RLS channel estimation and tracking for MIMO-extended IEEE 802.11a WLANs

Wireless communication systems based on multiple-input multiple-output (MIMO) technology and orthogonal frequency division multiplexing (OFDM) have the potential to achieve enormous increase in the capacity and link reliability. In order to realize such systems, channel estimation is crucial. In this paper, an adaptive channel estimation and tracking scheme based on recursive least squares (RLS) algorithm is proposed for MIMO OFDM-based wireless local area networks (WLANs). Preamble-aided channel estimation is performed in time-domain (TD). The estimator is then extended to perform decision-directed (DD) channel tracking during data transmission. The channel is assumed to be constant during one OFDM symbol and evolving in time according to the first-order Markov process. Different training rates at different Doppler frequencies were investigated. Simulation results show that the proposed estimation scheme has excellent performance measured in terms of the mean squares error (MSE) and the bit error rate (BER), provided that the forgetting factor of the RLS algorithm is optimally selected

Subspace Tracking and Least Squares Approaches to Channel Estimation in Millimeter Wave Multiuser MIMO

The problem of MIMO channel estimation at millimeter wave frequencies, both in a single-user and in a multi-user setting, is tackled in this paper. Using a subspace approach, we develop a protocol enabling the estimation of the right (resp. left) singular vectors at the transmitter (resp. receiver) side; then, we adapt the projection approximation subspace tracking with deflation and the orthogonal Oja algorithms to our framework and obtain two channel estimation algorithms. We also present an alternative algorithm based on the least squares approach. The hybrid analog/digital nature of the beamformer is also explicitly taken into account at the algorithm design stage. In order to limit the system complexity, a fixed analog beamformer is used at both sides of the communication links. The obtained numerical results, showing the accuracy in the estimation of the channel matrix dominant singular vectors, the system achievable spectral efficiency, and the system bit-error-rate, prove that the proposed algorithms are effective, and that they compare favorably, in terms of the performance-complexity trade-off, with respect to several competing alternatives.Comment: To appear on the IEEE Transactions on Communication

Time-domain adaptive channel estimation for OFDM-based WLAN with multiple-antennas

In this paper, an adaptive time-domain (TD) channel estimation scheme, based on recursive least squares (RLS) algorithm, is proposed for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) based wireless local area networks (WLANs). The estimator is then extended to perform decision-directed (DD) channel tracking during data transmission. The channel is assumed to be constant during one OFDM symbol but evolves in time according to the first-order Markov process. Different training rates at different Doppler frequencies were investigated. Simulation results show that the proposed estimation scheme has excellent performance measured in terms of the mean squares error (MSE) and the bit error rate (BER), provided that the forgetting factor of the RLS algorithm is optimally selected

Optimum-Weighted RLS Channel Estimation for Rapid Fading MIMO Channels

This paper investigates on an accurate channel estimation scheme for fast fading channels in multiple-input multiple-output (MIMO) mobile communications. A high-order exponential-weighted recursive least-squares (EW-RLS) method has been known as a good channel estimation scheme in rapid fading. however, there exists a drawback that we need to properly adjust the estimation order according to the channel environment. In this paper, we theoretically derive an optimum-weighted LS (OW-LS) channel estimation based on the statistical knowledge of the spatio-temporal channel correlation. Through the analysis, we reveal that the zero-th order polynomial becomes optimal when the optimum-weighting is employed. Furthermore, we propose an efficient recursive algorithm for channel tracking in oder to reduce the computational complexity. Since the proposed scheme automatically adapts the weighting coefficients to the channel condition, it has a significant advantage in mean-square error (MSE) performance compared to EW-RLS scheme.Engineering and Applied Science

Massive MIMO-based Localization and Mapping Exploiting Phase Information of Multipath Components

In this paper, we present a robust multipath-based localization and mapping framework that exploits the phases of specular multipath components (MPCs) using a massive multiple-input multiple-output (MIMO) array at the base station. Utilizing the phase information related to the propagation distances of the MPCs enables the possibility of localization with extraordinary accuracy even with limited bandwidth. The specular MPC parameters along with the parameters of the noise and the dense multipath component (DMC) are tracked using an extended Kalman filter (EKF), which enables to preserve the distance-related phase changes of the MPC complex amplitudes. The DMC comprises all non-resolvable MPCs, which occur due to finite measurement aperture. The estimation of the DMC parameters enhances the estimation quality of the specular MPCs and therefore also the quality of localization and mapping. The estimated MPC propagation distances are subsequently used as input to a distance-based localization and mapping algorithm. This algorithm does not need prior knowledge about the surrounding environment and base station position. The performance is demonstrated with real radio-channel measurements using an antenna array with 128 ports at the base station side and a standard cellular signal bandwidth of 40 MHz. The results show that high accuracy localization is possible even with such a low bandwidth.Comment: 14 pages (two columns), 13 figures. This work has been submitted to the IEEE Transaction on Wireless Communications for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl