Multiple-input Multiple-output Multiplexing Systems Research Articles

Doppler Division Multiplexed Multiple-Input–Multiple-Output Imaging Using Cascaded Millimeter-Wave Radars

Radar-based near-field 3-D imaging technology has recently attracted increasing attention in the field of security systems. This article presents a novel multiple-input–multiple-output (MIMO) synthetic aperture radar imaging algorithm for security checkpoints attached to a moving walkway. The proposed algorithm is characterized by transmitting-signal multiplexing on the Doppler frequency domain, which allows for a reduced data acquisition time compared with that of conventional time-division multiplexed MIMO systems and therefore achieves the image reconstruction of dangerous objects with smaller motion errors. This algorithm can be applied to 1-D antenna array systems, and image reconstruction is based on a back-projection algorithm with some modifications. The mathematical derivation of the algorithm and its advantages and disadvantages in comparison with those of a conventional system are detailed in this article. Details of numerical simulation of a point target as well as the experimental results of image reconstruction of a pinball and toy gun, using cascaded millimeter-wave sensors, are also presented for verifying the performance of the algorithm.

Characteristic Mode Analysis of ESPAR for Single-RF MIMO Systems

A systematic method based on the Theory of Characteristic Modes (TCM) for finding orthogonal radiation patterns of any electronically steerable parasitic array radiator (ESPAR) is described. This method can be useful for designing single-RF front-end multiple-input multiple-output (MIMO) systems in which orthogonal patterns can be utilized as a basis set for space modulation (SM) or full multiplexed MIMO systems. The method is based on the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> -port formulation of TCM and is not restricted to antenna type or array configuration. It can also provide closed formed solutions for the antenna element currents required to generate the orthogonal patterns. In addition an approach to finding the required load reactances in ESPAR for generating the orthogonal patterns is provided and is based on the quasi-Newton method utilizing a closed form expression for the initial approximate solution. Approximate estimation of the effective aerial degrees of freedom of the ESPARs is also discussed. Two simulation examples of ESPARs, a 4-element linear dipole array and an 8-element rectangular planar inverted-F antenna array, using SM as well as full multiplexed MIMO are provided, demonstrating the effectiveness of the proposed method.

Coverage Performance in MIMO-ZFBF Dense HetNets with Multiplexing and LOS/NLOS Path-Loss Attenuation

The performance of multiple-input multiple-output (MIMO) multiplexing heterogenous cellular networks are often analyzed using a single-exponent path-loss model. Thus, the effect of the expected line-of-sight (LOS) propagation in densified settings is unaccounted for, leading to inaccurate performance evaluation and/or inefficient system design. This is due to the complexity of LOS/non-LOS models in the context of MIMO communications. We address this issue by developing an analytical framework based on stochastic geometry to evaluate the coverage performance. We focus on the zero-forcing beamforming where the maximum signal-to-interference ratio is used for cell association. We analytically derive the coverage. We then investigate the cross-stream interference correlation, and develop two approximations of the coverage: Alzer Approximation (A-A) and Gamma Approximation (G-A). The former is often used in the single antenna and single-stream MIMO. We extend A-A to a MIMO multiplexing system and evaluate its utility. We show that the inverse interference is well-fitted by a Gamma random variable, where its parameters are directly related to the system parameters. The accuracy and robustness of G-A is higher than that of A-A. We observe that depending on the multiplexing gain, it is possible to attain the best coverage probability by proper densification.

Low-Latency Lattice Reduction Based on Dual-Basis Updates for High-Dimensional MIMO Streams

Lattice reduction (LR) techniques have been widely adopted to enhance the detection performance with low additional complexity in spatial multiplexed multiple-input multiple-output (MIMO) systems. However, in large MIMO systems, the required number of iterations and the corresponding latency and complexity of the existing LR algorithms increase exponentially. In this brief, we propose a low-latency LR method based on Seysen's algorithm (SA) for high-dimensional MIMO systems. The proposed algorithm introduces dual-index selection and simultaneously updates two basis pairs without the recalculation of metrics to reduce the latency and complexity. Additionally, it introduces a reduced candidate set to decrease the computational complexity and memory usage. The numerical results demonstrate that the proposed LR-aided linear detector outperforms the conventional Lenstra-Lenstra-Lovász algorithm. Furthermore, the performance of the proposed method is comparable to that of SA; it achieves reductions of 40% and 12.5% in the number of iterations and computational complexity, respectively. The proposed 65-nm CMOS implementation achieves an overall latency of 196 ns and a throughput of 25.5 M matrix/s with a clock frequency of 357.1 MHz for $8 \times 8$ MIMO systems.

