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13th IEEE Digital Signal Processing Workshop/5th IEEE Signal Processing Education Workshop

作者： Browning, J. Paul Fuhrmann, Daniel R. Rangaswamy, Muralidhar USAF Res Lab Wright Patterson AFB OH 45433 USA Michigan Technol Univ Dept Elect & Comp Engn Houghton MI 49931 USA

ISBN: (纸本)9781424436767

multiple-input multiple-output (MIMO) radar is a multiple aperture technology characterized by the ability to transmit diverse signals at each aperture. This is in contrast to traditional phased-array radar whereby a single signal is transmitted with a phase shift applied at each element to enable steering of the transmit beam. The hybrid MIMO phased-array radar (HMPAR) concept is an outgrowth of the monostatic MIMO construct, in which all sensors have the same view of the far-field target. In the HMPAR, the full transmit array is partitioned into sub-arrays which can be electronically steered in different directions and driven by separate transmit waveforms;furthermore the configuration of the array into sub-arrays can be changed. Here we explore the variety of transmit beampatterns that could be achieved using such a system.

关键词： multiple-input multiple-output beamforming radar

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A Particle Filter for Frequency Synchronization in MIMO-OFDM Systems

A Particle Filter for Frequency Synchronization in MIMO-OFDM...

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5th International Conference on Wireless Communications, Networking and Mobile Computing

作者： Zhang Jing Luo Han-wen Jin Rong-hong Zhang Jing Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200030 Peoples R China Shanghai Normal Univ Dept Commun Engn Shanghai Peoples R China

ISBN: (纸本)9781424436927

A particle filter algorithm is investigated to perform joint estimation of carrier frequency offset (CFO) and channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) wireless communication systems. The filter marginalizes out the channel parameters from the sampling space in sequential importance sampling, and propagates them with the Kalman filter. Then the importance weights of CFO particles are evaluated according to the imaginary part of error between measurement and estimate. Moreover, the varieties of particles are maintained by sequential importance resampling. Simulations demonstrate the algorithm can estimate the CFO and channel with high accuracy, as well as has some robustness to the channel model variation.

关键词： frequency offset orthogonal frequency division multiplexing multiple-input multiple-output channel estimation sequential Monte Carlo particle filter

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Performance Evaluation of MIMO Systems with Transmit Antenna Selection over Correlated Rayleigh Fading Channels

Performance Evaluation of MIMO Systems with Transmit Antenna...

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69th IEEE Vehicular Technology Conference

作者： Xu, Rongtao Zhong, Zhangdui Chen, Jiann-Mou Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing Peoples R China Hwa Hsia Univ Technol Dept Assets & Property Management Taipei Taiwan

ISBN: (纸本)9781424425167

In this paper, we investigate MIMO systems with transmit antenna selection over an intra-class correlated Rayleigh fading channel. In our study, one single transmit antenna with an aim to maximizing the total received signal-to-noise ratio (SNR) is selected for transmission, while it is assumed that the receive side use all the available antennas. Using binary-phase-shift-keying (BPSK) modulation as an illustration, we derive the exact bit error rates (BERs) of two diversity schemes, namely transmit antenna selection and full complexity schemes. Moreover, we compare the asymptotic performance of the two diversity schemes analytically. The effect of correlation among the sub-channels on the SNR degradation is also determined in terms of the correlation coefficient and the number of transmit/receive antennas. Finally, results show that the transmit antenna selection scheme can achieve better performance than the full complexity scheme at the expense of a small amount of feedback information from the receiver.

关键词： multiple-input multiple-output transmit antenna selection intra-class correlation Rayleigh fading

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Robust Recursive Two-Dimensional Channel Estimators for the MIMO-OFDM Systems

Robust Recursive Two-Dimensional Channel Estimators for the ...

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1st International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace and Electronic Systems Technology

作者： Golovins, Eugene Ventura, Neco Univ Cape Town Dept Elect Engn ZA-7701 Rondebosch South Africa

ISBN: (纸本)9781424440665

MIMO-OFDM systems operating in the wireless doubly-selective channels rely on the pilot-assisted transmissions to acquire channel state information. Application of the two-dimensional filtering algorithms to channel estimation in the MIMO configurations is challenging due to the complexity considerations. Furthermore, different pilot structures employed in different spatial links necessitate development of scalable and reconfigurable estimator structures. The estimation scheme should also be robust to the changes in channel statistics and operation mode restrictions. To address these problems, robust estimator architecture is presented, which is based on the transform-domain processing and separable adaptive filtering modules.

