human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "fractional interference alignment an interference alignment scheme for finite alphabet signals"):
  Abstract: Interference Alignment (IA) is a transmission scheme which achieves 1/2 Degrees-of-Freedom (DoF) per transmit-antenna per user. The constraints imposed on the scheme are based on the linear receiver since conventional IA assumes Gaussian signaling. However, when the transmitters employ Finite Alphabet (FA) signaling, neither the conventional IA precoders nor the linear receiver are optimal structures. Therefore, a novel Fractional Interference Alignment (FIA) scheme is introduced when FA signals are used, where the alignment constraints are now based on the non-linear, minimum distance (MD) detector. Since DoF is defined only as signal-to-noise ratio tends to infinity, we introduce a new metric called SpAC (number of Symbols transmitted-per-transmit Antenna-per-Channel use) for analyzing the FIA scheme. The maximum SpAC is one, and the FIA achieves any value of SpAC in the range [0,1]. The key motivation for this work is that numerical simulations with FA signals and MD detector for fixed SpAC (=1/2, as in IA) over a set of optimization problems, like minimizing bit error rate or maximizing the mutual information, achieves a significantly better error rate performance when compared to the existing algorithms that minimize mean square error or maximize signal-to-interference plus noise ratio.

Includes members:
  Member "on precoding for constant k user mimo gaussian interference channel with finite constellation inputs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on mimo transmission with discrete input signals technical challenges advances and future trends")
  Member "partial interference alignment for k user mimo interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cellular multiuser two way mimo af relaying via signal space alignment minimum weighted sinr maximization")
  Member "interference alignment as a rank constrained rank minimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "generalized low rank optimization for topological cooperation in ultra dense networks")
  Member "approaching the capacity of wireless networks through distributed interference alignment":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fundamental limits of dynamic interference management with flexible message assignments")
  Member "gaussian interference channel capacity to within one bit":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")

Question: Please tell me which class the source paper 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)