Spatial Multiplexing Multiple-input Multiple-output Systems Research Articles

Multi-Array Visible-Light Optical Generalized Spatial Multiplexing–Multiple Input Multiple-Output System with Pearson Coefficient-Based Antenna Selection

To address the limitations of poor environmental adaptability, unsatisfactory bit-error performance, and high complexity of conventional antenna selection algorithms applied to a multi-array visible-light optical generalized spatial multiplexing–multiple-input multiple-output (OGSMP-MIMO) system, an OGSMP-MIMO system based on Pearson coefficient antenna selection is proposed. The algorithm adopts the correlation of Pearson coefficients among photoelectric detector (PD) terminals at different positions and active transmit antennas to select the optimal antenna combination without relying on the accuracy of channel estimation, for realizing the multiplexing of the time and space domains, and to improve the bit-error performance. Finally, experiments were conducted to verify the feasibility of the antenna selection algorithm, based on the Pearson coefficients. The results indicated that when the bit-error rate reached 10−6, using the antenna selection algorithm based on the Pearson coefficient, the signal-to-noise ratio was improved by 2.7 dB and 3.7 dB when compared with the norm-based antenna and random selection algorithms, respectively. In addition, increasing the number of active transmitting antennas can improve the transmission rate; however, the bit-error performance will be compromised. In the same modulation mode, increasing the number of transmitting antennas will reduce the bit-error performance.

Complex-amplitude radiation-type metasurface enabling beamform-controlled energy allocation

Fifth-generation (5G) communication requires spatial multiplexing multiple-input multiple-output systems with integrated hardware. With the increase in the number of users and emergence of the Internet of Things devices, complex beamforming devices have become particularly important in future wireless systems to meet different communication requirements, where independent amplitude and phase modulations are urgently required for integrated beamforming devices. Herein, by utilizing the constructive interference between multiple geometric-phase responses, the mathematical relation for decoupling amplitude and phase modulations in the radiation-type operational mode is derived. Based on this strategy, complex-amplitude radiation-type metasurfaces (RA-Ms) are implemented, with an integrated feeding network. Such metasurfaces exploit full 2π phase modulation and tailorable radiation amplitude in the circular polarization state. Meanwhile, a complex-amplitude retrieval method is developed to design the RA-Ms, enabling precise beamforming performances. On this basis, several functional devices based on the complex-amplitude RA-Ms, including energy-allocable multi-router, shape-editable beam generator, and complex beamformer, are demonstrated in the microwave region. The amplitude-phase decoupling mechanism with the retrieval method merges amplitude and phase modulations, and energy distribution into one compact and integrated electromagnetic component and may find applications in multi-target detection, 5G mobile communication, and short-range ground-to-sea radar.

Performance analysis of sparse code multiple access with variant MIMO techniques

Performance analysis, in terms of the (ABER), mutual information and theoretical capacity, for sparse code multiple access (SCMA) with variant multiple-input multiple-output (MIMO) techniques is presented and thoroughly discussed in this article. In particular, novel combination between space modulation techniques (SMTs) and SCMA is proposed and analyzed. As well, the performance of spatial multiplexing (SMX)-SCMA MIMO system is presented and used as a benchmark for the sake of comparison. Additionally, several designs for the mother constellation (MC) matrices are studied and their impact on the performance of the considered MIMO system is investigated. It is reported that different MC designs can lead to different performance and the performance of both MIMO systems can be optimized based on the considered codebook design. The closed-form analytical upper bound of the ABER over Rayleigh, Rician and Nakagami-m fading channels is derived and corroborated through Monte Carlo simulation results. Also, the theoretical capacity and the mutual information for SCMA–SMTS and SCMA–SMX MIMO systems are derived and studied over the considered fading channels. Monte-Carlo simulation results reveal that the derived capacity is the true upper bound for the simulated mutual information results and the conditions under which the capacity can be achieved are discussed. The performances of the considered SCMA–MIMO systems are compared to (OFDMA)–MIMO systems and significant gains are reported.

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.

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.

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.

