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 as noise friend or foe"
  Abstract: This paper shows that for the two-user Gaussian Interference Channel (G-IC) Treating Interference as Noise without Time Sharing (TINnoTS) achieves the closure of the capacity region to within either a constant gap, or to within a gap of the order O(logln(min(S,I))) where S is the largest Signal to Noise Ratio (SNR) on the direct links and I is the largest Interference to Noise Ratio (INR) on the cross links. As a consequence, TINnoTS is optimal from a generalized Degrees of Freedom (gDoF) perspective for all channel gains except for a subset of zero measure. TINnoTS with Gaussian inputs is known to be optimal to within 1/2 bit for a subset of the weak interference regime. Surprisingly, this paper shows that TINnoTS is gDoG optimal in all parameter regimes, even in the strong and very strong interference regimes where joint decoding of Gaussian inputs is optimal. For approximate optimality of TINnoTS in all parameter regimes it is critical to use non-Gaussian inputs. This work thus proposes to use mixed inputs as channel inputs where a mixed input is the sum of a discrete and a Gaussian random variable. Interestingly, compared to the Han-Kobayashi inner bound, the discrete part of a mixed input is shown to effectively act as a common message in the sense that, although treated as noise, its effect on the achievable rate region is as if it were jointly decoded together with the desired messages at a non-intended receiver. The practical implication is that a discrete interfering input is a 'friend', while a Gaussian interfering input is in general a 'foe'. Since TINnoTS requires neither joint decoding nor time sharing, the results of this paper are applicable to a variety of oblivions or asynchronous channels, such as the block asynchronous G-IC (which is not an information stable) and the G-IC with partial codebook knowledge at one or more receivers.

Connected through hyperedge HE-1 (induced by source paper "on linearly precoded rate splitting for mimo broadcast channels"):
  with members:
    - "rate splitting multiple access for downlink communication systems bridging generalizing and outperforming sdma and noma"
    - "optimal dof region of the k user miso bc with partial csit"
    - "sum rate maximization for linearly precoded downlink multiuser miso systems with partial csit a rate splitting approach"
    - "robust transmission in downlink multiuser miso systems a rate splitting approach"
    - "a rate splitting strategy for massive mimo with imperfect csit"
    - "real interference alignment exploiting the potential of single antenna systems"
    - "degrees of freedom of time correlated miso broadcast channel with delayed csit"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-2 (induced by source paper "on the optimality of treating inter cell interference as noise in uplink cellular networks"):
  with members:
    - "on multi cell uplink downlink duality with treating inter cell interference as noise"
    - "on the optimality of treating interference as noise for interfering multiple access channels"
    - "opportunistic treating interference as noise"
    - "optimality of treating interference as noise a combinatorial perspective"
    - "on the optimality of treating interference as noise compound interference networks"
    - "on the optimality of treating interference as noise general message sets"
    - "on the optimality of treating interference as noise for k user parallel gaussian interference networks"
    - "achievable and crystallized rate regions of the interference channel with interference as noise"

Connected through hyperedge HE-3 (induced by source paper "linearly precoded rate splitting optimality and non optimality for mimo broadcast channels"):
  with members:
    - "tomlinson harashima precoded rate splitting for multiuser mimo systems"
    - "robust transmission in downlink multiuser miso systems a rate splitting approach"
    - "real interference alignment exploiting the potential of single antenna systems"
    - "degrees of freedom of time correlated miso broadcast channel with delayed csit"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-4 (induced by source paper "upper and lower bounds on the capacity of amplitude constrained mimo channels"):
  with members:
    - "the capacity of gaussian mimo channels under total and per antenna power constraints"
    - "an upper bound for the capacity of amplitude constrained scalar awgn channel"
    - "capacity bounds for discrete time amplitude constrained additive white gaussian noise channels"
    - "on the capacity of vector gaussian channels with bounded inputs"
    - "miso capacity with per antenna power constraint"
    - "on the boundedness of the support of optimal input measures for rayleigh fading channels"

Connected through hyperedge HE-5 (induced by source paper "on communication through a gaussian channel with an mmse disturbance constraint"):
  with members:
    - "on the two user interference channel with lack of knowledge of the interference codebook at one receiver"
    - "soft decoding based strategies for relay and interference channels analysis and achievable rates using ldpc codes"
    - "analysis of mismatched estimation errors using gradients of partition functions"
    - "mmse of bad codes"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "capacity bounds for the gaussian interference channel"

Connected through hyperedge HE-6 (induced by source paper "on the minimum mean p th error in gaussian noise channels and its applications"):
  with members:
    - "on communication through a gaussian channel with an mmse disturbance constraint"
    - "lower bounds on parameter modulation estimation under bandwidth constraints"
    - "exponential error bounds on parameter modulation estimation for discrete memoryless channels"
    - "on conditions for linearity of optimal estimation"
    - "mmse of bad codes"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "mutual information and minimum mean square error in gaussian 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)