A new layered space-time detection algorithm for frequency selective fading multiple-input multiple-output channels based on particle filter

In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.

SEMI-BLIND CHANNEL ESTIMATION OF MULTIPLE-INPUT/MULTIPLE-OUTPUT SYSTEMS BASED ON MARKOV CHAIN MONTE CARLO METHODS

This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and the transmitted signals. The deduced algorithms can work well under circumstances of low Signal-to-Noise Ratio (SNR). Simulation results are presented to demonstrate their effectiveness.

Extended Kalman filtering-based channel estimation for space-time coded MIMO-OFDM systems

A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing （MIMO-OFDM） system is considered as a solution to the future wideband wireless communication system. This paper proposes an extended Kalman filtering-based （EKF-based） channel estimation method for space-time coded MIMO-OFDM systems. The proposed method can exploit pilot symbols and an extended Kalman filter to estimate channel without any prior knowledge of channel statistics. In comparison with the least square （LS） and the least mean square （LMS） methods, the EKF-based approach has a better performance in theory. Computer simulations demonstrate the proposed method outperforms the LS and LMS methods. Therefore it can offer draznatic system performance improvement at a modest cost of computational complexity.

Generalized 3D Scattering Channel Model with MIMO Antenna Systems

In this paper, a generalized three-dimensional(3D) scattering channel model for macrocellular land mobile environments is considered. This model simultaneously describes angular arrival of multi-path signals in the azimuth and elevation planes in an environment where uniformly distributed scatterers are assumed to be present in hemispheroids around the base station(BS) and mobile station(MS). Using this channel model, we first derive the closed-form expression for the joint and marginal probability density functions of the angle-of-arrival and time-of-arrival measured at the BS and the MS corresponding to the azimuth and elevation angles. Next, we derive an expression for the Doppler spectral distribution caused by motion of the MSs. Furthermore, we analyze the performance of multiple-input multiple-output antenna systems numerically. The results show that the proposed 3D scattering channel model performs better than previously proposed two-dimensional(2D) models for indoor and outdoor environments. We compare the results with previous scattering channel models and measurement results to validate the generalizability of our model.

Robust Blind Separation for MIMO Systems against Channel Mismatch Using Second-Order Cone Programming

To improve the deteriorated capacity gain and source recovery performance due to channel mismatch problem,this paper reports a research about blind separation method against channel mismatch in multiple-input multiple-output(MIMO) systems.The channel mismatch problem can be described as a channel with bounded fluctuant errors due to channel distortion or channel estimation errors.The problem of blind signal separation/extraction with channel mismatch is formulated as a cost function of blind source separation(BSS) subject to the second-order cone constraint,which can be called as second-order cone programing optimization problem.Then the resulting cost function is solved by approximate negentropy maximization using quasi-Newton iterative methods for blind separation/extraction source signals.Theoretical analysis demonstrates that the proposed algorithm has low computational complexity and improved performance advantages.Simulation results verify that the capacity gain and bit error rate(BER) performance of the proposed blind separation method is superior to those of the existing methods in MIMO systems with channel mismatch problem.

Impact of Depolarization Phenomena on Polarized MIMO Channel Performances

The performance and capacity of multiple-input multiple-output (MIMO) wireless channels are limited by the spatial fading correlation between antenna elements. This limitation is due to the use of mono polarized antennas at receiver and transmitter sides. In this paper, in order to reduce the antenna correlation, the polarization diversity technique is employed. Although the spatial antenna correlation is attenuated for multi-polarization configurations, the cross-polar components appear. This paper highlights the impact of depolarization effect on the MIMO channel capacity for a 4×4 uniform linear antenna array. We assume that the channel is unknown at the transmitter and perfectly known at the receiver so that equal power is distributed to each of the transmit antennas. The numerical results illustrate that for low depolarization and spatial correlation, the capacity of single-polarization configuration behaves better than that of multi-polarization configuration.

