Construction of 1-Bit Transmit-Signal Vectors for Downlink MU-MISO Systems With PSK Signaling

Park, Gyu-Jeong; Hong, Song‐Nam

doi:10.1109/tvt.2019.2926486

Cited by 19 publications

(10 citation statements)

References 15 publications

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“…For example, [8] proposes the optimal 1-bit solution through the use of branch-and-bound (BB) framework, which applies to small-sized MIMO systems due to the prohibitive computational costs of the BB operations. In addition, [10] enables zero-power allocation for part of the antenna elements in 1-bit precoding design, and has shown that such an approach enables further performance improvements under certain scenarios. It should be mentioned that although the concept of CI is not mentioned explicitly, the problem formulation in the two works above coincides with the symbol-scaling formulation in [2].…”

Section: Ci-based 1-bit Precoding Solutionsmentioning

confidence: 99%

1-Bit Massive MIMO Transmission: Embracing Interference with Symbol-Level Precoding

et al. 2021

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The deployment of large-scale antenna arrays for cellular base stations (BSs), termed as 'Massive MIMO', has been a key enabler for meeting the ever-increasing capacity requirement for 5G communication systems and beyond. Despite their promising performance, fully-digital massive MIMO systems require a vast amount of hardware components including radio frequency chains, power amplifiers, digital-to-analog converters (DACs), etc., resulting in a huge increase in terms of the total power consumption and hardware costs for cellular BSs. Towards both spectrally-efficient and energy-efficient massive MIMO deployment, a number of hardware limited architectures have been proposed, including hybrid analog-digital structures, constantenvelope transmission, and use of low-resolution DACs. In this paper, we overview the recent interest in improving the errorrate performance of massive MIMO systems deployed with 1-bit DACs through precoding at the symbol level. This line of research goes beyond traditional interference suppression or cancellation techniques by managing interference on a symbol-by-symbol basis. This provides unique opportunities for interference-aware precoding tailored for practical massive MIMO systems. Firstly, we characterize constructive interference (CI) and elaborate on how CI can benefit the 1-bit signal design by exploiting the traditionally undesired multi-user interference as well as the interference from imperfect hardware components. Subsequently, we overview several solutions for 1-bit signal design to illustrate the gains achievable by exploiting CI. Finally, we identify some challenges and future research directions for 1-bit massive MIMO systems that are yet to be explored.

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Section: Ci-based 1-bit Precoding Solutionsmentioning

confidence: 99%

1-Bit Massive MIMO Transmission: Embracing Interference with Symbol-Level Precoding

et al. 2021

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“…In [20] the MMDDT criterion is also utilized this time under the convex hull constraint. In [21] and [22] different greedy-search (GS) algorithms were developed using the MMDDT criterion for the 1-bit case with PSK modulation. The work from [22] is extended in [23] for QAM modulation.…”

Section: A Related Workmentioning

confidence: 99%

“…In [21] and [22] different greedy-search (GS) algorithms were developed using the MMDDT criterion for the 1-bit case with PSK modulation. The work from [22] is extended in [23] for QAM modulation. In [15] a partial B&B algorithm was considered in the context of PSK signaling for the 1-bit case.…”

Section: A Related Workmentioning

confidence: 99%

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Minimum Symbol Error Probability Low-Resolution Precoding for MU-MIMO Systems With PSK Modulation

Lopes,

Landau,

Mezghani

2021

Preprint

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We propose an optimal low-resolution precoding technique that minimizes the symbol error probability of the users. Unlike existing approaches that rely on QPSK modulation, for the derivation of the minimum symbol error probability objective function the current approach allows for any PSK modulation order. Moreover, the proposed method solves the corresponding discrete optimization problem optimally via a sophisticated branch-and-bound method. Moreover, we propose different approaches based on the greedy search method to compute practical solutions. Numerical simulations confirm the superiority of the proposed minimum symbol error probability criteria in terms of symbol error rate when compared with the established MMDDT and MMSE approaches.

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“…In addition to capacity characterization studies, channel estimation [10], [11], [12] and signal detection [13], [14], [15], [16], [17] have also been analyzed, where the work in [16] has been developed for frequency-selective channels. In a massive MIMO downlink system with 1-bit digital-to-analog converters (DACs), the severe distortions due to the coarse quantization can be partially recovered by using appropriate precoding designs [18], [19], [20], [21]. However, most of the previously reported works operate over frequency-flat fading channels, which are rarely encountered in modern broadband wireless communication systems.…”

Section: A Previous Workmentioning

confidence: 99%

Dynamic Oversampling Tecniques for 1-Bit ADCs in Large-Scale MIMO Systems

Shao¹,

Landau²,

Lamare³

2021

Preprint

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In this work, we investigate dynamic oversampling techniques for large-scale multiple-antenna systems equipped with low-cost and low-power 1-bit analog-to-digital converters at the base stations. To compensate for the performance loss caused by the coarse quantization, oversampling is applied at the receiver. Unlike existing works that use uniform oversampling, which samples the signal at a constant rate, a novel dynamic oversampling scheme is proposed. The basic idea is to perform timevarying nonuniform oversampling, which selects samples with nonuniform patterns that vary over time. We consider two system design criteria: a design that maximizes the achievable sum rate and another design that minimizes the mean square error of detected symbols. Dynamic oversampling is carried out using a dimension reduction matrix ∆, which can be computed by the generalized eigenvalue decomposition or by novel submatrix-level feature selection algorithms. Moreover, the proposed scheme is analyzed in terms of convergence, computational complexity and power consumption at the receiver. Simulations show that systems with the proposed dynamic oversampling outperform those with uniform oversampling in terms of computational cost, achievable sum rate and symbol error rate performance.

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Construction of 1-Bit Transmit-Signal Vectors for Downlink MU-MISO Systems With PSK Signaling

Cited by 19 publications

References 15 publications

1-Bit Massive MIMO Transmission: Embracing Interference with Symbol-Level Precoding

1-Bit Massive MIMO Transmission: Embracing Interference with Symbol-Level Precoding

Minimum Symbol Error Probability Low-Resolution Precoding for MU-MIMO Systems With PSK Modulation

Dynamic Oversampling Tecniques for 1-Bit ADCs in Large-Scale MIMO Systems

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