A new zero-forcing block diagonalization (ZF-BD) scheme that enables both a more simplified ZF-BD and further increase in sum rate of MU-MIMO channels is proposed in this paper. The proposed scheme provides the improvement in BER performance for equivalent SU-MIMO channels. The proposed scheme consists of two components. First, a permuted channel matrix (PCM), which is given by moving the submatrix related to a target user to the bottom of a downlink MIMO channel matrix, is newly defined to obtain a precoding matrix for ZF-BD. Executing QR decomposition alone for a given PCM provides null space for the target user. Second, a partial MSQRD (PMSQRD) algorithm, which adopts MSQRD only for a target user to provide improvement in bit rate and BER performance for the user, is proposed. Some numerical simulations are performed, and the results show improvement in sum rate performance of the total system. In addition, appropriate bit allocation improves the bit error rate (BER) performance in each equivalent SU-MIMO channel. A successive interference cancellation is applied to achieve further improvement in BER performance of user terminals.

Conventional subband ADF's (adaptive digital filters) using filter banks have shown a degradation in performance because of the non-ideal nature of filters. To solve this problem, we propose a new type of subband ADF incorporating two types of analysis filter bank. In this paper, we show that we can design the optimum filter bank which minimizes the LMSE (least mean squared error). In other words, we can design a subband ADF with less MSE than that of conventional subband ADF's.

In this report, we propose a robust block adaptive digital filter (BADF) which can improve the accuracy of the estimated weights by averaging the adaptive weight vectors. We show that the improvement of the estimated weights is independent of the input signal correlation.

In this paper, we propose a zero-forcing (ZF) Tomlinson-Harashima precoding (THP) with substream permutations based on the bit rate maximization for single-user MIMO (SU-MIMO) systems. We study the effect of substream permutations on the ZF-THP SU-MIMO systems, when the mean squared error (MSE) and the bit rate are adopted for the selection of the permutation matrix as criteria. Based on our analysis, we propose a method to increase the bit rate by substream permutations, and derive QR and Cholesky decomposition-based algorithms which realize the proposed method. Furthermore, to improve the error rate performance, we apply zero transmission to subchannels with low signal-to-noise ratios. Numerical examples are provided to demonstrate the effectiveness of the proposed THP MIMO system.

Orthogonal frequency division multiplexing (OFDM) is an attractive technique to accomplish wired or wireless broadband communications. Since it has been adopted as the terrestrial digital-video-broadcasting standard in Europe, it has also subsequently been embedded into many broadband communication standards. Many techniques for frame timing and frequency synchronization of OFDM systems have been studied as a result of its increasing importance. We propose a new technique of simultaneously synchronizing frame timing and frequency utilizing matched filters. First, a new short preamble consisting of short sequences multiplied by a DBPSK coded sequence is proposed. Second, we show that the new short preamble results in a new structure for matched filters consisting of a first matched filter, a DBPSK decoder, and a second matched filter. We can avoid the adverse effects of carrier frequency offset (CFO) when frame timing is synchronized because a DBPSK decoder has been deployed between the first and second matched filters. In addition, we show that the CFO can be directly estimated from the peak value of matched filter output. Finally, our simulation results demonstrate that the proposed scheme outperforms the conventional schemes.

An alias free parallel structure for adaptive digital filters (ADF's) is considered. The method utilizes the properties of the Frequency-Sampling Filter (FSF) banks to obtain alias free points in the frequency domain. We propose a new cost function for parallel ADF's. The limiting value analysis of system identification using proposed cost function is given in stochastic sense. It is also shown by simulation examples that we can carry out precise system identification. The cost function is defined in each bin; accordingly, it enables the parallel processing of ADF's.

In this paper, we propose a new structure of blind equalizer and its cost function. The proposed cost function is a quadratic form and has the unique solution. In addition, the proposed scheme can employ iterative algorithms which achieve less computational complexity and can be easily realized in real time processing. In order to verify the effectiveness of the proposed schemes, several computer simulations including a 64-QAM signal equalization have been shown.

In case of the system identification problem, such as an echo canceller, estimated impulse response obtained by the frequency-domain adaptive filter based on the circular convolution has estimation error because the unknown system is based on the linear convolution in the time domain. In this correspondence, we consider a sufficient condition to reduce the estimation error.

An adaptive bit allocation scheme for zero-forcing (ZF) Tomlinson-Harashima precoding (THP) is proposed. The ZF-THP enables us to achieve feasible bit error rate (BER) performance when appropriate substream permutations are installed at the transmitter. In this study, the number of bits in each substream is adaptively allocated to minimize the average BER in fading environments. Numerical examples are provided to compare the proposed method with eigenbeam space division multiplexing (E-SDM) method.

Two-dimensional (2-D) adaptive digital filters (ADFs) for 2-D signal processing have become a fascinating area of the adaptive signal processing. However, conventional 2-D FIR ADF's require a lot of computations. For example, the TDLMS requires 2N2 multiplications per pixel. We propose a new 2-D adaptive filter using the FFTs. The proposed adaptive filter carries out the fast convolution using overlap-save method, and has parallel structure. Thus, we can reduce the computational complexity to O(log2N) per pixel.