关键词： multiple-input multiple-output multipath mean square error forgetting factor

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PARTICLE SWARM OPTIMISATION AIDED SEMI-BLIND JOINT MAXIMUM LIKELIHOOD CHANNEL ESTIMATION AND DATA DETECTION FOR MIMO SYSTEMS

PARTICLE SWARM OPTIMISATION AIDED SEMI-BLIND JOINT MAXIMUM L...

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15th IEEE/SP Workshop on Statistical Signal Processing

作者： Palally, H. R. Chen, S. Yao, W. Hanzo, L. Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

ISBN: (纸本)9781424427093

A novel scheme of semi-blind joint maximum likelihood (ML) channel estimation and data detection is proposed for multiple-input multiple-output (MIMO) systems by decomposing the joint ML optimisation over channel and data into an iterative two-level optimisation loop. Particle swarm optimisation (PSO) is invoked at the upper level to identify the unknown MIMO channel while an enhanced ML sphere detector is used at the lower level to detect the transmitted data. The scheme is semi-blind as a minimum pilot overhead is employed to aid the initialisation of the PSO based channel estimator.

关键词： multiple-input multiple-output joint maximum likelihood estimation particle swarm optimisation

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Performance Evaluation of MIMO-OFDM with Twin Turbo Decoder

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IEICE TRANSACTIONS ON COMMUNICATIONS 2009年第1期E92B卷 228-236页

作者： Hatakawa, Yasuyuki Miyazaki, Noriaki Suzuki, Toshinori KDDI R&D Labs Inc Fujimino 3568502 Japan

This paper proposes Twin Turbo (T2) MIMO-OFDM (multiple input multiple output-Orthogonal Frequency Division multiplexing). The advanced iterative decoder, called the T2 decoder, decreases the transmission error rate compared to conventional turbo decoders because it uses the correlation information among the bits mapped on an identical symbol of multi-level modulation and updates the channel reliability. When T2 is applied to a MIMO-OFDM, the required symbol energy to noise power density ratio (E-s/N-0) can be reduced more effectively than when T2 is applied to SISO (Single input Single output). This is because T2 can use the correlation among the bits not only mapped on an identical symbol but also transmitted from different antennas. Moreover, T2 achieves good performance in a correlated MIMO channel because the average minimum squared Euclidean distances between symbol replica candidates consisting of signals transmitted from multiple transmitter antennas are reduced. Computer simulations verify that the required E-s/N-0 of T2 MIMO-OFDM using 16QAM is 1.9 dB lower than that of a conventional turbo decoder when the correlation coefficients of transmitter and receiver antennas are 0.8. A computational complexity analysis clarifies the relation between the increase in computational complexity and the reduction in the required E-s/N-0.

关键词： iterative decoder multiple-input multiple-output FEC (Forward Error Correction) correlated channel turbo coding computational complexity

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Improved Codebook Design for Precoding of OSTBCs in Correlated MIMO Channels with Finite Rate Feedback

Improved Codebook Design for Precoding of OSTBCs in Correlat...

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European Wireless Conference

作者： Lu Lu Gang Wu Haiyang Huang Shaoqian Li Fan Sun Communication Theory Lab Royal Institute of Techonology (KTH) National Key Lab of Communications University of Electronic Science and Technology of China National Key Lab of Communications University of Electronic Science and Technologyof China Ericsson Research

In this paper, we propose a novel codebook-based precoding design for orthogonal space-time block codes (OSTBCs) over multiple-input multiple-output (MIMO) channels with finite rate feedback. The proposed approach aims at providing better system performance by utilizing the property of OSTBCs and the prior information of the statistical antenna correlation. Under a new way of controlling the average transmit power, a novel structure of precoding matrix is given, which is different from the unitary precoding. Moreover, with the information of the transmit correlation matrix, the codebook design is generalized to correlated channels. Both theoretical analyses and simulation results are provided.

