A key challenge of future mobile communication research is to strike an attractive compromise between wireless network's area spectral efficiency and energy efficiency. This necessitates a clean-slate approach to wireless system design, embracing the rich body of existing knowledge, especially on multiple-input-multiple-ouput (MIMO) technologies. This motivates the proposal of an emerging wireless communications concept conceived for single-radio-frequency (RF) large-scale MIMO communications, which is termed as SM. The concept of SM has established itself as a beneficial transmission paradigm, subsuming numerous members of the MIMO system family. The research of SM has reached sufficient maturity to motivate its comparison to state-of-the-art MIMO communications, as well as to inspire its application to other emerging wireless systems such as relay-aided, cooperative, small-cell, optical wireless, and power-efficient communications. Furthermore, it has received sufficient research attention to be implemented in testbeds, and it holds the promise of stimulating further vigorous interdisciplinary research in the years to come. This tutorial paper is intended to offer a comprehensive state-of-the-art survey on SM-MIMO research, to provide a critical appraisal of its potential advantages, and to promote the discussion of its beneficial application areas and their research challenges leading to the analysis of the technological issues associated with the implementation of SM-MIMO. The paper is concluded with the description of the world's first experimental activities in this vibrant research field.

https://hal-supelec.archives-ouvertes.fr/hal-00840278/document

Spatial Modulation for Generalized MIMO: Challenges, Opportunities, and Implementation

A new class of low-complexity, yet energy-efficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely, the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO), has emerged. These systems are capable of exploiting the spatial dimensions (i.e., the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication while relying on a single-Radio Frequency (RF) chain. Moreover, SM may be also viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/cooperative protocol design issues, and on their meritorious variants.

/pdf/design-guidelines-for-spatial-modulation-4di7fcwiu9.pdf

Design Guidelines for Spatial Modulation

The benefits of transmit antenna selection (TAS) invoked for spatial modulation (SM) aided multiple-input multiple-output (MIMO) systems are investigated. Specifically, we commence with a brief review of the existing TAS algorithms and focus on the recently proposed Euclidean distance-based TAS (ED-TAS) schemes due to their high diversity gain. Then, a pair of novel ED-TAS algorithms, termed as the improved QR decomposition (QRD)-based TAS (QRD-TAS) and the error-vector magnitude-based TAS (EVM-TAS) are proposed, which exhibit an attractive system performance at low complexity. Moreover, the proposed ED-TAS algorithms are amalgamated with the low-complexity yet efficient power allocation (PA) technique, termed as TAS-PA, for the sake of further improving the system’s performance. Our simulation results show that the proposed TAS-PA algorithms achieve signal-to-noise ratio (SNR) gains of up to 9 dB over the conventional TAS algorithms and up to 6 dB over the TAS-PA algorithm designed for spatial multiplexing systems.

/pdf/transmit-antenna-selection-for-multiple-input-multiple-50vuab79w2.pdf

Transmit Antenna Selection for Multiple-Input Multiple-Output Spatial Modulation Systems

A complete list of the titles in this series appears at the end of this volume. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com.

Inverse Synthetic Aperture Radar Imaging with MATLAB® Algorithms: With Advanced SAR/ISAR Imaging Concepts, Algorithms, and MATLAB® Codes

Review on interferometric ISAR 3D imaging: Concept, technology and experiment

For bistatic inverse synthetic aperture radar (Bi-ISAR) imaging of space targets, the impacts of scatterers’ migration through resolution cell (MTRC) and azimuth high-order phase (AHP) are becoming more severe, especially for a long coherent processing interval (CPI). In this paper, the movement of a scatterer is modeled as a quartic function under the restriction of the space target orbit, then an MTRC-AHP compensation algorithm is proposed. A fourth-order keystone transform is introduced to remove the MTRC firstly, then the residual AHP terms are compensated gradually via the azimuth compensation phase and fractional Fourier transform (FRFT). The impact of the orbit prediction error of the space target on the algorithm is analyzed theoretically. Numerical simulations illustrate the effectiveness of the proposed method and validation of the theoretical analysis.

An MTRC-AHP Compensation Algorithm for Bi-ISAR Imaging of Space Targets

Multiband fusion imaging can effectively improve the range resolution of inverse synthetic aperture radar (ISAR) imaging. In this study, the block sparse Bayesian learning (BSBL) method is applied to multiband fusion imaging to achieve high-resolution ISAR imaging of a block-structured target. The BSBL method is suitable for the ISAR imaging of numerous and continuous scatterers because it considers the block structure characteristics of the signal. The validity of the proposed method is verified by the simulation and real-data experimental results.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2019.0369

BSBL-based multiband fusion ISAR imaging

In this paper, the spatial-variant property of inverse synthetic aperture radar (ISAR) imaging plane of space targets is exploited for phase unwrapping in bistatic interferometric ISAR (InISAR) imaging of space targets. We utilize the interferometric phases in different orbit arcs to obtain the correct fuzzy factor in a calculated set. The threshold for incorrect fuzzy factor excluding and the orbit arc selection strategy are derived for efficiency. Numerical simulations illustrate the effectiveness of the proposed method.

Phase Unwrapping for Bistatic InISAR Imaging of Space Targets

Phase-coherence of signals in different sub-bands is a prerequisite for multiband fusion radar imaging. Here, a mutual-coherence compensation method based on valid dominant poles and phase autofocusing is proposed to compensate for the incoherent phases (ICPs) between sub-bands in multiband fusion inverse synthetic aperture radar (ISAR) imaging. In the proposed method, the linear ICP compensation and fixed ICP compensation are decoupled rather than the ICPs being compensated pulse by pulse as in traditional methods. In this method, the valid dominant poles that correspond to strong scatterers in the estimated poles of each sub-band are first extracted to estimate the linear ICP. Then, phase autofocusing technology based on the same rotation centre is applied to multiple pulses in each sub-band in the ISAR coherently processing time to jointly compensate for all the fixed ICPs at once. Furthermore, a unitary estimation of signal parameters via the rotational invariance techniques (U-ESPRIT) method, which can exploit considerable information from the measured data, is utilised to estimate the poles of the sub-bands to improve the accuracy of the estimation of the linear ICP between sub-bands. The effectiveness and robustness of the method were verified experimentally based on both numerical simulations and real data.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rsn.2018.5400

Sub-band mutual-coherence compensation in multiband fusion ISAR imaging

In this paper, a coherent processing method based on valid poles and phase auto-focusing is proposed to compensate the incoherent phases between subbands in multiband radar signal fusion imaging. In order to eliminate the effect of noise on incoherent phase estimation, valid poles are firstly extracted based on the maximum cross correlation of subbands pole phase sequences, and then are reordered to estimate the linear incoherent phase. For the fixed incoherent phase estimation, phase auto-focusing which can effectively compensate the random initial phases is applied for subband echoes respectively. And the method is effective and noise insensitive as verified by simulation results.

A coherent compensation method for multiband fusion imaging

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