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41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Cherubini, Giovanni Hurley, Paul Simeoni, Matthieu Kazemi, Sanaz IBM Res Zurich CH-8803 Ruschlikon Switzerland IBM Netherlands Amsterdam Netherlands

ISBN: (纸本)9781479999880

Imaging techniques in radio interferometry often face a significant challenge posed by the large number of antenna signals received, from which the image information needs to be extracted. Beamforming is envisaged to reduce the rate required for transporting data from groups of antennas to a central site for further processing. We propose a novel method for image reconstruction based on the iterative scanning of a region of interest, combined with randomized beamforming. A modified approximate message-passing algorithm is adopted to extract relevant image information from beamformed signals received at the antenna stations. The method is illustrated by simulations, with reference to the LOFAR radio interferometer, and compared with the CLEAN algorithm.

关键词： Radio interferometry amp algorithm imaging sensor arrays antenna arrays

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IMAGING IN RADIO INTERFEROMETRY BY ITERATIVE SUBSET SCANNING USING A MODIFIED amp algorithm

IMAGING IN RADIO INTERFEROMETRY BY ITERATIVE SUBSET SCANNING...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Giovanni Cherubini Paul Hurley Matthieu Simeoni Sanaz Kazemi IBM Research - Zurich 8803 Rüschlikon Switzerland

ISBN: (纸本)9781479999897

关键词： Radio interferometry amp algorithm imaging sensor arrays antenna arrays

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Efficient hybrid Neumann series based MMSE assisted detection for 5G and beyond massive MIMO systemsInspec keywordsOther keywords

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IET COMMUNICATIONS 2020年第22期14卷 4142-4151页

作者： Khurshid, Kiran Imran, Muhammad Khan, Adnan Ahmed Rashid, Imran Siddiqui, Haroon Natl Univ Sci & Technol Dept Elect Engn Islamabad Pakistan Natl Univ Sci & Technol Dept Comp Software Engn Islamabad Pakistan

Massive multiple-input multiple-output (M-MIMO) is one of the cutting edge technologies that provides significant improvement in throughput, coverage and spectral efficiency. The challenge with M-MIMO systems is to extract individual signals from the composite signal, thus making optimal detectors prohibitively complex. Recently, approximate message passing (amp) and its variant detectors have gained substantial importance due to their decreased complexity and improved performance. However, amp algorithm does not always converge. Non-linear detectors like vertical Bell-Labs layered space-iime improve the bit error rate (BER) but with high complexity, whereas, linear minimum mean square error (MMSE) detector offers low complexity while compromising on BER performance. Neumann series based MMSE detectors further reduce MMSE computational complexity, however, the BER performance remains the same. In this work, the authors propose a hybrid Neumann series based MMSE detector which decomposes the detected signal into its constituent components and apply a neighbourhood selection algorithm on the obtained components thus improving the overall performance. Another contribution of this work is derivation of an off-set value for optimised neighbourhood set selection that enables more accurate detection while further reducing computational complexity. Simulation results confirm that the proposed scheme outperforms aforementioned algorithms in terms of BER performance and computational complexity in a continuously changing Rayleigh channel.

关键词： computational complexity least mean squares methods error statistics message passing MIMO communication Rayleigh channels 5G mobile communication signal detection efficient hybrid Neumann series MMSE assisted detection massive MIMO systems cutting edge technologies spectral efficiency M‐ MIMO systems individual signals composite signal optimal detectors approximate message passing variant detectors substantial importance decreased complexity amp algorithm nonlinear detectors vertical Bell‐ Labs layered space‐ iime bit error rate linear minimum mean square error detector BER performance Neumann series based MMSE detectors MMSE computational complexity hybrid Neumann series based MMSE detector detected signal neighbourhood selection algorithm optimised neighbourhood set selection reducing computational complexity

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A layered grouping random access scheme based on dynamic preamble selection for massive machine type communications

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Science China(Information Sciences) 2022年第7期65卷 269-270页

作者： Gaofeng CHENG Huan CHEN Pingzhi FAN Li LI Li HAO Information Coding & Transmission Key Lab of Sichuan Province CSNMT International Cooperation Research Centre of China Southwest Jiaotong University

Dear editor, The massive random access （RA） schemes in the existing literature are mainly grant-free approaches, which are supported by non-orthogonal multiple access [1–3], compressive sensing （CS） [4, 5], group paging [2, 6], and multichannel ALOHA [7]. However, they still face the challenges of high energy consumption and data overhead, especially in future ultra-dense Internet of Things （Io T） networks （> 10～6devices/km2） [8].