关键词： Precoding multiple-input multiple-output Orthogonal space-time block codes Antenna correlation Finite rate feedback Codebook

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Reduced-complexity equalization techniques for ISI and MIMO wireless channels in iterative decoding

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2008年第2期26卷 256-268页

作者： Wong, Kitty K. Y. McLane, Peter J. Queens Univ Dept Elect & Comp Engn Kingston ON K7L 3N6 Canada

Two reduced-complexity soft-input soft-output trellis decoding techniques are presented in this paper for equalizing single-input single-output InterSymbol Interference (ISI) channels and multiple-input multiple-output (MIMO) frequency selective fading channels. Given a trellis representing an ISI channel, the Soft-output M-Algorithm (SOMA) reduces the complexity of equalization by retaining only the best M survivors at each trellis interval. The remaining survivors are discarded. The novelty of the SOMA is the use of discarded paths to obtain soft-information. Through a simple update-and-discard procedure, the SOMA extracts reliable soft-information from discarded paths which enables a large trellis to be successfully decoded with a relatively small value of M. To decode a trellis representing a MIMO frequency selective fading channel, two challenges are faced. Not only that the trellis has a large number of states, the number of branches per trellis interval is also enormous. The Soft-output Trellis/Tree M-Algorithm (SOTTMA) expands each trellis interval into a tree-like structure and performs the M-algorithm twice: once at each trellis interval to reduce the number of states and the other at each tree sub-level to remove unwanted branches. With the proposed technique, high-order trellises with million of branches per interval can be decoded with modest complexity.

关键词： equalization Intersymbol Interference M-algorithm multiple-input multiple-output sequential decoding soft-information turbo-detection

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Semi-Blind Adaptive Spatial Equalization for MIMO Systems with High-Order QAM Signalling

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2008年第11期7卷 4486-4491页

作者： Chen, S. Yao, W. Hanzo, L. Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

This contribution investigates semi-blind adaptive spatial filtering or equalisation for multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation (QAM) signalling. A minimum number of training symbols, equal to the number of receivers (we assume that the number of transmitters is no more than that of receivers), are first utilized to provide a rough least squares channel estimate of the system's MIMO channel matrix for the initialization of the spatial equalizers' weight vectors. A constant modulus algorithm aided soft decision-directed blind algorithm, originally derived for blind equalization of single-input single-output and single-input multiple-output systems employing high-order QAM signalling, is then extended to adapt the spatial equalizers for MIMO systems. This semi-blind scheme has a low computational complexity, and our simulation results demonstrate that it converges fast to the minimum mean-square-error spatial equalization solution.

关键词： multiple-input multiple-output quadrature amplitude modulation spatial equalisation semi-blind adaptive algorithm concurrent constant modulus algorithm and soft decision-directed scheme

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Low-complexity MAP channel estimation for mobile MIMO-OFDM systems

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2008年第3期7卷 774-780页

作者： Gao, Jie Liu, Huaping Oregon State Univ Sch Elect Engn & Comp Sci Corvallis OR 97331 USA

This paper presents a reduced-complexity maximum a posteriori probability (MAP) channel estimator with iterative data detection for orthogonal frequency division multiplexing (OFDM) systems over mobile multiple-input multiple-output channels. The optimal MAP estimator needs to invert an N N-T x N N-T data-dependent matrix each in OFDM symbol interval, where N is the number of subcarriers and N-T is the number of transmit antennas. We derive an expectation maximization (EM) algorithm with low-rank approximation to avoid inverting large-size matrices, and thus drastically reduce the receiver complexity. In the iterative process, channel parameters are initially obtained by a least square (LS) estimator for temporary symbol decisions. Then, inter-carrier interference (ICI) due to fast fading is approximated and canceled. Finally, the temporary symbol decisions and the ICI-canceled received signals are processed by the EM-based MAP estimator to refine the channel state information for improved detection. The proposed scheme achieves about 2 dB gain over the LS scheme in channels with medium to high normalized Doppler shifts.

关键词： multiple-input multiple-output orthogonal frequency division multiplexing fast fading inter-carrier interference maximum a posteriori probability estimation low-rank approximation

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