Achieving optimum performance with ZF detector by using a novel precoding approach in spatial multiplexing MIMO systems

Zero forcing (ZF) detector is unable to exploit all of the available diversity order of a spatial multiplexing multiple-input multiple-output (MIMO) systems. Thus, its performance is clearly inferior to the maximum likelihood (ML) detector. However, this is no longer true if the MIMO channel matrix is orthogonal. Motivated by this statement, in this paper, we propose a novel precoding approach for channel matrix orthogonalization for spatial multiplexing MIMO systems. In general, at the transmitter, we first find out the precoding matrix that transforms a MIMO channel matrix into an orthogonal matrix. After that, at the receiver, the ZF detector applied to the orthogonal channel matrix obtain the same optimum performance of ML detector. Simulation results show that the proposed approach achieves the optimum performance with reduced complexity at the expense of a small increase in the total average transmitted power.

Performance of decremental antenna selection algorithms for spatial multiplexing MIMO systems with linear receiver over correlated fading channels

This study proposes enhanced suboptimal transmit antenna selection algorithms based on eigenvalue decomposition for spatial multiplexing multiple-input multiple-output (MIMO) systems with linear receivers over correlated MIMO flat fading channels. The suboptimal algorithms presented are based on the n th rooting of maximal ratio combined full channel matrix, in which the condition number significantly decreases, and the decremental selection strategy. The first algorithm exploits channel gains obtained by the channel scaling technique, and is further simplified with much lower complexity in the second algorithm. It is shown that they outperform other suboptimal algorithms in terms of bit error rate minimisation under doubly correlated channels. Moreover, their computational complexities are compared with those of other fast antenna selection algorithms. In addressing channel estimation errors on doubly correlated channels, the proposed decremental selection approaches are shown to offer more robustness than other algorithms.

How significant is the assumption of the uniform channel phase distribution on the performance of spatial multiplexing MIMO system?

Spatial multiplexing (SMX) multiple-input multiple-output (MIMO) systems are promising candidates to enhance the achievable throughput and the overall spectral efficiency in future wireless systems. Performance studies of these systems over different channel conditions assume simplified models for the channel phase distribution. This paper highlights the impact of the channel phase distribution assumption on the performance of SMX MIMO systems. The Nakagami-m and the $$\eta -\mu$$ fading channels are considered in this study. In existing literature, performance studies of SMX MIMO systems over Nakagami-m fading channel assume uniform phase distribution. Though, it has been reported recently that the Nakagami-m channel phase distribution is not uniform. In this article, we show that the assumption of the channel phase distribution has a major impact on the performance of SMX MIMO systems. The obtained results demonstrate that the performance of SMX MIMO systems significantly varies with different channel phase distributions. Furthermore, it is shown that uniform assumption of channel phase distribution is incorrect and leads to erroneous conclusions. Detailed performance analysis for more accurate channel models are provided and results are sustained through Monte-Carlo simulations.

Precoded spatial multiplexing MIMO system with spatial component interleaver.

In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.

Joint Modulation Classification and Antenna Number Detection for MIMO Systems

Noncooperative classification of the modulation type of communication signals finds application in both civilian and military contexts. Existing modulation classification methods for multiple-input multiple-output (MIMO) communication systems commonly require a priori information on the number of transmit antennas employed by the multiantenna transmitter, which, in most of the noncooperative scenarios involving modulation classification, is unknown and needs to be blindly extracted from the received signal. Since the problems of MIMO modulation classification and detection of the number of transmit antennas are highly coupled, we propose a decision theoretic approach for spatial multiplexing MIMO systems that considers these two tasks as a joint multiple hypothesis testing problem. The proposed method exhibits a high performance even in moderate to low SNR regimes while requiring no a priori knowledge of the channel state information and the noise variance.

Performance Improvement in Spatially Multiplexed MIMO Systems over Weibull-Gamma Fading Channel

AbstractIn multiple-input multiple-output (MIMO) systems, spatial demultiplexing at the receiver has its own significance. Thus, several detection techniques have been investigated. There is a tradeoff between computational complexity and optimal performance in most of the detection techniques. One of the detection techniques which gives improved performance and acceptable level of complexity is ordered successive interference cancellation (OSIC) with minimum mean square error (MMSE). However, optimal performance can be achieved by maximum likelihood (ML) detection but at a higher complexity level. Therefore, MMSE-OSIC with candidates (OSIC

Efficient and Low Complexity Modulation Classification Algorithm for MIMO Systems

This study develops a feature-based Automatic Modulation Classification (AMC) algorithm for spatially multiplexed Multiple-Input Multiple-Output (MIMO) systems employing two Higher Order Cumulants (HOCs) of the estimated transmit signal streams as discriminating features and a multiclass Support Vector Machine (SVM) as a classification system. The algorithm under study has the capability to recognize a wide range of modulation schemes without any prior information about the channel state. The classification performance of the proposed algorithm was evaluated via extensive simulations under different operating conditions and was also compared with the one obtained with the optimal Hybrid Likelihood Ratio Test (HLRT) approach. The results show that the proposed algorithm is capable of classifying the considered modulation schemes with good classification accuracy and can achieve performance comparable to that of the HLRT approach while having a significantly lower computational complexity.

