperative spectrum sensing"
    - "an efficient technique for protecting location privacy of cooperative spectrum sensing users"
    - "securefind secure and privacy preserving object finding via mobile crowdsourcing"
    - "lpos location privacy for optimal sensing in cognitive radio networks"
    - "geo indistinguishability differential privacy for location based systems"
    - "security of spectrum learning in cognitive radios"
    - "towards practical oblivious ram"
    - "multi agent q learning of channel selection in multi user cognitive radio systems a two by two case"

Connected through hyperedge HE-2 (induced by source paper "multi channel mac protocol for full duplex cognitive radio networks with optimized access control and load balancing"):
  with members:
    - "experiment driven characterization of full duplex wireless systems"
    - "performance of joint spectrum sensing and mac algorithms for multichannel opportunistic spectrum access ad hoc networks"
    - "distributed mac protocol for cognitive radio networks design analysis and optimization"

Connected through hyperedge HE-3 (induced by source paper "opportunistic spectrum sharing in dynamic access networks deployment challenges optimizations solutions and open issues"):
  with members:
    - "exploiting self interference suppression for improved spectrum awareness efficiency in cognitive radio systems"
    - "optimal multiband joint detection for spectrum sensing in cognitive radio networks"
    - "cognitive mimo radio"

Connected through hyperedge HE-4 (induced by source paper "design and optimal configuration of full duplex mac protocol for cognitive radio networks considering self interference"):
  with members:
    - "distributed mac protocol design for full duplex cognitive radio networks"
    - "passive self interference suppression for full duplex infrastructure nodes"
    - "joint cooperative spectrum sensing and mac protocol design for multi channel cognitive radio networks"
    - "widely linear digital self interference cancellation in direct conversion full duplex transceiver"
    - "design and characterization of a full duplex multiantenna system for wifi networks"
    - "full duplex cooperative cognitive radio with transmit imperfections"
    - "in band full duplex wireless challenges and opportunities"
    - "experiment driven characterization of full duplex wireless systems"

Connected through hyperedge HE-5 (induced by source paper "distributed mac protocol design for full duplex cognitive radio networks"):
  with members:
    - "experiment driven characterization of full duplex wireless systems"
    - "distributed mac protocol for cognitive radio networks design analysis and optimization"

Connected through hyperedge HE-6 (induced by source paper "joint cooperative spectrum sensing and mac protocol design for multi channel cognitive radio networks"):
  with members:
    - "performance of joint spectrum sensing and mac algorithms for multichannel opportunistic spectrum access ad hoc networks"
    - "distributed mac protocol for cognitive radio networks design analysis and optimization"

Connected through hyperedge HE-7 (induced by source paper "general analytical framework for cooperative sensing and access trade off optimization"):
  with members:
    - "performance of joint spectrum sensing and mac algorithms for multichannel opportunistic spectrum access ad hoc networks"
    - "distributed mac protocol for cognitive radio networks design analysis and optimization"

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)