All digital communication channels are subject to inter-symbol interference (ISI). To achieve the desired system performance, at receiver end, the effect of ISI must be compensated and the task of the equalizer is to combat the degrading effects of ISI on the transmission. Due to the demand of high data transmission rate, the multicarrier modulation (MCM) technique implemented with the orthogonal frequency division multiplexing (OFDM) has been adopted in many modern communications systems for block transmission. In block transmission systems, transmitter-included redundancy using finite-impulse response (FIR) filterbanks can be utilized to suppress inter-block-interference (IBI). However, the length of redundancy will affect the system performance, which is highly dependent on the length of channel impulse response. To deal with the effect of ISI, many equalizing schemes have been proposed, among them the FIR zero-forcing (ZF) equalizer with the non-orthogonal projector provides a useful transceiver design structure for suppressing the IBI and ISI, simultaneously. In this thesis, we propose a new equalizing scheme; it combines the FIR-ZF equalizer with non-orthogonal projector as well as the Bayesian decision feedback equalizer (DFE) for IBI and ISI suppression. The Bayesian DFE is known to be one of the best schemes to achieve the desired performance for eliminating ISI. It can be employed to achieve the full potential of symbol-by-symbol equalizer. That is, after removing the effect of IBI with the non-orthogonal projector, the Bayesian DFE is employed for eliminating the ISI, simultaneously. For comparison, the system performance, in term of bit error rate (BER) is investigated, and compared with the minimum mean square error (MMSE)-IBI-DFE. The advantage of the new proposed equalizing scheme is verified via computer simulation under condition of insufficient redundancy.

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In this thesis, an alternative solution for designing power line conductive electromagnetic interference (EMI) filter by using the consecutive orthogonal array method is proposed. The circuit parameters of EMI filters to be determined are assigned as the control variables in the orthogonal arrays, and the average effects corresponding to each control variable are calculated from the measured results. In accordance with the inferential rules, the average effects are used as the observational indices to adjust the levels of the control variables of the subsequent orthogonal array. Through manipulating consecutive orthogonal arrays step by step, the applicable ranges of circuit parameters are approached with desired output performances. Finally, the component values of EMI filters with minimum size can be found. The design procedure and the inferential rules are described by illustrative examples for a single-stage high-power-factor converter.

In polymerase chain reaction (PCR), in order to amplify massive DNA sequences successfully, it needs to design an appropriate primer pair. The constraints derived from the traits of PCR for proceeding PCR are used in searching for primer pairs. In this paper, in order to decrease the searching space and to increase the feasible quality of primers, a double orthogonal arrays intelligent crossover genetic algorithm (DOAIGA) is used to solve the primer design problem. DOAIGA combines the traditional genetic algorithm and the Taguchi methodology to efficiently search feasible primers under required constraints. The proposed intelligent crossover subsystem mainly concentrates on the better genes more systematic. The key point of DOAIGA is to achieve the elitism goal by applying the orthogonal arrays (OAs) that is used in quality engineering with a small amount of experiment features. In this thesis, the double orthogonal arrays are used to approach a better forward and reverse primers separately. Compared to the current existing softwares, DOAIGA can obtain feasible primer pairs more effectively. Finally the correctness of primer pair is verified by PCR experiment.

In this thesis, One of the difficulties in the orthogonal frequency division multiple access (OFDMA) systems is the multi-user interference (MUI) induced by the carrier frequency offset (CFO). In sub-band OFDMA systems, each user occupies a consecutive and non-overlapping frequency sub-band. The pilots are usually placed at the edges of a sub-band for frequency synchronization and channel estimation. However, the both frequency synchronization and channel estimation performance are influenced seriously by the multi-user interference (MUI) induced by CFO of other users. The MUI can be reduced by inserting the guard sub-carrier between adjacent users. In this paper, a novel pilot architecture is investigated, which has the same bandwidth efficiency as the conventional guard sub-carrier insertion scheme. In addition, the proposed pilot architecture provides better carrier frequency synchronization and channel estimation performance than conventional pilot assignment. Moreover, this new pilot architecture also has MUI reduction utility.

Selected mapping (SLM) schemes are commonly employed to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It has been shown that the computational complexity of the traditional SLM scheme can be substantially reduced by adopting conversion vectors obtained by using the inverse fast Fourier transform (IFFT) of the phase rotation vector in place of the conventional IFFT operations [21]. Unfortunately, however, the elements of these phase rotation vectors of the conversion vectors in [21] do not generally have an equal magnitude, and thus a significant degradation in the bit error rate (BER) performance is incurred. This problem can be remedied by utilizing conversion vectors having the form of a perfect sequence. This paper presents three novel classes of perfect sequence, each of which comprises certain base vectors and their cyclic-shifted versions. Three novel low-complexity SLM schemes are then proposed based upon the unique structures of these perfect sequences. It is shown that while the PAPR performances of the proposed schemes are marginally poorer than that of the traditional SLM scheme, the three schemes achieve an identical BER performance and have a substantially lower computational complexity.

