This paper presents an adaptive feedback canceller (AFC) based on a pseudo affine projection (PAP) algorithm that can provide fast and stable adaptation to the time-varying environment. The proposed algorithm utilizes the adaptive linear prediction (LP) to obtain the LP coefficients of input signal model and the inverse gain filter (IGF) to alleviate the effect of compensation gain. As a result, when the input is model as an AR signal, the proposed algorithm satisfies the condition for having an almost unbiased estimatie of the feedback path and then its performance is relatively independent of the gain setting of hearing aids. Simulation results showed that the proposed algorithm is capable of obtaining unbaised feedback path estimates and high speech quality.

For the modeling of power amplifiers (PAs) using sub-Nyquist-rate sampling (sub-sampling), a quadratic down-converting architecture with a parallel-cascade method is suggested. Its performance was analyzed regarding the sampling rate below the input Nyquist rate. As a result, the model from the sub-sampling below the input Nyquist rate characterized long-term memory effects whereas the memoryless model could not. The measurement results from RF PAs with the mWiMAX signal verified the modeling performance of this architecture. Also, for the modeling of memoryless PAs, it was shown that this sub-sampled model is still effective regardless of the sampling rate.

When we design a robust vector quantizer (VQ) for noisy channels, an appropriate index assignment function should be contrived to minimize the channel-error effect. For relatively high rates, the complexity for finding an optimal index assignment function is too high to be implemented. To overcome such a problem, we use a structurally constrained VQ, which is called the sample-adaptive product quantizer (SAPQ) [12], for low complexities of quantization and index assignment. The product quantizer (PQ) and its variation SAPQ [13], which are based on the scalar quantizer (SQ) and thus belong to a class of the binary lattice VQ [16], have inherent error resilience even though the conventional affine index assignment functions, such as the natural binary code, are employed. The error resilience of SAPQ is observed in a weak sense through worst-case bounds. Using SAPQ for noisy channels is useful especially for high rates, e.g., > 1 bit/sample, and it is numerically shown that the channel-limit performance of SAPQ is comparable to that of the best codebook permutation of binary switching algorithm (BSA) [23]. Further, the PQ or SAPQ codebook with an affine index assignment function is used for the initial guess of the conventional clustering algorithm, and it is shown that the performance of the best BSA can be easily achieved.

This paper suggests an outphasing scheme to reduce adjacent channel spectral regrowth triggered by the gain and phase mismatch between two signal paths in linear amplification with nonlinear component (LINC) systems. The error vector magnitude and power spectral density of the output signal considering path mismatch are described analytically using path mismatch factor. An outphasing scheme is proposed to reduce the spectral regrowth. The proposed outphasing scheme reshapes the phases of the separated signals in LINC systems to reduce the changes of the phases. Its performance is verified by performing simulations with multi-tone signals. The result shows that the scheme can reduce the spectral regrowth of the multi-tone signals significantly compared to the conventional outphasing scheme for LINC systems with path imbalance.

To use the voluntary electromyogram (EMG) as a control signal of the EMG controlled functional electrical stimulator (FES), it is required to reduce the stimulation artifact and non-voluntary contribution (M-wave). In this study, a Gram-Schmidt (GS) prediction error filter (PEF) that can effectively eliminates the M-wave from voluntary EMG is presented. Also, the presented GS PEF is implemented on the field the programmable gate array (FPGA) for real-time processing and the performance is tested with simulated and real signals. Experimental results showed that GS-PEF was effective in reducing M-wave and preserving voluntary EMG.

This letter describes a method that characterizes and improves the performance of a time-interleaved (TI) digital-to-analog converter (DAC) system by using multiport signal-flow graphs at microwave frequencies. A commercial signal generator with two TI DACs was characterized through s-parameter measurements and was compared to the conventional method. Moreover, prefilters were applied to correct the response, resulting in an error-vector magnitude improvement of greater than 8 dB for a 64-quadrature-amplitude-modulated signal of 4.8 Gbps. As a result, the bandwidth limitation and the complex post processing of the conventional method could be minimized.

This paper discusses an efficient discrete model for nonlinear RF power amplifier (PA) with long-term memory effects and analyzes its error. The procedure of converting RF signals and systems into a discrete domain is explained for a discrete baseband memory polynomial model. Unlike a previous simple memory polynomial model, the proposed discrete model has two different sampling frequencies: one for nonlinear system with long-term memory effects and one for input signal. A method to choose an optimal sampling frequency for the system and a discrete memory depth is proposed to minimize the sensitivity of the system for perturbation of the measured data. A two-dimensional sensitivity function which is a product of relative residual and matrix condition number is defined for least square problem of the proposed model. Examples with a wideband WiBro 3FA signal and a WCDMA 4FA signal for nonlinear transmitters are presented to describe the overall procedure and effectiveness of the proposed scheme.

For realizing wideband class-F power amplifiers (PA), geo-electrical analysis methods are introduced to determine the best design parameters in a simpler way than relying on computer-guided optimization. The fabricated class-F PA at 1.9 GHz demonstrated a peak efficiency of 80.5% and a bandwidth of 750 MHz for an efficiency of more than 63%. It is presumed that the optimization increased the bandwidth by 10%.