Xiaoli Ma

Adaptive state feedback and tracking control of systems with actuator failures

Direct adaptive-state feedback control schemes are developed for linear time-invariant plants with actuator failures with characterizations that some of the plant inputs are stuck at some fixed or varying values which cannot be influenced by control action. Conditions and controller structures for achieving plant-model state matching in the presence of actuator failures are derived. Adaptive laws are designed for updating the controller parameters when both the plant parameters and actuator-failure parameters are unknown. Closed-loop stability and asymptotic-state tracking are ensured. Simulation results show that desired system performance is achieved with the developed adaptive actuator failure compensation control designs.

Optimal training for block transmissions over doubly selective wireless fading channels

High data rates give rise to frequency-selective propagation, whereas carrier frequency-offsets and mobility-induced Doppler shifts introduce time-selectivity in wireless links. To mitigate the resulting time- and frequency-selective (or doubly selective) channels, optimal training sequences have been designed only for special cases: pilot symbol assisted modulation (PSAM) for time-selective channels and pilot tone-assisted orthogonal frequency division multiplexing (OFDM) for frequency-selective channels. Relying on a basis expansion channel model, we design low-complexity optimal PSAM for block transmissions over doubly selective channels. The optimality in designing our PSAM parameters consists of maximizing a tight lower bound on the average channel capacity that is shown to be equivalent to the minimization of the minimum mean-square channel estimation error. Numerical results corroborate our theoretical designs.

OFDM or single-carrier block transmissions?

We compare two block transmission systems over frequency-selective fading channels: orthogonal frequency-division multiplexing (OFDM) versus single-carrier modulated blocks with zero padding (ZP). We first compare their peak-to-average power ratio (PAR) and the corresponding power amplifier backoff for phase-shift keying or quadrature amplitude modulation. Then, we study the effects of carrier frequency offset on their performance and throughput. We further compare the performance and complexity of uncoded and coded transmissions over random dispersive channels, including Rayleigh fading channels, as well as practical HIPERLAN/2 indoor and outdoor channels. We establish that unlike OFDM, uncoded block transmissions with ZP enjoy maximum diversity and coding gains within the class of linearly precoded block transmissions. Analysis and computer simulations confirm the considerable edge of ZP-only in terms of PAR, robustness to carrier frequency offset, and uncoded performance, at the price of slightly increased complexity. In the coded case, ZP is preferable when the code rate is high (e.g., 3/4), while coded OFDM is to be preferred in terms of both performance and complexity when the code rate is low (e.g., 1/2) and the error-correcting capability is enhanced. As ZP block transmissions can approximate serial single-carrier systems as well, the scope of the present comparison is broader.

Non-data-aided carrier offset estimators for OFDM with null subcarriers: identifiability, algorithms, and performance

The ability of orthogonal frequency-division multiplexing systems to mitigate frequency-selective channels is impaired by the presence of carrier frequency offsets (CFOs). In this paper, we investigate identifiability issues involving high-resolution techniques that have been proposed for blind CFO estimation based on null subcarriers. We propose new approaches that do not suffer from the lack of identifiability and adopt adaptive algorithms that are computationally feasible. The performance of these techniques in relation to the location of the null subcarriers is also investigated via computer simulations and compared with the modified Cramer-Rao bound.

Space-time coding and Kalman filtering for time-selective fading channels

This paper proposes a novel decoding scheme for Alamoutis (see IEEE J. Select. Areas Commun., vol.16, p.1451-1458, 1998) space-time (ST) coded transmissions over time-selective fading channels that arise due to Doppler shifts and carrier frequency offsets. Modeling the time-selective channels as random processes, we employ Kalman filtering for channel tracking in order to enable ST decoding with diversity gains. Computer simulations confirm that the proposed scheme exhibits robustness to time-selectivity with a few training symbols.

Maximum-diversity transmissions over doubly selective wireless channels

High data rates and multipath propagation give rise to frequency-selectivity of wireless channels, while carrier frequency offsets and mobility-induced Doppler shifts introduce time-selectivity in wireless links. The resulting time- and frequency-selective (or doubly selective) channels offer joint multipath-Doppler diversity gains. Relying on a basis expansion model of the doubly selective channel, we prove that the maximum achievable multipath-Doppler diversity order is determined by the rank of the correlation matrix of the channels expansion coefficients, and is multiplicative in the effective degrees of freedom that the channel exhibits in the time and frequency dimensions. Interestingly, it turns out that time-frequency reception alone does not guarantee maximum diversity, unless the transmission is also designed judiciously. We design such block precoded transmissions. The corresponding designs for frequency-selective or time-selective channels follow as special cases, and thorough simulations are provided to corroborate our theoretical findings.

Full-diversity full-rate complex-field space-time coding

Exciting developments in wireless multiantenna communications have led to designs aiming mainly at one of two objectives: either high-performance by enabling the diversity provided by multi-input multi-output (MIMO) channels or high-rates by capitalizing on space-time multiplexing gains to realize the high capacity of MIMO fading channels. By concatenating a linear complex-field coder (a.k.a. linear precoder) with a layered space-time mapper, we design systems capable of achieving both goals: full-diversity and full-rate (FDFR), with any number of transmit- and receive-antennas. We develop FDFR designs not only for flat-fading but for frequency-selective, or, time-selective fading MIMO channels as well. Furthermore, we establish the flexibility of our FDFR designs in striking desirable performance-rate-complexity tradeoffs. Our theoretical claims are confirmed by simulations.

Optimal training for block transmissions over doubly-selective fading channels

High data rates give rise to frequency-selective propagation, while carrier frequency-offsets and mobility-induced Doppler shifts introduce time-selectivity in wireless links. To mitigate the resulting time- and frequency-selective (or doubly-selective) channels, an optimal training strategy is designed in this paper for block transmissions over doubly-selective channels, relying on a basis expansion channel model. The optimality in designing our PSAM parameters consists of maximizing a tight lower bound on the average channel capacity, that is also shown to be equivalent to the minimization of the minimum mean-square channel estimation error. Numerical results corroborate our theoretical designs.

Optimal training for MIMO frequency-selective fading channels

High data rates give rise to frequency-selective channel effects. Space-time multiplexing and/or coding offer attractive means of combating fading, and boosting capacity of multi-antenna communications. As the number of antennas increases, channel estimation becomes challenging because the number of unknowns increases, and the power is split at the transmitter In this paper, we design a low complexity optimal training scheme for block transmissions over frequency-selective channels with multiple antennas. The optimality in designing our training schemes consists of maximizing a lower bound on the average capacity that is shown to be equivalent to minimizing the mean-square error of the linear channel estimator. Simulation results confirm our theoretical analysis.

First-Order Perturbation Analysis of Singular Vectors in Singular Value Decomposition

The perturbation analysis of singular value decomposition (SVD) has been well documented in the literature within the context of subspace decomposition. The contribution of the signal subspace to the perturbation of the singular vectors that span the signal subspace is often ignored as it is treated as second and higher order terms, and thus the first-order perturbation is typically given as the column span of the noise subspace. In this paper, we show that not only the noise subspace, but also the signal subspace, contribute to the first-order perturbation of the singular vectors. We further show that the contribution of the signal subspace does not impact on the performance analysis of algorithms that rely on the signal subspace for parameter estimation, but it affects the analysis of algorithms that depends on the individual basis vectors. For the latter, we also give a condition under which the contribution of the signal subspace to the perturbation of singular vectors may be ignored in the statistical sense.