One of the major drawbacks of multi-carrier systems is the high peak-to-average power ratio (PAPR) of the transmitted signals. In this paper, the proposed novel low-complexity selective mapping (SLM) schemes are applicable to interleaved-4 orthogonal frequency division multiple access (OFDMA) uplink systems for PAPR reduction. The novel scheme just needs one inverse fast Fourier transform (IFFT) block because that the phases of the transmitted signals in frequency domain are rotated by circular convolution with conversion vectors in time domain. Moreover, a special set of conversion vectors are proposed in novel scheme, which are not only computed with low complexity but also reduce the PAPR effectively. In proposed scheme, different conversion vectors and appropriate subcarriers mapping are picked up for different users. The scheme supplies a practicable low-complexity method for PAPR reduction in interleaved-4 OFDMA uplink systems. Besides, the bit error rate (BER) performance is as good as the SLM scheme.

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology has been used widely in many wireless communication systems. Signals will be distorted when they are transmitted in wireless channels. For the reason that wireless channel is time or location variant, we have to estimate the channel impulse response and use the channel state information to compensate the channel distortion. In order to estimate the state of the channel, let the known training symbols put in front of the data symbols and use training symbols to estimate channel response. A typical channel estimate for MIMO OFDM systems is treated as spatially uncorrelated. However in many realistic scenarios, the channel tends to be spatially correlated. Indeed, we have no prior knowledge of the channel spatial correlation. So consider the spatial correlation, the channel can estimate accurately. And it is important that how to combine spatial correlation and channel estimation to reduce the estimation error. In the paper we propose a iterative channel spatial correlation and channel estimation algorithm. At first, channel spatial correlation estimation is obtained by synchronize symbols. The receiver uses the estimated channel to help the detection/decision of data symbol. And then the channel estimation treats the detected signals as known data to perform a next stage channel estimation iteratively. By utilizing the iterative channel estimation and signal detection process we can reduce the estimation error caused by channel spatial correlation estimation. The accuracy of the channel estimation can be improved by increasing the number of iteration process. Simulation results demonstrate the iterative spatial correlation and channel estimation algorithm can provide better mean-square-error performance.

The Orthogonal frequency division multiplexing (OFDM) modulator with redundancy has been adopted in many wireless communication systems for higher data rate transmissions .The block transmission of signal-blocks through the channel will suffer from the inter-block interference (IBI) and inter-symbol interference (ISI). In the traditional transmitter of the OFDM systems, redundancy (or guard interval), such cyclic prefix (CP) or zero padding (ZP), with sufficient length, is inserted in the transmitted block to avoid the IBI. In this thesis, we propose a novel pseudo random cyclic postfix (PRCP-) OFDM system configuration and joint a blind channel shortening algorithm which named MERRY algorithm [18], which adopts the PRCP as redundancy and combines with multiple antennas. In fact, the multiple input and multiple output (MIMO) system, which exploits the spatial diversity, it can be used to further enhance the channel capacity and achieve high data-rate, and we extend the PRCP-OFDM to the MIMO case with space-time block coding. In redundancy insufficient case, the blind channel shortening algorithm be adopted for suppressing the IBI. The main property of PRCP-OFDM modulation is that it exploits the cyclic-postfix sequences to estimate channel information with a low complexity method. For CP-OFDM, it overcomes the channel null problem. Compared with ZP-OFDM, it uses the additional information to estimate channel which is replaced by zero samples in ZP-OFDM. Moreover, PRCP-OFDM avoids the interference of signals to the desired postfix when we estimate channel impulse response (CIR) and which is different from pseudo random postfix (PRP-) OFDM [8]. Thus, when SNR grows, PRCP-OFDM can have better performance than PRP-OFDM. With the help of [9], [12] and [13]. Via computer simulation, we verify that the performance is improved.

Müntz polynomials arise from consideration of Müntz's Theorem, which is a beautiful generalization of Weierstrass's Theorem. We prove a new surprisingly simple representation for the Müntz orthogonal polynomials on the interval of orthogonality, and in particular obtain new formulas for some of the classical orthogonal polynomials (e.g. Legendre, Jacobi, Laguerre). This allows us to determine the strong asymptotics and endpoint limit asymptotics on the interval. The zero spacing behavior follows, as well as estimates for the smallest and largest zeros. This is the first time that such asymptotics have been obtained for general Müntz exponents. We also look at the asymptotic behavior outside the interval and the asymptotic properties of the associated Christoffel functions.