Orthogonal Frequency Division Multiplexing (OFDM) transmission is robust to frequency-selective channels but sensitive to time-selective channels. Time variations of channels generate inter-carrier interference (ICI), which degrades system performance. In this paper, we develop frequency-domain Viterbi-type algorithm to effectively suppress the ICI, by exploiting the property of ICI terms in OFDM symbols. Null subcarriers, which are embedded in OFDM symbols for the reduction of interferences from/to adjacent bands, are exploited to reduce the complexity of the algorithm. Then, an approximate BER expression of Viterbi-type equalizer is derived. Simulations are provided to show the Viterbi-type equalizer works well in time- and frequency-selective (doubly selective) channel with affordable complexity.

For copyright protection, a watermark signal is embedded in host images with a secret key, and a correlation is applied to judge the presence of watermark signal in the watermark detection. This paper treats a discrete wavelet transform (DWT)-based image watermarking method under specified false positive probability. We propose a new watermarking method to improve the detection performance by using not only positive correlation but also negative correlation. Also we present a statistical analysis for the detection performance with taking into account the false positive probability and prove the effectiveness of the proposed method. By using some experimental results, we verify the statistical analysis and show this method serves to improve the robustness against some attacks.

We study the bit-error rate (BER) for different code lengths and number of users in CDMA system with linear minimum mean squared error (MMSE) and non-linear equalizations. We first show that for a fix channel and a fix number of users, BER of each symbol after linear equalization degrades with a decrease in the code length. Then, we prove that for a fix code length, the BER averaged over random channels improves with a decrease in the number of users. Furthermore, in the non-linear serial-interference cancellation (SIC) scheme, we prove analytically that the BER improves with each step of symbol cancellation for any channel not just at high signal-to-interference noise ratio (SINR) but at all range of SINR. Simulation results are presented to substantiate our theoretical findings.

The minimization problem of an L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints is formulated for a class of two-dimensional (2-D) state-space digital filters. First, the problem is converted into an unconstrained optimization problem by using linear-algebraic techniques. Next, the unconstrained optimization problem is solved by applying an efficient quasi-Newton algorithm with closed-form formula for gradient evaluation. The coordinate transformation matrix obtained is then used to synthesize the optimal 2-D state-space filter structure that minimizes the L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints. Finally, a numerical example is presented to illustrate the utility of the proposed technique.

Simple but efficient antenna selection schemes are proposed for the downlink of Orthogonal Frequency Division Multiplexing (OFDM) transmission with multiple transmit antennas over frequency selective fading channels, where transmit antennas are selected at the mobile terminal and the base station is informed of the selected antennas through feedback channel. To obtain the optimal antenna selection, channel frequency responses are required and performances have to be evaluated at all the subcarriers. To reduce the computational complexity at mobile terminal, time-domain channels are utilized for antenna selection in place of channel frequency responses. Our scheme does not guarantee the optimal antenna selection but is shown by numerical simulations to yield reasonable selections. Moreover, by using a specially designed pilot OFDM preamble, an antenna selection without channel estimation is developed. Efficiencies of our suboptimal antenna selections with less computational complexities are verified by numerical simulations.

In Orthogonal Frequency Division Multiplexing (OFDM), the composite time signal exhibits a high peak-to-average power ratio (PAPR). Due to non-linearities of the transmit power amplifiers, this high PAPR generates in-band distortion, out of band noise (OBN) or spectral spreading, which degrades the bit-error rate (BER) performance. In this paper, we propose a simple way to combat this problem without sacrificing channel estimation and frequency-offset tracking accuracy, by designing a sub-optimal configuration of the pilot tones. The effectiveness of the newly designed pilot tones in reducing PAPR is validated by Monte-Carlo simulations. The corresponding improvement in BER is also verified by simulations under IEEE 802.11a standard settings, by using the channel with perfect CSI and the designed pilot-aided estimated channel for coherent detection.

To take intercarrier interference (ICI) attributed to time variations of the channel into consideration, the time- and frequency-selective (doubly-selective) channel is parameterized by a finite parameter model. By capitalizing on the finite parameter model to approximate the doubly-selective channel, a Kalman filter is developed for channel estimation. The ICI suppressing, reduced-complexity Viterbi-type Maximum Likelihood (RML) equalizer is incorporated into the Kalman filter for recursive channel tracking and equalization to improve the system performance. An enhancement in the channel tracking ability is validated by theoretical analysis, and a significant improvement in BER performance using the channel estimates obtained by the recursive channel estimation method is verified by Monte-Carlo simulations.

This paper considers a link of two problems; multichannel blind deconvolution and multichannel blind identification of linear time-invariant dynamic systems. To solve these problems, cumulant maximization has been proposed for blind deconvolution, while cumulant matching has been utilized for blind identification. They have been independently developed. In this paper, a cumulant maximization criterion for multichannel blind deconvolution is shown to be equivalent to a least-squares cumulant matching criterion after multichannel prewhitening of channel outputs. This equivalence provides us with a new link between a cumulant maximization criterion for blind deconvolution and a cumulant matching criterion for blind identification.

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.