Capacity analysis of spectrum sharing spatial multiplexing MIMO systems

This paper considers a spectrum sharing (SS) multiple-input multiple-output (MIMO) system operating in a Rayleigh fading environment. First the capacity of a single-user SS spatial multiplexing system is investigated in two scenarios that assume different receivers. To explicitly show the capacity scaling law of SS MIMO systems, some approximate capacity expressions for the two scenarios are derived. Next, we extend our analysis to a multiple user system with zero-forcing receivers (ZF) under spatially-independent scheduling and analyze the sum-rate. Furthermore, we provide an asymptotic sum-rate analysis to investigate the effects of different parameters on the multiuser diversity gain. Our results show that the secondary system with a smaller number of transmit antennas Nt and a larger number of receive antennas Nr can achieve higher capacity at lower interference temperature Q, but at high Q the capacity follows the scaling law of the conventional MIMO systems. However, for a ZF SS spatial multiplexing system, the secondary system with small Nt and large Nr can achieve the highest capacity throughout the entire region of Q. For a ZF SS spatial multiplexing system with scheduling, the asymptotic sum-rate scales like Ntlog2(Q(KNtNp−1)/Nt), where Np denotes the number of antennas of the primary receiver and K represents the number of secondary transmitters.

Precoded Spatial Multiplexing MIMO Systems in Time- Varying Fading Channel

Conventional precoded spatial multiplexing multiple-input multiple-output (MIMO) systems using limited feedback are mainly based on the notion of time invariant channels throughout transmission. Consequ-encely, the precoding matrix can be found during the training symbols and used over the subsequent data symbols. In this paper, a more practical system where the channel varies from one block of symbols to another is considered. In such scenario, the precoding matrix designed at the receiver based on the previous training symbols becomes outdated, which results in significant system performance degradation. In order to avoid this problem, and reduce performance degradation, we propose the use of a Kalman filter linear predictor at the receiver to provide the transmitter with the precoding matrix for the next block of symbols. The performance of this method is assessed using computer simulation, and the obtained results for the proposed channel prediction demonstrate improved bit error rate performance for time-varying Rayleigh fading channels. 

Improvement of Rotation Matrix Based Differential Limited Feedback with DFT Codebook and Its Application in CoMP Environment

Recently, exploiting the temporal correlation of slowly varied multiple input multiple output (MIMO) channels to further improve the system performance or the feedback efficient in MIMO wireless communication systems with limited feedback has been investigated in many papers. Among them, T. Kim et al. proposed a rotation matrix based differential feedback scheme which is shown to have good performance with regard to the system throughput for spatial multiplexing MIMO systems. Although the rotation matrix codebook and the precoding codebook in their scheme are optimally constructed, they are not fit for a practical system due to the structure constraints. In this paper, we propose to replace the optimal codebook in the rotation matrix based differential feedback scheme with discrete Fourier transform (DFT) structured codebook, and propose a search-based method to decrease the performance degradation induced by the un-optimality of the DFT codebook. In addition, the modified algorithm is also applied to a per-cell codebook based coordinated multi-point (CoMP) transmission system to verify its applicability to different MIMO scenarios. Simulation results show the effectiveness of our modified scheme. Index Terms—Temporal correlation, differential feedback, DFT codebook, spatial multiplexing 

Transmitter-based Inter-channel Interference Cancellation and Prerake Combining for UWB Spatial Multiplexing MIMO Systems

In this paper, an ultra-wideband (UWB) spatial multiplexing (SM) multiple input multiple output (MIMO) system exploiting a transmitter-side preprocessing technique is presented. Its transmitter consists of a symbol-based zero-forcing (ZF) inter-channel interference canceller followed by prerake combiners that collect the energies of L resolvable multipath components and its receiver employs correlators. The improved transceiver scheme based on transmit preprocessing and correlation at the receiver is analyzed in a log-normal multipath fading channel. It is shown that it can provide the same diversity order of (LN−M+1) as the UWB SM MIMO system with prerakes in the transmitter and a ZF filter in the receiver for N transmit antennas, M receive antennas, and L resolvable paths. The theoretical and simulated error performances of the presented transmit ZF and prerake combining scheme are also evaluated and compared with those of the UWB SM MIMO systems using prerake combiners at the transmitter and a ZF detector at the receiver.