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 

A Low Complexity Modulation Classification Algorithm for MIMO Systems

A novel algorithm is proposed for automatic modulation classification in multiple-input multiple-output spatial multiplexing systems, which employs fourth-order cumulants of the estimated transmit signal streams as discriminating features and a likelihood ratio test (LRT) for decision making. The asymptotic likelihood function of the estimated feature vector is analytically derived and used with the LRT. Hence, the algorithm can be considered as asymptotically optimal for the employed feature vector when the channel matrix and noise variance are known. Both the case with perfect channel knowledge and the practically more relevant case with blind channel estimation are considered. The results show that the proposed algorithm provides a good classification performance while exhibiting a significantly lower computational complexity when compared with conventional algorithms.

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.

RF beamforming for MIMO cognitive user

Using Multiple Input Multiple Output (MIMO) architecture in cognitive radio (CR) secondary users improves the system performance in terms of interference cancellation and data rate enhancement but at the expense of adding complexity and cost. A solution to reduce this complexity is employing radio frequency (RF) beamforming networks at the transmitter/receiver front-ends. In this paper, we consider a MIMO secondary user equipped with such RF beamforming network. Moreover, we find the transmit/receive optimum RF beamforming network for a MIMO spatial multiplexing system. We evaluate the performance of the optimally designed RF beamforming technique over a Rician channel via computer simulations. The simulation results are assessed for different RF beamforming structures and the number of primary transmitters which cause interference on the secondary receiver.

Low-SNR Analysis of MIMO Weibull Fading Channels

The capacity performance of multiple-input multiple-output (MIMO) systems in Weibull fading channels has not been properly addressed in the literature. In this paper, we consider three MIMO architectures, namely spatial-multiplexing (SM) MIMO systems with optimal and minimum mean square error (MMSE) receivers as well as orthogonal space-time block-codes (OSTBC) MIMO systems, that operate over Weibull fading channels. Since the capacity analysis at arbitrary Signal-to-Noise ratios (SNRs) is intractable, we focus on the low-SNR regime which is characterized by the minimum energy per information bit to reliably convey any positive rate and the wideband slope. For these two metrics, new closed-form expressions are derived which enable us to perform a detailed comparative study of the considered configurations and assess MIMO capacity in Weibull fading channels.

Taps Delayed Lines Architecture Based on Linear Transmit Zero-Forcing Approach for Ultra-Wide Band MIMO Communication Systems

In this paper, a transmitter-based multipath processing and inter-channel interference (ICI) cancellation scheme for a ultra-wideband (UWB) spatial multiplexing (SM) multiple input multiple output (MIMO) system is presented. It consists of taps delayed lines and zero-forcing (ZF) filters in the transmitter and correlators in the receiver. For a UWB SM MIMO system with N transmit antennas, M receive antennas, and Q resolvable multipath components, the BER performance of a linear transmit ZF scheme is analyzed in a log-normal fading channel and also compared with that of a receiver-based ICI rejection approach. It is found that when M <TEX>${\leq}$</TEX> N, the transmit ZF processing approach outperforms the ZF receiver while making the mobile units low-cost and low-power.

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.

DESIGN AND IMPLEMENTATION OF SYMBOL DETECTOR FOR MIMO SPATIAL MULTIPLEXING SYSTEMS

In this paper, we propose an efficient symbol detection algorithm for multiple-input multiple-output spatial multiplexing (MIMO-SM) systems and present its design and implementation results. By enhancing the error performance of the first detected symbol that causes error propagation, the proposed algorithm achieves a considerable performance gain compared with the conventional sorted QR decomposition (SQRD) based detection and the ordered successive detection (OSD) algorithms. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by a simulation. In the case of a 16QAM MIMO-SM system with 4 transmit and 4 receive (4 × 4) antennas, at BER = 10-3 the proposed algorithm results in a gain improvement of about 2.5–13.5 dB over the previous algorithms. The proposed detection algorithm was designed in a hardware description language (HDL) and synthesized to gate-level circuits using 0.18 μm 1.8 V CMOS standard cell library. The results show that the proposed algorithm can be implemented without increasing the hardware costs significantly.

