Channel estimation for layered space-time systems in time-varying frequency selective wireless channels

Space-time techniques for multiple-input multiple-output (MIMO) systems potentially provide vast increases in capacity. In order to achieve the quoted capacity gains the MIMO channel impulse response (CIR) must be known or estimated. Thus far, existing MIMO channel estimation techniques have been limited to the narrowband case or cater specifically for coded space-time systems. In this paper, we present a novel training-based MIMO channel estimation scheme for an uncoded layered space-time system that operates in the wideband frequency-selective fading environment. The method uses a pilot matrix consisting of pilot symbols derived from the Paley-Hadamard matrix in order to jointly estimate the individual CIR of the MIMO channel. The orthogonal property of the pilot matrix is utilized to resolve both intersymbol interference and intercarrier interference of the multiple transmit and received signals. The Paley Toeplitz structure is also exploited in order to minimise the length of the pilot sequence for a given length of CIR and thus maximise the effective data throughput. Results are presented which demonstrate the accuracy of the proposed channel estimation scheme and its performance in a layered space-time system.

A 2-D shooting-and-bouncing (SBR) ray-tracing method considering ray reflect, transmission and diffraction is used to analyze antenna spacing effect on capacity complementary cumulative distribution functions(CCDFS) of indoor non-line-of-sight (NLOS) MIMO channel and indoor multiple-input multiple-output (MIMO) channel with line-of-sight (LOS) path. The results show that the capacities of MIMO channel with LOS path are less than NLOS MIMO channel capacities in general. But whether in indoor MIMO channel with LOS path or in NLOS indoor MIMO channel, capacities CCDFS of indoor MIMO systems with antenna spacing of 5/spl times/ can reach the theoretical independent and identically distribution (i.i.d) Rayleigh capacities nearly fully. With the decrease of antenna spacing, the capacities dropped also. And the less antenna spacing, the more difference between indoor NLOS MIMO channel capacities and capacities of MIMO channel with LOS path.

In the emerging high mobility vehicle-to-everything (V2X) communications using millimeter wave (mmWave) and sub-THz, multiple-input multiple-output (MIMO) channel estimation is an extremely challenging task. At mmWaves/sub-THz frequencies, MIMO channels exhibit few leading paths in the space-time (ST) domain (i.e., directions or arrival/departure and delays). Algebraic low-rank (LR) channel estimation exploits ST channel sparsity through the computation of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">position-dependent</i> MIMO channel eigenmodes leveraging recurrent training vehicle passages in the coverage cell. LR requires vehicles’ geographical positions and tens to hundreds of training vehicles’ passages for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">each</i> position, leading to significant complexity and control signaling overhead. Here, we design a deep-learning (DL)-based LR channel estimation method to infer MIMO channel eigenmodes in V2X urban settings, starting from a single least squares (LS) channel estimate and without needing vehicle’s position information. Numerical results show that the proposed method attains comparable mean squared error (mse) performance as the position-based LR. Moreover, we show that the proposed model can be trained on a reference scenario and be effectively transferred to urban contexts with different ST channel features, providing comparable mse performance without an explicit transfer learning procedure. This result eases the deployment in arbitrary dense urban scenarios.

We study how to design a worst-case robust training sequence for multiple-input multiple-output (MIMO) channel estimation. We consider mean-squared error of channel estimates as the figure of merit which is a function of second-order statistics of the MIMO channel, i.e., channel covariance matrix, in order to optimize training sequences under a total power constraint. In practical applications, the channel covariance matrix is not known perfectly. Thus the main aspect of our design is to improve robustness of the training sequences against possible uncertainties in the available channel covariance matrix. Using a deterministic uncertainty model, we formulate a robust training sequence design as a minimax optimization problem where we take such imperfections into account. We investigate the robust design problem assuming the general case of an arbitrarily correlated MIMO channel and a non-empty compact convex uncertainty set. We prove that such a problem admits a globally optimal solution by exploiting the convex-concave structure of the objective function, and propose numerical algorithms to address the robust training design problem. We proceed the analysis by considering multiple-input single-output (MISO) channels and Kronecker structured MIMO channels along with unitarily-invariant uncertainty sets. For these scenarios, we show that the problem is diagonalized by the eigenvectors of the nominal covariance matrices so that the robust design is significantly simplified from a complex matrix-variable problem to a real vector-variable power allocation problem. For the MISO channel, we provide closed-form solutions for the robust training sequences with the uncertainty sets defined by the spectral norm and nuclear norm.

A novel stochastic multiple-input multiple-output (MIMO) channel model based on the singular value decomposition of the channel matrix is proposed in this study. Under the framework of the proposed model, each of the right singular vectors can be modelled as the product of a stochastic scalar and a non-random vector, as is each of the left singular vectors. The non-random vectors, defined as the eigenmodes of the transmitter and receiver, respectively, can be easily extracted from the measurements, so are the singular values of the channel matrix. The implications of the proposed model's parameters that provide further insight into the MIMO channel are interpreted and a way of exploiting the parameters is given. To validate the proposed model, MIMO channel measurement is carried out under different indoor environments and the channel capacity is analysed. It is shown that the proposed model provides a better fit to the measurement results than the other popular stochastic channel models. The proposed stochastic MIMO channel model can be used for the MIMO communication system design and evaluation.