Evaluation of Preamble Based Channel Estimation for MIMO-FBMC Systems

Filter-bank multicarrier （FBMC） with offset quadrature amplitude modulation （OQAM） is a candidate waveform for future wireless communications due to its advantages over orthogonal frequency division multiplexing （OFDM） systems. However, because of or-thogonality in real field and the presence of imaginary intrinsic interference, channel estimation in FBMC is not as straightforward as OFDM systems especially in multiple antenna scenarios. In this paper, we propose a channel estimation method which employs intrinsic interference cancellation at the transmitter side. The simulation results show that this method has less pilot overhead, less peak to average power ratio （PAPR）, better bit error rate （BER）, and better mean square error （MSE） performance compared to the well-known intrinsic approximation methods （IAM）.

Robust MSE precoder for imperfectly known MIMO wireless correlated channel

Aimed at that only one form of channel statistic information is utilized in traditional robust precoder schemes: either the channel mean or the transmit antenna correlation in multiple-input multiple-output (MIMO) wireless system, this paper proposes robust precoder designs which exploit both of statistic information to minimize the equalization mean-square error (MSE) with power constraint. Two different power constraints are studied. Besides the usual sum power constraint over all antennas, the per-antenna power constraint is imposed at transmitter in this paper. Since each antenna has its own amplifier, individual power constraint on each antenna is more realistic. Especially in MIMO-OFDM systems, the Peak-to-Average Ratio (PAR) is one of main practical problems. Simulations show that the proposed schemes have better performance than traditional normalized zero forcing schemes for imperfectly known correlated channel. Moreover, per-antenna power constraint can efficiently decrease the demand of dynamic range of power amplifier on each transmit antenna, especially in MIMO-OFDM systems.

Statistical Modeling of the High Altitude Platform Dual-Polarized MIMO Propagation Channel

In order to investigate the benefit of multiple-input multiple-output(MIMO) technique applying to the high altitude platform(HAP), a 2×2 MIMO statistical model, which can accurately describe the channel between HAP and high-speed train, is presented. And dual polarization diversity is particularly considered. Based on first-order three-state Markov chain, the single-input single-output(SISO) channel, a subset of the MIMO channel is first established. The ray tracing approach applied to the digital relief model(DRM) which covers the railway between Xi'an and Zhengzhou is used to obtain the state probability vector and matrix of the state transition probability. The proposed model considers both Doppler shift and temporal correlation, and the polarization correlation and spatial correlation statistical properties of large-scale fading and smallscale fading are analyzed. Moreover, useful numerical results on the MIMO HAP channel outage capacity are provided based on which, significant capacity gains with respect to the conventional SISO case are illustrated. Such statistical channel model can be applied to the future wireless communication system between HAP and high-speed train.

Sparse channel estimation for MIMO-OFDM systems using distributed compressed sensing

A sparse channel estimation method is proposed for doubly selective channels in multiple- input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems. Based on the basis expansion model （BEM） of the channel, the joint-sparsity of MIMO-OFDM channels is described. The sparse characteristics enable us to cast the channel estimation as a distributed compressed sensing （DCS） problem. Then, a low complexity DCS-based estimation scheme is designed. Compared with the conventional compressed channel estimators based on the compressed sensing （CS） theory, the DCS-based method has an improved efficiency because it reconstructs the MIMO channels jointly rather than addresses them separately. Furthermore, the group-sparse structure of each single channel is also depicted. To effectively use this additional structure of the sparsity pattern, the DCS algorithm is modified. The modified algorithm can further enhance the estimation performance. Simulation results demonstrate the superiority of our method over fast fading channels in MIMO-OFDM systems.

Joint Channel and Multi-User Detection Empowered with Machine Learning

The numbers of multimedia applications and their users increase with each passing day.Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network systems.In this article,a fuzzy logic empowered adaptive backpropagation neural network(FLeABPNN)algorithm is proposed for joint channel and multi-user detection(CMD).FLeABPNN has two stages.The first stage estimates the channel parameters,and the second performsmulti-user detection.The proposed approach capitalizes on a neuro-fuzzy hybrid systemthat combines the competencies of both fuzzy logic and neural networks.This study analyzes the results of using FLeABPNN based on a multiple-input andmultiple-output(MIMO)receiver with conventional partial oppositemutant particle swarmoptimization(POMPSO),total-OMPSO(TOMPSO),fuzzy logic empowered POMPSO(FL-POMPSO),and FL-TOMPSO-based MIMO receivers.The FLeABPNN-based receiver renders better results than other techniques in terms of minimum mean square error,minimum mean channel error,and bit error rate.

