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 "soft output detection methods for sparse millimeter wave mimo systems with low precision adcs"):
  Abstract: The use of low-precision analog-to-digital converters (ADCs) is a low-cost and power-efficient solution for a millimeter wave (mmWave) multiple-input multiple-output (MIMO) system operating at sampling rates higher than a few Gsample/sec. This solution, however, can make significant frame-error-rates (FERs) degradation due to inter-subcarrier interference when applying conventional frequency-domain equalization techniques. In this paper, we propose computationally-efficient yet near-optimal soft-output detection methods for the coded mmWave MIMO systems with low-precision ADCs. The underlying idea of the proposed methods is to construct an extremely sparse inter-symbol-interference (ISI) channel model by jointly exploiting the delay-domain sparsity in mmWave channels and a high quantization noise caused by low-precision ADCs. Then we harness this sparse channel model to create a trellis diagram with a reduced number of states or a factor graph with very sparse edge connections. Using the reduced trellis diagram, we present a soft-output detection method that computes the log-likelihood ratios (LLRs) of coded bits by optimally combining the quantized received signals obtained from multiple receive antennas using a forward-and-backward algorithm. To reduce the computational complexity further, we also present a low-complexity detection method using the sparse factor graph to compute the LLRs in an iterative fashion based on a belief propagation algorithm. Simulations results demonstrate that the proposed soft-output detection methods provide significant FER gains compared to the existing frequency-domain equalization techniques in a coded mmWave MIMO system using one- or two-bit ADCs.

Includes members:
  Member "joint channel estimation decoding with frequency selective channels and few bit adcs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "reliable ofdm transmission with ultra low resolution adc")
  Member "on low resolution adcs in practical 5g millimeter wave massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")
  Member "bayesian optimal data detector for hybrid mmwave mimo ofdm systems with low resolution adcs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hardware constrained millimeter wave systems for 5g challenges opportunities and solutions")
  Member "one bit sphere decoding for uplink massive mimo systems with one bit adcs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo")
  Member "performance analysis of mixed adc massive mimo systems over rician fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "angle aware user cooperation for secure massive mimo in rician fading channel")
  Member "bayesian optimal data detector for mmwave ofdm system with low resolution adc":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "time varying downlink channel tracking for quantized massive mimo networks")
  Member "bayes optimal joint channel and data estimation for massive mimo with low precision adcs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "faster activity and data detection in massive random access a multi armed bandit approach")
  Member "on the spectral efficiency of massive mimo systems with low resolution adcs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multiple antenna technologies for beyond 5g")

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)