Multicanonical Monte Carlo (MMC) is an adaptive importance sampling technique which employs a blind adaptation algorithm to converge to the optimal biasing distribution. In this paper, we propose an improved MMC algorithm for fast estimation of outage probabilities in Multiple Input Multiple Output (MIMO) channels. The algorithm uses an improved estimator which can provide smooth estimates with high reliability at very low error probabilities. The proposed estimator uses moving average filtering to smooth the visits histograms at each iteration thereby reducing the stochastic fluctuations between iterations. We compare the proposed estimator with the well known Berg's update and the simulation results show that the new estimator can accurately estimate lower error probabilities with the same number of samples.

This paper describes a broadband multiple input, multiple output (MIMO) channel characterization platform and capacity measurement results in indoor office environment. The MIMO testbed has been designed for broadband MIMO channel sounding, capacity measurements and for characterizing the directional-multipaths of the radio propagation channel. The MIMO channel data have been collected in 5 GHz band inside a modern office environment. Capacity results from these experiments are discussed for different propagation conditions, including non line-of-sight (NLOS) and LOS propagations with various spacings between array elements. Spatial correlations are analyzed from the measured data and a frequency selective MIMO channel model based on the correlation statistics is validated. Post-processing of the measured data with a sequential ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is utilized to extract the directions of departures and arrivals of multipath components at the transmitting and receiving arrays, respectively. A method of obtaining broadband MIMO capacity, indirectly, from a single directional measurement of MIMO propagation channel is also proposed and verified from the measurement results.

This thesis describes the analytical design and the performance analysis of optimum receivers for Multiple Input - Multiple Output (MIMO) fading channels. In particular, a novel Optimum Receiver for separately-correlated MIMO channels is proposed. This novel pilot-aided receiver is able to process jointly the pilot symbols, transmitted within each time frame as a preamble, and the information symbols and to decode the transmitted data in a single step, avoiding the explicit estimation of the channel matrix. The optimum receiver is designed for the following two scenarios, corresponding to different transmission schemes and channel models: 1) Narrowband Rician fading MIMO channel with spatial separate correlation; 2) MIMO-OFDM Rician fading channel with space and frequency separate correlation. For each system the performance of the optimum receiver is studied in detail under different channel conditions. The optimum receiver is compared with: - the ideal Genie Receiver, knowing perfectly the Channel State Information (CSI) at no cost; - the standard Mismatched Receiver, estimating the CSI in a first step, then using this imperfect estimate in the ideal channel metric. Since the optimum receiver requires the knowledge of the channel parameters for the decoding process, an estimation algorithm is proposed and tested. Moreover, a complexity analysis is carried out and methods for complexity reduction are proposed. Furthermore, the narrowband receiver is tested in realistic conditions using measured channel samples. Finally, a blind version of the receiver is proposed

In this paper, a power water-filling scheme for unequal error protection (UEP) based on set partitioning in hierarchical trees (SPIHT) coded image transmission over multiple input multiple output(MIMO) channels is proposed. SPIHT coded image information is divided into different sub-streams according to their different importance, which is allocated to different channels. Then unequal error protection (UEP) of image with singular value decomposition and power water-filling policy is achieved. The simulation results show that the quality of reconstructed image of using UEP is better than equal error protection (EEP).

In this paper, we build up a new intelligent reflecting surface (IRS) aided multiple-input multiple-output (MIMO) channel model, named the cascaded LoS MIMO channel, that is applicable to both near-field and far-field scenarios. The proposed channel model consists of a transmitter (Tx) and a receiver (Rx) both equipped with uniform linear arrays (ULAs), and an IRS is used to enable communications between the transmitter and the receiver through the line-of-sight (LoS) links seen by the IRS. When modeling the reflection of electromagnetic waves at the IRS, we take into account the curvature of the wavefront on different reflecting elements. Based on the established channel model, we show that an IRS-assisted MIMO channel is able to support spatial multiplexing solely by the cascaded LoS links. We generalize the notion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Rayleigh distance</i> originally coined for the single-hop MIMO channel to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">full multiplexing region (FMR)</i> for the cascaded LoS MIMO channel, where the FMR is the union of all the Tx-IRS and IRS-Rx distance pairs that enable full multiplexing communication. We derive an inner bound of the FMR under a special passive beamforming (PB) strategy named reflective focusing, and provide the corresponding orientation settings of the antenna arrays that achieve full multiplexing.