Science Letters:Peak-power reduction by the lattice-reduction-aided closest point search for MIMO broadcast channels

In this letter, we present a modified vector-perturbation precoding scheme for the multiple-input multiple-output broadcast channel, where a perturbation vector is chosen to take into account both the instantaneous power and the instantaneous peak power of the transmitted signal. This perturbation vector is obtained by using the closest point search, with the aid of the lattice-reduction algorithm. Simulation results show that the proposed scheme yields a tradeoff among power efficiency, peak-to-average power ratio reduction, and complexity.

Blind Joint Maximum Likelihood Channel Estimation and Data Detection for SIMO Systems

A blind adaptive scheme is proposed for joint maximum likelihood （ML） channel estimation and data detection of singleinput multiple-output （SIMO） systems. The joint ML optimisation over channel and data is decomposed into an iterative optimisation loop. An efficient global optimisation algorithm called the repeated weighted boosting search is employed at the upper level to optimally identify the unknown SIMO channel model, and the Viterbi algorithm is used at the lower level to produce the maximum likelihood sequence estimation of the unknown data sequence. A simulation example is used to demonstrate the effectiveness of this joint ML optimisation scheme for blind adaptive SIMO systems.

Power duality for multi-antenna OFDM system in broadcast channel with user scheduling

This paper deals with design and analysis of user scheduling and power allocation for multi-antenna OFDM systems with DPC,ZF-DPC,ZF-BF and TDMA transmit strategies.We consider the general multi-user downlink scheduling problem and power minimization with multi-user rate constraints.According to the channel state,it is shown that there is a power optimal policy which selects a subset of users in each scheduling interval.We present user selection algorithms for DPC,ZF-DPC,ZF-BF and TDMA for multi-antenna OFDM system in broadcast channels,and we also present the practical water-filling solution in this paper.By the selected users with the consideration of fairness,we derive the power optimization algorithm with multi-user rate constraints.We also analyze the power duality of uplink-downlink for the transmit strategies of DPC,ZF-DPC and ZF-BF.Simulation results show that the present user-scheduling algorithm and power minimization algorithm can achieve good power performance,and that the scheduling algorithm can guarantee fairness.

Particle filter for joint frequency offset and channel estimation in MIMO-OFDM systems

A particle filter is proposed to perform joint estimation of the carrier frequency offset （CFO） and the channel in multiple-input multiple-output orthogonal frequency division multiplexing （MIMO-OFDM） wireless communication systems. It marginalizes out the channel parameters from the sampling space in sequential importance sampling （SIS）, and propagates them with the Kalman filter. Then the importance weights of the CFO particles are evaluated according to the imaginary part of the error between measurement and estimation. The varieties of particles are maintained by sequential importance resampling （SIR）. Simulation results demonstrate this algorithm can estimate the CFO and the channel parameters with high accuracy. At the same time, some robustness is kept when the channel model has small variations.

Suboptimal MMSE Channel Estimation with Subspace Tracking for MIMO-OFDM Transmission

A suboptimal minimum mean-squared error estimation （MMSE） is proposed for a dispersive wireless channel in the absence of its .orrelation matrix for multipleinput multiple-output ort,ogonal frequency division multiplexing （MIMO - OFDM） transmission. It utilizes a fast subspace approximation tracking to separate signal subspace with a limited set of channel estimates. The subspace rank is adjusted by pre-set thresholds in different signal-to-noise ratios （SNRs）. The performance comparison among the proposed algorithm, least square based, and the optimal MMSE estimation is shown by numerical simulation under a spatially correlated multi-tap channel scenario. It demonstrates that the approach has better normalized mean square error than recursive least square estimation and yields 3 dB gain over the latter.

