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: "interference alignment and neutralization in a cognitive 3 user mac interference channel degrees of freedom"
  Abstract: A network consisting of a point-to-point (P2P) link and a multiple access channel (MAC) sharing the same medium is considered. The resulting interference network, with three transmitters and two receivers is studied from degrees of freedom (DoF) perspective, with and without cognition. Several cognition variants are examined. Namely, the setup is studied with (1) no cognitive transmitters, (2) a cognitive P2P transmitter, (3) one cognitive MAC transmitter, and (4) with two cognitive MAC transmitters. It is shown that having a cognitive P2P transmitter does not bring any DoF gain to the network. This is obtained by showing that the DoF of the two former cases (1) and (2) is 1. However, it is shown that a cognitive MAC transmitter is more beneficial since the latter two cases (3) and (4) have 3/2 DoF. The achievability of 3/2 DoF is guaranteed by using a combination of interference neutralization and interference alignment.

Connected through hyperedge HE-1 (induced by source paper "on the efficiency of widely linear precoding and symbol extension in cellular uplink"):
  with members:
    - "harvesting the self interference in heterogeneous full duplex networks for joint rate energy optimization"
    - "approximate capacity region of the mac ic mac"
    - "improper signaling and symbol extensions how far can we go with gaussian p2p codebooks in the interfering mac with tin"
    - "enabling the multi user generalized degrees of freedom in the gaussian cellular channel"
    - "transmit optimization with improper gaussian signaling for interference channels"

Connected through hyperedge HE-2 (induced by source paper "improper signaling and symbol extensions how far can we go with gaussian p2p codebooks in the interfering mac with tin"):
  with members:
    - "transmit optimization with improper gaussian signaling for interference channels"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"

Connected through hyperedge HE-3 (induced by source paper "sub optimality of treating interference as noise in the cellular uplink with weak interference"):
  with members:
    - "on the optimality of treating interference as noise general message sets"
    - "extended generalized dof optimality regime of treating interference as noise in the x channel"
    - "on the optimality of treating interference as noise"
    - "achievable and crystallized rate regions of the interference channel with interference as noise"
    - "the deterministic sum capacity of a multiple access channel interfering with a point to point link"
    - "sub optimality of treating interference as noise in the cellular uplink"
    - "rate region frontiers for n user interference channel with interference as noise"
    - "on the capacity of the 2 user gaussian mac interfering with a p2p link"

Connected through hyperedge HE-4 (induced by source paper "improved transmission strategies for cognitive radio under the coexistence constraint"):
  with members:
    - "cognitive radio with partial channel state information at the transmitter"
    - "interference mitigation through limited receiver cooperation"
    - "capacity gain from two transmitter and two receiver cooperation"
    - "on the fading paper achievable region of the fading mimo broadcast channel"
    - "cognitive radio an information theoretic perspective"

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)