关键词： grant free layered grouping amp algorithm minimum preamble length mMTC

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Cross Validation Aided Approximated Message Passing algorithm for User Identification in mMTC

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IEEE COMMUNICATIONS LETTERS 2021年第6期25卷 2077-2081页

作者： Yang, Linjie Fan, Pingzhi Li, Li Ding, Zhiguo Hao, Li Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu 610031 Peoples R China Princeton Univ Dept Elect Engn Princeton NJ 08544 USA Univ Manchester Dept Elect & Elect Engn Manchester M13 9PL Lancs England

Recently, the approximate message passing (amp) algorithm is advocated for overcoming the active user identification challenge in grant free (GF) massive random access (RA). However, requiring the perfect knowledge of user sparsity is a quite strong assumption of amp algorithm in practical applications. Accordingly, we incorporate the cross validation (CV) method into the minimum mean square error (MMSE) denoiser based amp algorithm, resulting a basic CV aided amp algorithm (BCV-amp) that can adaptively estimate the user sparsity. In order to further reduce its complexity, an improved CV aided MMSE denoiser based amp algorithm (ICV-amp) is proposed. Simulation results show that both the BCV-amp and the ICV-amp algorithms achieve almost the same user identification performance as the well-known MMSE denoiser based amp algorithm, while the ICV-amp algorithm has essentially the same complexity as that of the latter.

关键词： Matching pursuit algorithms Estimation Complexity theory Approximation algorithms Message passing Sparse matrices Simulation Grant-free compressed sensing amp algorithm cross-validation

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Preamble Split Transmission and Joint Active User Detection for Massive Connectivity

Preamble Split Transmission and Joint Active User Detection ...

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IEEE/CIC International Conference on Communications in China (ICCC)

作者： Yang, Linjie Fan, Pingzhi Li, Li Hao, Li Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu 610031 Peoples R China

ISBN: (纸本)9781728173276

Low-power delay-tolerable services are very important applications of future large-scale IoT. Active user detection is its critical challenge. By exploiting the sparsity of the received signal, this challenge could be converted to a compressive sensing problem and hence solved by the approximated message passing (amp) algorithm. In order to improve the active user detection performance, a preamble split transmission (PST) random access (RA) scheme is proposed, in which each partition of the preamble is sent in different coherent time duration to achieve the time diversity. Correspondingly, a joint active user detection (JAUD) algorithm is proposed to jointly detect the distributed split preambles at the base station. Simulation results show that the proposed access scheme achieves a higher detection accuracy at the cost of a longer access delay. According to the delay-tolerable characteristic of the target network, this cost could be acceptable.

关键词： Grant-free Preamble split amp algorithm Compressed sensing

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Iterative Image Subset Scanning for Image Reconstruction From Sensor Signals 15

Iterative Image Subset Scanning for Image Reconstruction Fro...

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IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Cherubini, Giovanni Hurley, Paul Simeoni, Matthieu Kazemi, Sanaz IBM Res Zurich CH-8803 Ruschlikon Switzerland

ISBN: (纸本)9781509004805

Image reconstruction techniques from signals received by sensors find application in several fields, including radio interferometry for astronomical investigations and magnetic resonance imaging for medical applications. This paper presents a novel method for image reconstruction based on the iterative scanning of a region of interest. A modified approximate message passing (amp) algorithm is adopted to extract relevant image information with low computational complexity from signals received by sensors. The method is illustrated by simulations, with reference to the LOFAR radio interferometer, and compared in the case of radio astronomy with the CLEAN algorithm.

关键词： amp algorithm imaging sensor arrays

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