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 mitigation through limited receiver cooperation symmetric case"
  Abstract: Interference is a major issue that limits the performance in wireless networks, and cooperation among receivers can help mitigate interference by forming distributed MIMO systems. The rate at which receivers cooperate, however, is limited in most scenarios. How much interference can one bit of receiver cooperation mitigate? In this paper, we study the two-user Gaussian interference channel with conferencing decoders to answer this question in a simple setting. We characterize the fundamental gain from cooperation: at high SNR, when INR is below 50% of SNR in dB scale, one-bit cooperation per direction buys roughly one-bit gain per user until full receiver cooperation performance is reached, while when INR is between 67% and 200% of SNR in dB scale, one-bit cooperation per direction buys roughly half-bit gain per user. The conclusion is drawn based on the approximate characterization of the symmetric capacity in the symmetric set-up. We propose strategies achieving the symmetric capacity universally to within 3 bits. The strategy consists of two parts: (1) the transmission scheme, where superposition encoding with a simple power split is employed, and (2) the cooperative protocol, where quantize-binning is used for relaying.

Connected through hyperedge HE-1 (induced by source paper "the finite state mac with cooperative encoders and delayed csi"):
  with members:
    - "dedicated relay vs user cooperation in time duplexed multiaccess networks"
    - "interference channels with source cooperation"
    - "source coding when the side information may be delayed"
    - "interference channels with destination cooperation"
    - "on the capacity of memoryless finite state multiple access channels with asymmetric state information at the encoders"
    - "compound multiple access channels with partial cooperation"
    - "on the symmetric gaussian interference channel with partial unidirectional cooperation"
    - "the gaussian mac with conferencing encoders"

Connected through hyperedge HE-2 (induced by source paper "uplink comp under a constrained backhaul and imperfect channel knowledge"):
  with members:
    - "application driven joint uplink downlink optimization in wireless communications"
    - "distributed mimo receiver achievable rates and upper bounds"
    - "cooperative multi cell networks impact of limited capacity backhaul and inter users links"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-3 (induced by source paper "scaling laws and techniques in decentralized processing of interfered gaussian channels"):
  with members:
    - "lattice strategies for the dirty multiple access channel"
    - "compute and forward harnessing interference through structured codes"
    - "lattices for distributed source coding jointly gaussian sources and reconstruction of a linear function"
    - "distributed mimo receiver achievable rates and upper bounds"
    - "a deterministic approach to wireless relay networks"

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)