Visible Light Communication (VLC) has emerged as a powerful technique for wireless communication systems. Providing high data rate and increasing capacity are the major problems in VLC. Recent evidence suggests that Multiple Input Multiple Output (MIMO) technique can offers improved data rates and increased link range. This paper describes the design and implementation of visible light communication system in indoor environment exploring the benefits of MIMO. The specific objective of this research was to implement a 4×4 Multiple Input (LEDs) Multiple Output (photodetectors)-VLC communication system, where a 16 white power LEDs in four arrays are setting up at transmitter and four RX modules are setting up at receiver side without the need for additional power or bandwidth as well as analyze a mathematical model for a VLC- 4×4 MIMO with different modes such as the suitable angles to cover the entire room. The research designs practically an electronic circuit for the transmitter and receiver with inexpensive components. The power distribution of different propagation modes is calculated for Single Input Single Output (SISO) and MIMO channels in typical room dimensions. The results in this paper indicate that the power is distributed uniformly for entire room when implemented VLC-MIMO as compared to VLC-SISO. Furthermore, a 4×4 MIMO implementing VLC is compared in term of BER vs. SINR with SISO communication system for both Line of Sight (LOS) and Non Line of Sight (NLOS) propagation modes. Comparing the two results of LOS and NLOS, it can be seen that a 4×4 MIMO implementing VLC for LOS perform better than the same system with NLOS due to decreasing in the received power resulted from the multipath effect.

This paper presents outdoor wideband 8×8 multiple-input multiple-output (MIMO) channel measurements using dual-polarized antennas at 11 GHz. The measurements were conducted in the urban and residential areas of Ishigaki City, Okinawa, Japan. The differences in polarization for MIMO capacity and efficiency are discussed with respect to the dependency on local propagation environments. The MIMO capacity increases in proportion to the number of antennas at least for 8×8 configuration in non-line-of-sight area. Finally, MIMO channel capacity comparison between ultra high frequency and super high frequency band cellular system is simulated using 11 GHz measurement data.

An important problem for delay-limited communications requires to minimize the required transmit power for ensuring an acceptable outage probability for a given number of blocks transmission. In this paper, we consider a multiple-input multiple-output (MIMO) Rayleigh block flat-fading channel and investigate the joint optimization of power allocation and MIMO vector coding exploiting causal channel state information at the transmitter (CSIT). Using an upper bound outage probability, we derive the suboptimal power allocation and MIMO vector coding solution in closed-form, and we show that the suboptimal solution has a water-filling interpretation among the MIMO channel at present and some statistics of the future channels.

After a few decades’ evolution of wireless communication systems, to ensure reliable highspeed communication over unreliable wireless channels is still one of the major challenges facing researchers and engineers. The use of multiple antennas at transmitter and receiver, known as multiple-input multiple-output (MIMO) communications, is one promising technology delivering desired wireless services. The main goal of this thesis is to study two important issues in wireless MIMO communication systems: receiver design for coded MIMO systems, and diversity-multiplexing tradeoff analysis in general fading channels. In the first part of this thesis, we decompose the receiver design problem into two subproblems: MIMO channel estimation and MIMO detection. For the MIMO channel estimation, we develop an expectation-maximization (EM) based semi-blind channel and noise covariance matrix estimation algorithm for space-time coding systems under spatially correlated noise. By incorporating the proposed channel estimator into the iterative receiver structure, both the channel estimation and the error-control decoding are improved significantly. We also derive the modified Cramer-Rao bounds (MCRB) for the unknown parameters as the channel estimation performance metric, and demonstrate that the proposed channel estimation algorithm can achieve the MCRB after several iterations. For the MIMO detection, we propose a novel lowcomplexity MIMO detection algorithm, which has only cubic order computational complexity, but with near-optimal performance. For a 4×4 turbo-coded system, we show that the proposed detector had the same performance as the maximum a posteriori (MAP) detector for BPSK modulation, and 0.1 dB advantage over the approximated MAP detector (list sphere decoding algorithm) for 16-QAM modulation at BER = 10−4. In the second part of this thesis, we derive the optimal diversity-multiplexing tradeoff for

Following the seminal work by Zheng and Tse on the diversity and multiplexing tradeoff (DMT) of multiple-input multiple-output (MIMO) channels, in this paper, we introduce the array gain to investigate the fundamental relation between transmission rate and reliability in MIMO systems. The array gain gives information on the power offset that results from exploiting channel state information at the transmitter or as a consequence of the channel model. Hence, the diversity, multiplexing, and array gain (DMA) analysis is able to cope with the limitations of the original DMT and provide an operational meaning in the sense that the DMA gains of a particular system can be directly translated into a parameterized characterization of its associated outage probability performance. In this paper, we derive the best DMA gains achievable by any scheme employing isotropic signaling in uncorrelated Rayleigh, semicorrelated Rayleigh, and uncorrelated Rician block-fading MIMO channels. We use these results to analyze the effect of important channel parameters on the outage performance at different points of the DMT curve.