One-bit Transceiver Cluster for Relay Transmission

Cao, Chen; Li, Hongxing; Hu, Zixia; Zeng, Huacheng

doi:10.1109/lcomm.2016.2643631

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…Few additional ANN assisted radio frequency-based wireless systems include identification of the modulation format of the received sequence and tracking of the carrier phase. The ANN-based channel estimation technique using support vector machine, considering one-bit transceiver cluster for a relay transmission system, was also reported [11].…”

Section: Related Work and Contributionsmentioning

confidence: 99%

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ANN-Assisted Real-Time Blind Signal Detection Over Time-Varying Doubly-Stochastic Poisson Channel for Indoor Optical Wireless Communications

Arya

Chung

2020

IEEE Photonics J.

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In this paper, we present a new real-time blind signal detection technique for indoor optical communications using a supervised learning framework in an artificial neural network (ANN). We model the optical channel as a time-varying doubly-stochastic Poisson process. To compare the performance of the proposed ANN network, we present an iterative method for joint channel estimation and symbol detection using expectation-maximization (EM) and Viterbi decoding and demonstrate that the bit error rate (BER) performance of the proposed technique is better than that of the Viterbi decoding. The proposed scheme is found to be resilient to indoor channel dynamics and can achieve a good BER performance over a wide range of channel variations.

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Section: Related Work and Contributionsmentioning

confidence: 99%

“…α 0 in (13) denotes the initial value of α at the start of the iteration process. Substituting (12) and (13) into (11) and after some mathematical manipulations, a linear lower bound on log e [h(t|α,γ)] is obtained as 2…”

Section: Channel Estimation Algorithmmentioning

confidence: 99%

ANN-Assisted Real-Time Blind Signal Detection Over Time-Varying Doubly-Stochastic Poisson Channel for Indoor Optical Wireless Communications

Arya

Chung

2020

IEEE Photonics J.

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“…The key tool for the analysis of the achievable rates in [18]- [20] is the use of the additive quantization noise model (AQNM) by leveraging the Bussgang's decomposition [21]. In [22], the channel estimation methods using support vector machine and neural networks were proposed when the one-bit relay cluster was considered. The common limitation of the prior works is that they consider the one-bit quantization at either the relay or the BS.…”

Section: A Related Workmentioning

confidence: 99%

Supervised-Learning for Multi-Hop MU-MIMO Communications With One-Bit Transceivers

Kim

Hong

Lee

2019

IEEE J. Select. Areas Commun.

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This paper considers a nonlinear multi-hop multi-user multiple-input multiple-output (MU-MIMO) relay channel, in which multiple users send information symbols to a multi-antenna base station (BS) with one-bit analog-to-digital converters via intermediate relays, each with one-bit transceiver. To understand the fundamental limit of the detection performance, the optimal maximum-likelihood (ML) detector is proposed with the assumption of perfect and global channel state information (CSI) at the BS. This multi-user detector, however, is not practical due to the unrealistic CSI assumption and the overwhelming detection complexity. These limitations are addressed by presenting a novel detection framework inspired by supervised-learning. The key idea is to model the complicated multihop MU-MIMO channel as a simplified channel with much fewer and learnable parameters. One major finding is that, even using the simplified channel model, a near ML detection performance is achievable with a reasonable amount of pilot overheads in a certain condition. In addition, an online supervised-learning detector is proposed, which adaptively tracks channel variations. The idea is to update the model parameters with a reliably detected data symbol by treating it as a new training (labelled) data. Lastly, a multi-user detector using a deep neural network is proposed. Unlike the modelbased approaches, this model-free approach enables to remove the errors in the simplified channel model, while increasing the computational complexity for parameter learning. Via simulations, the detection performances of classical, model-based, and model-free detectors are thoroughly compared to demonstrate the effectiveness of the supervised-learning approaches in this channel.

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“…In particular, one-bit ADCs can be used in the future wireless systems by significantly decreasing the power consumption [ 15 , 16 ]. Despite their potential use, only a few studies have investigated one-bit ADCs in cooperative communications [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. The descriptions of the studies are briefly summarized in Table 1 .…”

Section: Introductionmentioning

confidence: 99%

Cooperative DF Protocol for MIMO Systems Using One-Bit ADCs

Kim

2022

Sensors

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This study considers a detection scheme for cooperative multi-input–multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs) in a decode-and-forward (DF) relay protocol. The use of one-bit ADCs is a promising technique for reducing the power consumption, which is necessary for supporting future wireless systems comprising a large number of antennas. However, the use of a large number of antennas remains still limited to mobile devices owing to their size. Cooperative communication using a DF relay can resolve this limitation; however, detection errors at the relay make it difficult to employ cooperative communication directly. This difficulty is more severe in a MIMO system using one-bit ADCs due to its nonlinear nature. To efficiently address the difficulty, this paper proposes a detection scheme that mitigates the error propagation effect. The upper bound of the pairwise error probability (PEP) of one-bit ADCs is first derived in a weighted Hamming distance form. Then, using the derived PEP, the proposed detection for the DF relay protocol is derived as a single weighted Hamming distance. Finally, the complexity of the proposed detection is analyzed in terms of real multiplications. The simulation results show that the proposed detection method efficiently mitigates the error propagation effect but has a relatively low level of complexity when compared to conventional detection methods.

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One-bit Transceiver Cluster for Relay Transmission

Cited by 6 publications

References 8 publications

ANN-Assisted Real-Time Blind Signal Detection Over Time-Varying Doubly-Stochastic Poisson Channel for Indoor Optical Wireless Communications

ANN-Assisted Real-Time Blind Signal Detection Over Time-Varying Doubly-Stochastic Poisson Channel for Indoor Optical Wireless Communications

Supervised-Learning for Multi-Hop MU-MIMO Communications With One-Bit Transceivers

Cooperative DF Protocol for MIMO Systems Using One-Bit ADCs

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