Channel estimation for time-varying MIMO relay systems

In this paper, we investigate the channel estimation problem for multiple-input multiple-output (MIMO) relay communication systems with time-varying channels. The time-varying characteristic of the channels is described by the complex-exponential basis expansion model (CE-BEM). We propose a superimposed channel training algorithm to estimate the individual first-hop and second-hop time-varying channel matrices for MIMO relay systems. In particular, the estimation of the second-hop time-varying channel matrix is performed by exploiting the superimposed training sequence at the relay node, while the first-hop time-varying channel matrix is estimated through the source node training sequence and the estimated second-hop channel. To improve the performance of channel estimation, we derive the optimal structure of the source and relay training sequences that minimize the mean-squared error (MSE) of channel estimation. We also optimize the relay amplification factor that governs the power allocation between the source and relay training sequences. Numerical simulations demonstrate that the proposed superimposed channel training algorithm for MIMO relay systems with time-varying channels outperforms the conventional two-stage channel estimation scheme.

Channel estimation for two-way MIMO relay systems in frequency-selective fading environments

© 2002-2012 IEEE. In this paper, we investigate the channel estimation problem for two-way multiple-input multiple-output (MIMO) relay communication systems in frequency-selective fading environments. We apply the method of superimposed channel training to estimate the individual channel state information (CSI) of the first-hop and second-hop links for two-way MIMO relay systems with frequency-selective fading channels. In this algorithm, a relay training sequence is superimposed on the received signals at the relay node to assist the estimation of the second-hop channel matrices. The optimal structure of the source and relay training sequences is derived to minimize the mean-squared error (MSE) of channel estimation. Moreover, the optimal power allocation between the source and relay training sequences is derived to improve the performance of channel estimation. Numerical examples are shown to demonstrate the performance of the proposed superimposed channel training algorithm for two-way MIMO relay systems in frequency-selective fading environments.

Multi-surface sliding control of MIMO autonomous flight systems

In this paper, a multi-surface sliding control (MSSC) is proposed for trajectory tracking of 6 degrees of freedom (6-DOF) inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). It is shown that an iterative MSSC design can be carried out to control flight. Using MSSC on MIMO autonomous flight systems creates confluent control that can account for model mismatches, system uncertainties, system disturbances and excitation in internal dynamics. We prove that the MSSC system guarantees asymptotic output tracking and ultimate uniform boundedness of the system. Simulation results are presented to validate the analysis.

Multi-surface sliding control of MIMO autonomous flight systems

In this paper, we present a hardware in the loop simulation of our proposed multi-surface sliding control (MSSC) for trajectory tracking of 6 degrees of freedom (6-DOF) inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). Using MSSC on MIMO autonomous flight systems creates confluent control that can account for both matched and mismatched uncertainties, system disturbances and excitation in internal dynamics. The control law is implemented on an onboard computer and is validated though Hardware-In-the-Loop (HIL) simulations, between the hardware and the flight simulator X-Plane, which simulates the unmanned aircraft dynamics, sensors, and actuators. Simulation results are presented to validate the analysis.

Superimposed channel training algorithm for time-varying MIMO relay systems

Two-way relaying systems are known to be capable of providing higher spectral efficiency compared with one-way relaying systems. However, the channel estimation problem for two-way relaying systems becomes more complicated. In this paper, we propose a superimposed channel training scheme for two-way MIMO relay communication systems, where the individ-ual channel information for users-relay and relay-users links are estimated. The optimal structure of the source and relay training sequences are derived when the mean-squared error (MSE) of channel estimation is minimized. We also optimize the power allocation between the source and relay training sequences to improve the performance of the algorithm. Numerical examples are shown to demonstrate the performance of the proposed channel training algorithm.

Blind channel estimation and signal retrieving for MIMO relay systems

In this paper, we propose a blind channel estimation and signal retrieving algorithm for two-hop multiple-input multiple-output (MIMO) relay systems. This new algorithm integrates two blind source separation (BSS) methods to estimate the individual channel state information (CSI) of the source-relay and relay-destination links. In particular, a first-order Z-domain precoding technique is developed for the blind estimation of the relay-destination channel matrix, where the signals received at the relay node are pre-processed by a set of precoders before being transmitted to the destination node. With the estimated signals at the relay node, we propose an algorithm based on the constant modulus and signal mutual information properties to estimate the source-relay channel matrix. Compared with training-based MIMO relay channel estimation approaches, the proposed algorithm has a better bandwidth efficiency as no bandwidth is wasted for sending the training sequences. Numerical examples are shown to demonstrate the performance of the proposed algorithm.

A new second-order method for blind signal separation from dynamic mixtures

This paper presents a new approach to separate colored stationary signals mixed by convolutive channels. A cost function is proposed by employing linear constraint to the demixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.

Blind equalization of nonirreducible systems using the CM criterion

We address the blind equalization of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channel systems excited by constant modulus (CM) signals. It is known that the algorithms based on the CM criterion can equalize an FIR MIMO system that is irreducible. The irreducible condition is restrictive as it requires all source signals to be received at sensors simultaneously. In this paper, we further show that the CM property of signals can be exploited to construct a zero-forcing equalizer for a system that is nonirreducible. Simulation examples demonstrate the proposed result.

A new second order method for blind signal separation from convolutive mixtures

This paper presents a new approach to separate colored signals mixed by FIR (finite impulse response) and MIMO (multiple-input multiple-output) channels. A cost function is proposed by employing linear constrainit to the de mixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.

Adaptive blind source separation using constant modulus criterion and signal mutual information

We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. It is known that the constant modulus (CM) criterion can be used to extract unknown source signals. However, the existing CM based algorithms normally extract the source signals in a serial manner. Consequently, the accuracy in extracting each source signal, except for the first one, depends on the accuracy of previous source extraction. This estimation error propagation (accumulation) causes severe performance degradation. In this paper, we propose a new adaptive separation algorithm that can separate all source signals simultaneously by directly updating the separation matrix. The superior performance of the new algorithm is demonstrated by simulation examples

Blind equalization of non-irreducible and non-column-reduced channels driven by constant modulus signals

We address the blind equalization of finite-impulse-response (FIR), multiple-input multiple-output (MIMO) channels excited by constant modulus (CM) signals. It is known that the algorithms based on the constant modulus (CM) criterion can equalize an FIR MIMO channel that is irreducible and column-reduced. We show in this paper that the CM property of signals can be exploited to construct a zero-forcing equalizer for a non-irreducible and non-column-reduced channel. We also give a lower bound for the order of the equalizer. Simulation examples demonstrate the proposed result.

Blind equalization of non-irreducible channels driven by MPSK signals

This paper deals with the problem of blind equalization of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channels excited by M-ary phase shift keying (MPSK) signals. It is known that the algorithms based on the constant modulus (CM) criterion can equalize an FIR MIMO channel that is irreducible. The irreducible condition is restrictive since it requires that all source signals arrive at the receiving antennas simultaneously. In this paper, we show that the CM criterion can also be used to construct a zero-forcing equalizer for a channel that is non-irreducible. We also derive a lower bound for the order of the equalizer. The proposed result is validated by numerical simulations.

Antenna selection and channel estimation for hybrid relay systems

The research addressed performance issues for wireless signal transmission and has shown that performance improves with the help of relays due to increased diversity. Further, the areas of antenna selection and channel estimation and modelling has been investigated for improved cost and complexity and has shown to further enhance the performance of the wireless relay systems.