Alamouti's orthogonal space-time block code (OSTBC) is a simple yet important technique to take advantage of transmit diversity to mitigate fading channel effects. In this paper, we analyze the effects of time-selective channels and channel estimation errors on the bit error rate (BER) performance of Alamouti's OSTBC. We develop an analytical expression of the BER performance for the linear decoding with minimum mean squared error (MMSE) channel estimates in place of the true channel. Based on the expression, we derive a BER performance limit in decision-directed mode where the channel is tracked with Kalman filtering. Numerical examples are provided to validate our analysis and to see the impact of time-selective fading and channel estimation errors on the BER performance.

This paper describes the experimental evaluation of a testbed with a simple decision-feedback channel tracking scheme for MIMO-OFDM systems. The channel tracking scheme periodically estimates the channel state matrix for each subcarrier from received signals and replicas of the transmitted signal. The estimated channel state matrices, which are obtained at mutually different timings, are combined based on maximum ratio combining and used for MIMO signal detection. The testbed was implemented on field programmable gate arrays (FPGAs) of 1/5 scale, which confirms the implementation feasibility of the channel tracking scheme. The packet error rate (PER) and mobility performance of the testbed were measured. The testbed employed a 22 MIMO channel, zero-forcing algorithm for MIMO signal detection, 16QAM for the subcarrier modulation scheme, and coding rate of 1/2. The proposed scheme suppressed the increase in the required SNR for PER of 10-2 to less than 1 dB when the relative velocity between the transmitter and the receiver was less than 45 km/h assuming 5 GHz band operation. In addition, the proposed scheme offers 6.3% better throughput than the conventional scheme. The experimental results demonstrate that the channel tracking scheme implemented in the testbed effectively tracks the fluctuation of a MIMO channel.

This paper proposes a simple and feasible decision-feedback channel tracking scheme for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems designed for wireless local area networks (LANs). In the proposed scheme, the channel state matrix for each subcarrier is tentatively estimated from a replica matrix of the transmitted signals. The estimated channel matrices, each derived at a different timing, are combined, and the previously estimated channel matrices are replaced with the latest ones. Unlike conventional channel tracking schemes based on a Kalman filter, the proposed scheme needs no statistical information about a MIMO channel, which makes the receiver structure quite simple. The packet error rate (PER) performances for the proposed scheme are evaluated on computer simulations. When there are three transmit and receive antennas, the subcarrier modulation scheme is 64 QAM, and the coding rate is 3/4, the proposed scheme keeps the SNR degradation at PER of 1e-2 less than 0.1 dB when the velocity of receiver is 3 km/h in an indoor office environment at 5 GHz band. In addition, compared to the conventional channel tracking scheme based on known pilot symbols, the proposed scheme improves throughput performance by 13.8% because it does not need pilot symbols. These results demonstrate that the proposed channel tracking scheme is simple and feasible for implementation in MIMO-OFDM systems based on wireless LANs.

This paper proposes a new decision feedback decoding scheme for Alamouti-based space-time block coding (STBC) transmission over time-selective fading channels. In wireless channels, time-selective fading effects arise mainly due to Doppler shift and carrier frequency offset. Modelling the time-selective fading channels as the first-order Gauss-Markov processes, we use recursive algorithms such as Kalman filtering, LMS and RLS algorithms for channel tracking. The proposed scheme consists of the symbol decoding stage and channel tracking algorithms. Computer simulations confirm that the proposed scheme shows the better performance and robustness to time-selectivity.

Multiple-input multiple-output (MIMO) wireless systems can realize large spectral efficiency and high performance communication links. For wideband transmissions, the combination of MIMO systems with orthogonal frequency division multiplexing (OFDM) has recently attracted a lot of attention and it is well known as MIMO-OFDM. In MIMO-OFDM systems, the overlapped signals over each subcarrier need to be separated by the receiver. For fading coefficients based receivers, the performance of the receiver depends largely on the accuracy of the estimated channel. Especially, when the channel varies with time, accurate channel tracking is needed. Conventional optimized channel tracking has large computational complexity because large matrix inverse computation is required. In order to reduce the complexity, a simplified channel tracking scheme assuming PSK modulation has been considered. However, such a simplified scheme is found to suffer from large performance degradation when applied to multi-level QAM modulation. In this paper, we derive a new simplified but improved channel tracking scheme for MIMO-OFDM systems that can be applied to both PSK and multi-level QAM modulation. The performance and the complexity of the proposed scheme are evaluated with comparisons to conventional schemes.

A cumulant-based lattice algorithm for multichannel adaptive filtering is proposed in this paper. Proposed algorithm takes into account the advantages of higer-order statistics, that is, improvement of estimation accuracy, blindness to colored Gaussian noise and the possibility to estimate the nonminimum-phase system etc. Without invoking the Instrumental Variable () method as used in other papers [1], [2], the algorithm is derived directly from the recursive pseudo-inverse matrix. The behavior of the algorithm is illustrated by numerical examples.

This paper presents an adaptive MLSE (Maximum Likelihood Sequence Estimator) suitable for TDMA cellular systems. The proposed MLSE has two special features such as handling wide dynamic range signals without analogue gain controls and fast channel tracking capability. In order to handle wide dynamic range signals without conventional AGCs (Automatic Gain Controller), the proposed MLSE uses envelope components of received signals obtained from a non-linear log-amplifier module which has wide log-linear gain characteristics. By using digital signal processing technique, the log-converted envelope components are normalized and converted to linear values which conventional adaptive MLSEs can handle. As a channel tracking algorithm of the channel estimator, the proposed MLSE adopts a QT-LMS (Quick-Tracking Least Mean Square) algorithm, which is obtained by modifying LMS algorithm to enable a faster tracking capability. The algorithm has a fast tracking capability with low complexity and is suitable for implementation in a fixed-point digital signal processor. The performances of the MLSE have been evaluated through experiments in TDMA cellular environments with π/4-shifted QPSK, 24.3k symbol/sec. It is shown that, under conditions of 65dB amplitude variations and 80Hz Doppler frequency, the MLSE successfully achieves less than 3% B.E.R., which is required for digital cellular systems.