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 "linear precoding with low resolution dacs for massive mu mimo ofdm downlink"):
  Abstract: We consider the downlink of a massive multiuser (MU) multiple-input multiple-output (MIMO) system in which the base station (BS) is equipped with low-resolution digital-to-analog converters (DACs). In contrast to most existing results, we assume that the system operates over a frequency-selective wideband channel and uses orthogonal frequency division multiplexing (OFDM) to simplify equalization at the user equipments (UEs). Furthermore, we consider the practically relevant case of oversampling DACs. We theoretically analyze the uncoded bit error rate (BER) performance with linear precoders (e.g., zero forcing) and quadrature phase-shift keying using Bussgang's theorem. We also develop a lower bound on the information-theoretic sum-rate throughput achievable with Gaussian inputs, which can be evaluated in closed form for the case of 1-bit DACs. For the case of multi-bit DACs, we derive approximate, yet accurate, expressions for the distortion caused by low-precision DACs, which can be used to establish lower bounds on the corresponding sum-rate throughput. Our results demonstrate that, for a massive MU-MIMO-OFDM system with a 128-antenna BS serving 16 UEs, only 3--4 DAC bits are required to achieve an uncoded BER of 10^-4 with a negligible performance loss compared to the infinite-resolution case at the cost of additional out-of-band emissions. Furthermore, our results highlight the importance of taking into account the inherent spatial and temporal correlations caused by low-precision DACs.

Includes members:
  Member "one bit massive mimo precoding via a minimum symbol error probability design":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "massive mu mimo ofdm uplink with direct rf sampling and 1 bit adcs")
  Member "a framework for one bit and constant envelope precoding over multiuser massive miso channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo")
  Member "mse optimal 1 bit precoding for multiuser mimo via branch and bound":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal precoding for multiuser mimo systems with phase quantization and psk modulation via branch and bound")
  Member "one bit precoding and constellation range design for massive mimo with qam signaling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo")
  Member "can hardware distortion correlation be neglected when analyzing uplink se in massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hardware distortion correlation has negligible impact on ul massive mimo spectral efficiency")
  Member "out of band radiation from antenna arrays clarified":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hardware distortion correlation has negligible impact on ul massive mimo spectral efficiency")
  Member "1 bit massive mu mimo precoding in vlsi":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo")
  Member "throughput analysis of massive mimo uplink with low resolution adcs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")

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)