ERGODIC CAPACITY FORMULA OF MIMO-OFDM SYSTEMS UNDER CORRELATED FREQUENCY SELECTIVE RAYLEIGH FADING CHANNELS

An explicit formula for the ergodic capacity of Orthogonal Frequency Division Multiplexing (OFDM)-based Multiple-Input Multiple-Output (MIMO) systems under correlated frequency selective Rayleigh channels is derived,by simplifying the channel response matrix in frequency domain into the so-called Kronecker model composed of three kinds of correlations,i.e.multipath tap gain correlation and spatial fading correlations at both transmitter and receiver.The derived formula is very simple and convenient for one to estimate the effects of all three kinds of correlations on MIMO-OFDM capacity.If taps are independent,there is a very simple expression for the ergodic capacity.In case of tap correlation,the capacity formula could be further given in an integral expression.The validity of the new formula is verified and the effects of correlations,delay spread as well as the number of subcarriers on the ergodic capacity are evaluated via Monte Carlo simulations.

Antenna selection for V-BLAST systems in correlated channel

Spatial multiplexing systems can provide significant capacity improvement but are sensitive to channel correlation. Antenna selection is a low-cost low-complexity ahemative to resolve these problems. This paper proposes a new transmit antenna selection algorithm for the spatial multiplexing systems with the Vertical-Bell Labs Layered Space-Time （V-BLAST） nonlinear receiver in correlated channel. The proposed scheme separates the optimization into two parts： it first chooses the optimal number of substreams in terms of the singular values of the channel matrix, then adapts the mapping of substreams to antennas according to the post-detection signal-to-noise ratio （SNR）. Simulation results illustrate that the proposed two-step selection criterion can provide greater selection gain than the existing singnlar value based selection criterion as SNR and scattering angle increases. The proposed criterion outperforms the existing one by 0.3 dB at a vector symbol error rate of 10^- 3 and scattering angle of 20 degree.

Spatial channel characteristics in the outdoor hotspot environment based on wideband MIMO measurements

Wideband multiple-input multiple-output (MIMO) channel measurements were performed at5.25GHz in the hotspot environment in Beijing.The propagation mechanism was line-of-sight and ob-structed-line-of-sight (LOS/OLOS) in the outdoor scenario.Using a large amount of estimated angle ofdeparture (AoD) and angle of arrival (AoA) results,the cumulative distribution functions (CDFs) of di-rectional spread (DS) are extracted,which illustrate that the spatial dispersion is quite significant at bothends due to the low antenna height of base station and rich scatterers.The average power azimuth spec-trum (PAS) is found to be well fitted with a Laplacian function.In addition,the non-isotropic property ofspatial correlation is investigated,and the average envelop correlation over arbitrary antenna spacing pro-vides the correlation distance to facilitate the MIMO optimization and deployment in the outdoor hotspotenvironment.

Ergodic secrecy capacity of MRC/SC in single-input multiple-output wiretap systems with imperfect channel state information

This paper investigates the secrecy performance of maximal ratio combining （MRC） and selection combining （SC） with imperfect channel state information （CSI） in the physical layer. In a single-input multiple- output （SIMO） wiretap channel, a source transmits confidential messages to the destination equipped with M antennas using the MRC/SC scheme to process the received multiple signals. An eavesdropper equipped with N antennas also adopts the MRC/SC scheme to promote successful eavesdropping. We derive the exact and asymptotic closed-form expressions for the ergodic secrecy capacity （ESC） in two cases： （1） MRC with weighting errors, and （2） SC with outdated CSI. Moreover, two important indicators, namely high signal-to-noise ratio （SNR） slope and high SNR power offset, which govern ESC at the high SNR region, are derived. Finally, simulations are conducted to validate the accuracy of our proposed analytical models. Results indicate that ESC rises with the increase of the number of antennas and the received SNR at the destination, and fades with the increase of those at the eavesdropper. Another finding is that the high SNR slope is constant, while the high SNR power offset is correlated with the number of antennas at both the destination and the eavesdropper.