In this paper, training symbol designs for estimation of frequency selective channels and compensation of in-phase (I) and quadrature (Q) imbalances on orthogonal frequency division multiplexing (OFDM) transmitters and receivers are studied. We utilize cross entropy (CE) optimization techniques together with convex optimization to design training sequences having low channel estimate mean squared error (MSE) and minimum effects of I/Q mismatch, while lowering the peak power of the training signals. The proposed design provides better channel estimate MSE and bit error rate (BER) performances and is applicable to OFDM systems with and without null subcarriers. The efficacies of the proposed designs are corroborated by analysis and simulation results.

To describe joint time- and frequency-selective (doubly-selective) channels in mobile broadband wireless communications, we propose to use the finite parameter model based on the same Bessel functions for each tap (Bessel model). An expression of channel estimation mean squared error (MSE) based on the finite parameter models in Orthogonal Frequency Division Multiplexing (OFDM) systems is derived. Then, our Bessel model is compared with commonly used finite parameter models in terms of the channel estimation MSE. Even if the channel taps have different channel correlations and some of the taps do not coincide with the Bessel function, the channel estimation MSE of the Bessel model is shown to be comparable or outperform existing models as validated by Monte-Carlo simulations over an ensemble of channels in typical urban and suburban environments.

An algorithm for blind identification of multichannel (single-input and multiple-output) FIR systems is proposed. The proposed algorithm is based on subspace approach to blind identification, which requires so-called noise space spanned by some eigenvectors of correlation matrices of observations. It is shown that a subspace of the noise space can be obtained by one-step scalar-valued linear prediction and then the subspace is sufficient for blind identification. To acquire the subspace, the proposed algorithm utilizes one-step scalar-valued linear prediction in place of a singular- (or eigen-) value decomposition and hence it is computationally efficient. Computer simulations are presented to compare the proposed algorithm with the original one.

Orthogonal Frequency Division Multiple Access (OFDMA) allows multiple users to make use of the same bandwidth as the single-user OFDM for data transmission and is a promising candidate to be used for future cellular systems. A key issue at hand is the rate-adaptive resource allocation problem. In this paper, we propose two basic subcarrier allocation schemes with low complexities based on the magnitude of the channel frequency responses. The proposed algorithms ensure a fair resource allocation in terms of the number of subcarriers with affordable bit-rates. Through extensive discussions and Monte Carlo simulations, a comprehensive comparison with previously derived subcarrier allocation schemes is performed which depicts the pros and cons of our proposed algorithms.

To evaluate or compare the convergence speed of adaptive digital filters (ADF) with least mean squared (LMS) algorithm, the condition numbers of correlation matrices of tap-input vectors are often used. In this paper, however, the comparison of the conventional fullband ADF and the subband ADF based on their condition numbers is shown to be invalid. In some cases, the over-sampled subband ADF converges faster than the fullband ADF, although the former has larger condition numbers. To explain the above phenomenon, an expression for the convergence behavior of the subband ADF and simulation results are provided.

In this paper, challenges regarding the provision of channel state information (CSI) and carrier frequency synchronization for orthogonal frequency division multiplexing (OFDM) systems with null subcarriers are addressed. We propose novel maximum likelihood (ML) based schemes that estimate the aggregate effects of the CFO and channel by using two successive OFDM preambles. In the presented scheme, CFO is estimated by considering the phase rotation between two consecutive received OFDM preambles. Both single input single output (SISO) as well as multiple input multiple output (MIMO) OFDM systems are considered. The mean squared errors (MSE) of the channel and CFO are used to evaluate the performance of our proposed scheme. By using two successive OFDM preambles, the estimation of channel and the estimation of CFO are decoupled, which leads to a simple estimation method. Simulation results show that the BER performance of the proposed estimators is comparable to that of known channel state information and the CFO MSE performance achieves the Cramer-Rao bound (CRB) of the fully loaded OFDM system.

This paper presents an approach to the blind identification of multichannel communication systems by using partial knowledge of the channel. The received signal is first processed by a filter constructed by the known component of the channel and then a blind identification algorithm based on the second-order statistics is applied to the filtered signal. It is shown that, if the unknown component satisfies the identifiability condition, the channel can be identified even though the channel does not satisfy the identifiability condition. Simulation results are presented to show the performance of the proposed approach. A comparison to the existing approaches is also presented.

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.

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 proposes a secure distributed transmission method that establishes multiple transmission routes in space to a destination. In the method, the transmitted information is divided into pieces of information by a secret-sharing method, and the generated pieces are separately transmitted to the destination through different transmission routes using individually-controlled antenna directivities. As the secret-sharing method can divide the transmitted information into pieces in such a manner that nothing about the original information is revealed unless all the divided pieces are obtained, the secrecy of the transmitted information is greatly improved from an information-theoretic basis. However, one problem is that it does not perform well in the vicinity around the receiver. This is due to the characteristics of distributed transmission that all distributed pieces of information must eventually gather at the destination; an eavesdropper can obtain the necessary pieces to reconstruct the original information. Then, this paper expands the distributed transmission method into a two-way communication scheme. By adopting the distributed transmission in both communication directions, a secure link can be provided as a feedback channel to enhance the secrecy of the transmitted information. The generation of the shared pieces of information is given with signal forms, and the secrecy of the proposed method is evaluated based on the signal transmission error rates as determined by computer simulation.