Polynomial matrix eigenvalue decomposition techniques for multichannel signal processing

Polynomial eigenvalue decomposition (PEVD) is an extension of the eigenvalue decomposition (EVD) for para-Hermitian polynomial matrices, and it has been shown to be a powerful tool for broadband extensions of narrowband signal processing problems. In the context of broadband sensor arrays, the PEVD allows the para-Hermitian matrix that results from the calculation of a space-time covariance matrix of the convolutively mixed signals to be diagonalised. Once the matrix is diagonalised, not only can the correlation between different sensor signals be removed but the signal and noise subspaces can also be identified. This process is referred to as broadband subspace decomposition, and it plays a very important role in many areas that require signal separation techniques for multichannel convolutive mixtures, such as speech recognition, radar clutter suppression, underwater acoustics, etc. The multiple shift second order sequential best rotation (MS-SBR2) algorithm, built on the most established SBR2 algorithm, is proposed to compute the PEVD of para-Hermitian matrices. By annihilating multiple off-diagonal elements per iteration, the MS-SBR2 algorithm shows a potential advantage over its predecessor (SBR2) in terms of the computational speed. Furthermore, the MS-SBR2 algorithm permits us to minimise the order growth of polynomial matrices by shifting rows (or columns) in the same direction across iterations, which can potentially reduce the computational load of the algorithm. The effectiveness of the proposed MS-SBR2 algorithm is demonstrated by various para-Hermitian matrix examples, including randomly generated matrices with different sizes and matrices generated from source models with different dynamic ranges and relations between the sources’ power spectral densities. A worked example is presented to demonstrate how the MS-SBR2 algorithm can be used to strongly decorrelate a set of convolutively mixed signals. Furthermore, the performance metrics and computational complexity of MS-SBR2 are analysed and compared to other existing PEVD algorithms by means of numerical examples. Finally, two potential applications of theMS-SBR2 algorithm, includingmultichannel spectral factorisation and decoupling of broadband multiple-input multiple-output (MIMO) systems, are demonstrated in this dissertation

Enhanced multi-user DMT spectrum management using polynomial matrix decomposition techniques

This thesis researches the increasingly critical roles played by intelligent resource management and interference mitigation algorithms in present-day input multiple output (MIMO) communication systems. This thesis considers the application of polynomial matrix decomposition (PMD) algorithms, an emerging broadband factorisation technology for broadband MIMO access networks. Present DSL systems’ performance is constrained by the presence of interference (crosstalk) between multiple users sharing a common physical cable bundle. Compared to the traditional static spectrum management methods that define their survival to the worst-case scenarios, DSM methods provides some degree of flexibility to both direct channel and noise parameters to improve evolvability and robustness significantly. A novel crosstalk-aware DSM algorithm is proposed for the efficient management of multi-user DSL systems. Joint power allocation procedures are considered for the proposed single-channel equalisation method in DSL access networks. This thesis then shows that DSM can also benefit overdetermined precoding-equalisation systems, when the channel state information (CSI) parameters call for a specific decision feedback criterion to achieve a perfect reconstruction. A reasonable redundancy is introduced to reformulate the original multi-user MIMO problem into the simplest case of power management problem. DSM algorithms are primarily applied to solve the power allocation problem in DSM networks with the aim of maximising the system attribute rather than meeting specific requirements. Also, a powerful PMD algorithm known as sequential matrix diagonalisation (SMD) is used for analysing the eigenvalue decomposition problem by quantifying the available system resource including the effects of the crosstalk and its parameters. This analysis is carried out through joint precoding and equalisation structures. The thesis also investigates dynamic interference mitigation strategies for improving the performance of DSL networks. Two different mitigation strategies through a decision feedback equalisation (DFE) criterion are considered, including zero-forcing (ZF) and minimum mean square error (MMSE) equalisers. The difference between ZF and MMSE equalisations is analysed. Some experimental simulation results demonstrate the performance of both ZF and MMSE equalisation under the DFE equalisation constraint settings. Model reduction on the MMSE equalisation is thus applied to balance the crosstalk interference and enhance the data-rate throughput. Finally, the thesis studies a multi-user MIMO problem under the utility maximisation framework. Simulation results illustrate that the power allocation of multi-user DSL transmission can be jointly controlled and the interference can often be mitigated optimally on a single user basis. Driven by imperfect CSI information in current DSL networks, the research presents a novel DSM method that allows not only crosstalk mitigation, but also the exploitation of crosstalk environments through the fielding of versatile, flexible and evolvable systems. The proposed DSM tool is presented to achieve a robust mitigating system in any arbitrary overdetermined multi-user MIMO environment. Numerical optimisation results show that the mitigation of crosstalk impairment using the proposed DSM strategy. The design and implementation of the proposed DSM are carried out in the environment of MATLAB