Multi-branch successive interference cancellation for MIMO spatial multiplexing systems: design, analysis and adaptive implementation

In this study, the authors propose a novel successive interference cancellation (SIC) strategy for multiple-input multiple-output spatial multiplexing systems based on a structure with multiple interference cancellation branches. The proposed multi-branch SIC (MB-SIC) structure employs multiple SIC schemes in parallel and each branch detects the signal according to its respective ordering pattern. By selecting the branch which yields the estimates with the best performance according to the selection rule, the MB-SIC detector, therefore, achieves higher detection diversity. The authors consider three selection rules for the proposed detector, namely, the maximum likelihood (ML), the minimum mean square error and the constant modulus criteria. An efficient adaptive receiver is developed to update the filter weight vectors and estimate the channel using the recursive least squares algorithm. Furthermore a bit error probability performance analysis is carried out. The simulation results reveal that the authors&apos; scheme successfully mitigates the error propagation and approaches the performance of the optimal ML detector, while requiring a significantly lower complexity than the ML and sphere decoder detectors.

ISIC-MMSE detector for BICM SM-MIMO systems with estimated CSI

We study the iterative soft interference cancellation-minimum mean square error filtering (ISIC-MMSE) detector with estimated channel state information (CSI) for bit-interleaved coded modulation (BICM) spatial multiplexing multiple input multiple output (SM-MIMO) systems. By considering the channel estimation errors in all detection modules, we propose a modified ISIC-MMSE detector which considerably outperforms the conventional ISIC-MMSE detector in terms of performance and transmission rate with only moderate complexity increase.

Enhanced Groupwise Detection with a New Receive Combiner for Spatial Multiplexing MIMO Systems

In this letter, we propose a new groupwise receive combiner design for multiple-input multiple-output spatial multiplexing systems. The conventional group detection (GD) suffers from a considerable performance loss since the noise components are not taken into account. The output signal-to-interference-plus-noise ratio (SINR) is defined in each subgroup in order to consider both the desired signal and noise statistics. Adopting the real-valued representation, we provide an optimal receive combiner which maximizes the SINR with a general group size. The simulation results show that the proposed scheme achieves a large performance gain over the conventional GD in coded systems. Also, when combining with near-optimal detection algorithms such as sphere decoder, the proposed GD scheme offers a comparable performance with significant reduced complexity.

Error Performance of Prerake Diversity Combining-Based UWB Spatial Multiplexing MIMO Systems over Indoor Wireless Channels

In this letter, we consider a novel ultra-wideband (UWB) spatial multiplexing (SM) multiple input multiple output (MIMO) structure, which consists of prerake diversity combiners in the transmitter and a zero forcing (ZF) detector in the receiver. For a UWB SM MIMO system with N transmit antennas, M receive antennas, and L resolvable multipath components, it is shown that the proposed prerake combining-based MIMO detection scheme has the diversity order of (LN - M + 1) and its BER performance is analytically presented in a log-normal fading channel and also compared with that of a rake combining-based ZF scheme.

Channel prediction for precoded spatial multiplexing multiple-input multiple-output systems in time-varying fading channels

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. Consequently, the precoding matrix can be found during the training symbols and used over the subsequent data symbols. In this study, the authors consider a more practical system where the channel varies from one block of symbols to another. In such a 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, the authors 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.

Efficient Hybrid DFE Algorithms in Spatial Multiplexing Systems

The wireless systems that establish multiple input multiple output (MIMO) channels through multiple antennas at both ends of the communication link, have been proved to have tremendous potential to linearly lift the capacity of conventional scalar channel. In this paper, we present two efficient decision feedback equalization algorithms that achieve optimal and suboptimal detection order in MIMO spatial multiplexing systems. The new algorithms combine the recursive matrix inversion and ordered QR decomposition approaches, which are developed for nulling cancellation interaface Bell Labs layered space time (BLAST) and back substitution interface BLAST. As a result, new algorithms achieve total reduced complexities in frame based transmission with various payload lengths compared with the earlier methods. In addition, they enable shorter detection delay by carrying out a fast hybrid preprocessing. Moreover, the operation precision insensitivity of order optimization greatly relaxes the word length of matrix inversion, which is the most computational intensive part within the MIMO detection task.