Adaptive Distributed MIMO Radar Waveform Optimization Based on Mutual Information

Chen, Yifan; Nijsure, Yogesh; Yuen, Chau; Chew, Yong Huat; Ding, Zhiguo; Boussakta, S.

doi:10.1109/taes.2013.6494422

Cited by 88 publications

(81 citation statements)

References 25 publications

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“…Signal-to-noise ratio (SNR) and MI based matched illumination waveform design approaches for extended target are developed in [23] [24]. Other existing works can refer to [25] [26].…”

Section: B Brief Survey Of Similar Workmentioning

confidence: 99%

Power Minimization-Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Shi

Wang

Sellathurai

et al. 2018

IEEE Trans. Signal Process.

253

144

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“…Signal-to-noise ratio (SNR) and MI based matched illumination waveform design approaches for extended target are developed in [23] [24]. Other existing works can refer to [25] [26].…”

Section: B Brief Survey Of Similar Workmentioning

confidence: 99%

Power Minimization-Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Shi

Wang

Sellathurai

et al. 2018

IEEE Trans. Signal Process.

253

144

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“…When considering the orthogonality of the transmitted waveforms and the influence of ionosphere to echoes, it is important to design optimized waveforms that are suitable for the multi-layer ionospheric propagation circumstance, which should also be able to reduce the impact of clutter, interference and noise. Based on the groundwork from [15,16,19,20], which applied mutual information theory to design of MIMO radar waveform in order to improve target detection performance, we propose a novel two-step waveform optimization algorithm (named Max-Min algorithm) for MIMO-OTHR.…”

Section: Two-step Waveform Optimization Algorithmmentioning

confidence: 99%

Mimo-Othr Waveform Optimization Based on the Mutual Information Theory

Luo¹,

Zhao

Luo³

2016

PIER M

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Abstract-In traditional over-the-horizon radar (OTHR), multipath propagation due to the multilayer ionospheric structure always deteriorates the detection performance. The properties of multipleinput multiple-output (MIMO) radar technique, which transmits wide beams with low gain at the transmitter and achieves receiver beam-forming to obtain narrow beams with high gain, make it an ideal choice for OTHR to detect target through multi-layer ionosphere and suppress strong clutter. This paper investigates the assumption of a two-layer ionospheric model and proposes a two-step MaxMin algorithm based on the mutual information theory to optimize MIMO-OTHR waveform so as to suppress clutter, interference and noise. The first step is to maximize the mutual information between the echo and target response from the same direction of arrival (DOA) in order to reduce the impact of noise. The second step is to minimize the mutual information between the echoes from different DOAs, in order to suppress the clutter and interference by reducing the correlation of the echoes from the different DOAs. Numerical experiments validate that this algorithm can improve range resolution and detection probability significantly. Experiment results also demonstrate that the previously harmful multipath propagation can be utilized to enhance the detection performance in MIMO-OTHR.

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“…The blossoming research on massive multiple-input multiple-output (MIMO) technology has captured the attention of researchers all over the world [1] [2] [3], as it is proposed to deal with the challenges of the exponentially growing communication traffic and spectrum bands with wider bandwidth [4] [5]. In order to achieve high array gain and high spatial multiplexing gain, massive MIMO employs an unprecedented number of base station antennas simultaneously to serve a smaller number of single-antenna user terminals in the same channel.…”

Section: Introductionmentioning

confidence: 99%

Low complexity hybrid precoding in finite dimensional channel for massive MIMO systems

Chen

Boussakta

Tsimenidis

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Massive multiple-input multiple-output (MIMO) is an emerging technology for future wireless networks, scaling up conventional MIMO to an unprecedented number of antennas at base stations. Such a large antenna array has the potential to make the system achieve high channel capacity and spectral efficiency, but it also leads to high cost in terms of hardware complexity. In this paper, we consider a finite dimensional channel model in which finite distinct directions are applied with M angular bins. In massive multi-user MIMO systems, a hybrid precoding method is proposed to reduce the required number of radio frequency (RF) chains at the base station, employing a single antenna per mobile station. The proposed precoder is partitioned into a high-dimensional RF precoder and a lowdimensional baseband precoder. The RF precoder is designed to obtain power gain with phase-only control and the baseband precoder is designed to facilitate multi-stream processing. For realistic scenarios, we consider the situation where the RF phase control is quantized up to B bits of precision. Furthermore, an upper bound on spectral efficiency is derived with the proposed precoding scheme. The simulation results show that hybrid precoding achieves desirable performance in terms of spectral efficiency, which approaches the performance of zero-forcing precoding.

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Adaptive Distributed MIMO Radar Waveform Optimization Based on Mutual Information

Cited by 88 publications

References 25 publications

Power Minimization-Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Power Minimization-Based Robust OFDM Radar Waveform Design for Radar and Communication Systems in Coexistence

Mimo-Othr Waveform Optimization Based on the Mutual Information Theory

Low complexity hybrid precoding in finite dimensional channel for massive MIMO systems

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