Polynomial matrix algebra with applications

[Abstract unavailable

Characterizations of Families of Rectangular, Finite Impulse Response, Para-Unitary Systems

We here study Finite Impulse Response (FIR) rectangular, not necessarily causal, systems which are (para)-unitary on the unit circle (=the class U). First, we offer three characterizations of these systems. Then, introduce a description of all FIRs in U, as copies of a real polytope, parametrized by the dimensions and the McMillan degree of the FIRs. Finally, we present six simple ways (along with their combinations) to construct, from any FIR, a large family of FIRs, of various dimensions and McMillan degrees, so that whenever the original system is in U, so is the whole family. A key role is played by Hankel matrices

Use of frequency response masking technique in designing A/D converter for SDR.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.Analog-to-digital converters (ADCs) are required in almost all signal processing and communication systems. They are often the most critical components, since they tend to determine the overall system performance. Hence, it is important to determine their performance limitations and develop improved realizations. One of the most challenging tasks for realizing software defined radio (SDR) is to move ND conversion as close to the antenna as possible, this implies that the ADC has to sample the incoming signal with a very high sample rate (over 100 MSample/s) and with a very high resolution (14 -to -16 bits). To design and implement AID converters with such high performance, it is necessary to investigate new designing techniques. The focus in this work is on a particular type of potentially high-performance (high-resolution and highspeed) analog-to-digital conversion technique, utilizing filter banks, where two or more ADCs are used in the converter array in parallel together with asymmetric filter banks. The hybrid filter bank analog-todigital converter (HFB ADC) utilizes analog filters (analysis filters) to allocate a frequency band to each ADC in a converter array and digital synthesis filters to reconstruct the digitized signal. The HFB improves the speed and resolution of the conversion, in comparison to the standard time-interleaving technique by attenuating the effect of gain and phase mismatches between the ADCs. Many of the designs available in the literature are compromising between some metrics: design complexity, order of the filter bank (computation time) and the sharpness of the frequency response rolloff (the transition from the pass band to the stop band). In this dissertation, five different classes of near perfect magnitude reconstruction (NPMR) continuoustime hybrid filter banks (CT HFBs) are proposed. In each of the five cases, two filter banks are designed; analysis filter bank and synthesis filter bank. Since the systems are hybrid, continuous time IlR filter are used to implement the analysis filter bank and digital filters are used for the synthesis filter bank. To optimize the system, we used a new technique, known in the literature as frequency response masking (FRM), to design the synthesis filter bank. In this technique, the sharp roll-off characteristics can be achieved while keeping the complexity of the filter within practical range, this is done by splitting the filter into two filters in cascade; model filter with relaxed roll-off characteristics followed by a masking filter. One of the main factors controlling the overall complexity of the filter is the way of designing the model filter and that of designing the masking filter. The dissertation proposes three combinations: use of HR model filter and IlR masking filter, HR model filter/FIR masking filter and FIR model filter/FIR masking filter. To show the advantages of our designs, we considered the cases of designing the synthesis filter as one filter, either FIR or IlR. These two filters are used as base for comparison with our proposed designs (the use of masking response filter). The results showed the following: 1. Asymmetric hybrid filter banks alone are not sufficient for filters with sharp frequency response roll-off especially for HR/FIR class. 2. All classes that utilize FRM in their synthesis filter banks gave a good performance in general in comparison to conventional classes, such as the reduction of the order of filters 3. HR/HR FRM gave better performance than HR/FIR FRM. 4. Comparing HR/HR FRM using FIR masking filters and HR/IIR FRM using IIR masking filters, the latter gave better performance (the performance is generally measured in terms of reduced filter order). 5. All classes that use the FRM approach have a very low complexity, in terms of reduced filter order. Our target was to design a system with the following overall characteristics: pass band ripple of -0.01 dB, stop band minimum attenuation of - 40 dB and of response roll-off of 0.002. Our calculations showed that the order of the conventional IIR/FIR filter that achieves such characteristics is aboutN =2000. Using the FRM technique, the order N reduced to aboutN = 244, N = 179 for IIRJFIR and IIR/IIR classes, respectively. This shows that the technique is very effective in reducing the filter complexity. 6. The magnitude distortion and the aliasing noise are calculated for each design proposal and compared with the theoretical values. The comparisons show that all our proposals result in approximately perfect magnitude reconstruction (NPMR). In conclusion, our proposal of using frequency-response masking technique to design the synthesis filter bank can, to large extent, reduce the complexity of the system. The design of the system as a whole is simplified by designing the synthesis filter bank separately from the design of the analysis filter bank. In this case each bank is optimized separately. This implies that for SDR applications we are proposing the use of the continuous-time HFB ADC (CT HFB ADC) structure utilizing FRM for digital filters