SNR‐dependent radius control sphere detection for MIMO systems and relay networks

AbstractA new sphere decoder algorithm for uncoded spatial multiplexing multiple‐input multiple‐output (MIMO) systems is proposed. It overcomes the drawbacks of traditional sphere decoders: variable complexity and high complexity in low signal‐to‐noise ratios (SNRs). Its main novelty lies in scaling the search radius by a heuristic SNR‐dependent factor. This new SNR‐dependent radius control sphere decoder offers near maximum likelihood performance over the entire range of SNRs, while keeping its complexity roughly constant. This algorithm also incorporates channel ordering to save complexity. To quantify the variability of complexity, the normalised variance of the complexity is evaluated. This algorithm is also extended for joint iterative detection and decoding in coded MIMO systems and for MIMO‐relay networks. Simulation results and theoretical analysis demonstrate the benefits of the proposed algorithm.Copyright © 2013 John Wiley &amp; Sons, Ltd.

Successive interference cancelation and MAP decoding for mobile MIMO OFDM systems and their convergence behavior

Turbo equalization schemes based on minimum mean square error criteria available in the literature for multiple-input multiple-output (MIMO) systems are computationally expensive, as they require a relatively large matrix inversion. In this article, we propose a suboptimal, successive interference cancelation (SIC)-based maximum a posteriori (MAP) decoding in doubly dispersive channels for orthogonal frequency division multiplexing (OFDM) MIMO systems (SIC-MAP-MIMO). SIC-MAP-MIMO leverages on the soft feedback symbol estimate to remove the intercarrier interference and coantenna interference from the received data thus making the subsequent MAP decoding simple. Extrinsic information transfer chart analysis supplemented with numerical simulation results show that SIC-MAP-MIMO achieves comparable BER performance to similar equalization schemes but with significant computational savings.

Joint Detection and Decoding for MIMO Systems Using Convolutional Codes: Algorithm and VLSI Architecture

In this paper, we present a novel approach to perform joint detection and decoding for spatial multiplexing multiple-input multiple-output (MIMO) systems which utilize convolutional codes. The bit error rate (BER) performance of the proposed approach is significantly better than that of systems which utilize separate detection and decoding blocks. Formal algorithms with two possible system setups are presented and their performance documented. In particular, for a reference 4 × 4, 16-QAM system using a rate 1/2 convolutional code with generator polynomial [247, 371] and a constraint length of 8, improvements in signal-to-noise ratio (SNR) of 2.5 dB and 3 dB are achieved over conventional soft decoding at a BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> . The proof of concept VLSI architecture for one algorithm is provided and a novel way to reduce memory usage is demonstrated. Results indicate that better performance over conventional systems is achievable with comparable hardware complexity. The proposed design was synthesized and layout with 65-nm CMOS technology at 181-MHz clock frequency. An average throughput of 216.9 Mbps at a SNR of 13 dB with area equivalent to 553 Kgates was achieved.

QRD-Based Antenna Selection for ML Detection of Spatial Multiplexing MIMO Systems: Algorithms and Applications

Antenna selection is a simple but effective technique to enhance the performance of a spatial multiplexing multiple-input-multiple-output (MIMO) system. The selection criterion depends on the detector used at the receiver. For the maximum-likelihood detector, the criterion is to maximize the free distance. However, an exhaustive search is required to derive the distance, and the computational complexity can be prohibitively high. To avoid the exhaustive search, a lower bound of the free distance derived with the singular value decomposition (SVD) was then developed. This bound only involves the smallest singular value of the channel matrix, and its maximization can easily be conducted. An alternative lower bound of the free distance with the QR decomposition (QRD) was also derived in the literature. In this paper, we first propose a QRD-based selection method maximizing the lower bound. With some matrix properties, we theoretically prove that the lower bound yielded by the QRD is tighter than that by the SVD. We then propose a basis transformation method so that the lower bound yielded by the QRD can further be tightened. As a result, the QRD-based selection method can achieve near optimum performance. Finally, we extend the use of the proposed methods to other applications, such as receive antenna selection, joint transmit/receive antenna selection, and antenna selection in MIMO relay systems. Simulations show that the proposed selection methods can significantly outperform existing methods.

Impact of Mutual Coupling and Polarization of Antennas on BER Performances of Spatial Multiplexing MIMO Systems

This paper is aimed at studying the impacts of mutual coupling, matching networks, and polarization of antennas on performances of Multiple-Input Multiple-Output (MIMO) systems employing Spatial Multiplexing (SM). In particular, the uncoded average Bit Error Rate (BER) of MIMO systems is investigated. An accurate signal analysis framework based on circuit network parameters is presented to describe the transmit/receive characteristics of the matched/unmatched antenna array. The studied arrays consist of matched/unmatched compact copolarization and polarization diversity antenna array. Monte-Carlo numerical simulations are used to study the BER performances of the SM MIMO systems using maximum-likelihood and/or zero-forcing detection schemes. The simulation results demonstrate that the use of matching networks can improve the BER performance of SM MIMO systems significantly, and the BER performance deterioration due to antenna orientation randomness can be compensated by use of polarization diversity antenna arrays.