Design of optimal equalizers and precoders for MIMO channels

Channel equalization has been extensively studied as a method of combating ISI and ICI for high speed MIMO data communication systems. This dissertation focuses on optimal channel equalization in the presence of non-white observation noises with unknown PSD but bounded power-norm. A worst-case approach to optimal design of channel equalizers leads to an equivalent optimal H-infinity filtering problem for the MIMO communication systems. An explicit design algorithm is derived which not only achieves the zero-forcing (ZF) condition, but also minimizes the RMS error between the transmitted symbols and the received symbols. The second part of this dissertation investigates the design of optimal precoders which minimize the bit error rate (BER) subject to a fixed transmit-power constraint for the multiple antennas downlink communication channels under the perfect reconstruction (PR) condition. The closed form solutions are derived and an efficient design algorithm is proposed. The performance evaluations indicate that the optimal precoder design for multiple antennas communication systems proposed herein is an attractive/reasonable alternative to the existing precoder design techniques

Advanced transceivers for spectrally-efficient communications

In this thesis, we will consider techniques to improve the spectral efficiency of digital communication systems, operating on the whole transceiver scheme. First, we will focus on receiver schemes having detection algorithms with a complexity constraint. We will optimize the parameters of the reduced detector with the aim of maximizing the achievable information rate. Namely, we will adopt the channel shortening technique. Then, we will focus on a technique that is getting very popular in the last years (although presented for the first time in 1975): faster-than-Nyquist signaling, and its extension which is time packing. Time packing is a very simple technique that consists in introducing intersymbol interference on purpose with the aim of increasing the spectral efficiency of finite order constellations. Finally, in the last chapters we will combine all the presented techniques, and we will consider their application to satellite channels.Comment: PhD Thesi

Design and analysis of iteratively decodable codes for ISI channels

Recent advancements in iterative processing have allowed communication systems to perform close to capacity limits withmanageable complexity.For manychannels such as the AWGN and flat fading channels, codes that perform only a fraction of a dB from the capacity have been designed in the literature. In this dissertation, we will focus on the design and analysis of near-capacity achieving codes for another important class of channels, namely inter-symbol interference (ISI)channels. We propose various coding schemes such as low-density parity-check (LDPC) codes, parallel and serial concatenations for ISI channels when there is no spectral shaping used at the transmitter. The design and analysis techniques use the idea of extrinsic information transfer (EXIT) function matching and provide insights into the performance of different codes and receiver structures. We then present a coding scheme which is the concatenation of an LDPC code with a spectral shaping block code designed to be matched to the channel??s spectrum. We will discuss how to design the shaping code and the outer LDPC code. We will show that spectral shaping matched codes can be used for the parallel concatenation to achieve near capacity performance. We will also discuss the capacity of multiple antenna ISI channels. We study the effects of transmitter and receiver diversities and noisy channel state information on channel capacity

Joint bit allocation and precoding for filterbank transceivers in NOFDM systems

Recently, the non orthogonal frequency division multiplexing (NOFDM) systems have attracted increased interest. They have several advantages over traditional OFDM systems: higher bandwidth efficiency; reduced sensitivity to carrier frequency offsets, oscillator phase noise and narrowband interference; and reduced intersymbol/intercarrier interference (ISI/ICI). In particular, low ISI/ICI will be important for future systems where Doppler frequencies will be larger (equivalently, channel variations will be faster) due to higher carrier frequencies and higher mobile velocities. In the first part of this thesis the duality of multicarrier systems and Gabor frames is discussed and applied to the design of a generalized multicarrier system based on a filterbank structure. The efficient polyphase implementation is also discussed. In this thesis the channel capacity of a GMC systems is evaluated through the diagonalization of an equivalent matrix model where intersymbol and intercarrier interferences have been included. Exploiting the majorization theory, the mutual information can be represented as a Schur-concave function and it is maximized through a joint transceiver design adding a linear precoder at the transmitter and a LMMSE equalizer at the receiver. The capacity is derived by the eigenvalue decomposition of the global system matrix including the noise colored by the receiver filtering and employing a power allocation of the transmitted power according to the well-known water-filling solution. This thesis investigates also the behaviour of the NOFDM systems when a power and bit allocation algorithm (like the Campello one) is employed in order to satisfy a certain QoS constrain. A comparison of the performances with OFDM systems is included. Finally a simple application of the cognitive radio paradigm employing filterbankbased multicarrier systems is developed and some interesting results are showed

Optimum quantization for the adaptive loops in MDFE

Multi-level decision feedback equalization (MDFE) is a sampled signal processing technique for data recovery from magnetic recording channels which use the 2/3(1,7) run length limited code. The key adaptive feedback loops in MDFE are those which perform the timing recovery, gain recovery, dc offset detection, and adaptive equalization of the feedback equalizer. The algorithms used by these adaptive loops are derived from the channel error which is the deviation of the equalized signal from its ideal value. It is advantageous to convert this error signal to a digital value using a flash analog-to-digital converter (flash ADC) to simplify the implementation of the adaptive loops. In this thesis, a scheme to place the thresholds of the flash ADC is presented. The threshold placement has been optimized based on the steady-state probability density function (pdf) of the signal to be quantized. The resolution constraints imposed by this quantization scheme on the adaptive loops has been characterized. As the steady-state assumption for the signal to be quantized is not valid during the transient state of the adaptive loops, the loop transients with this quantization scheme have been analyzed through simulations. The conditions under which the channel can recover from a set of start-up errors and converge successfully into steady-state have been specified. The steady-state channel performance with the noise introduced by the iterative nature of the adaptive loops along with this quantization scheme has also been verified

Constrained Linear and Non-Linear Adaptive Equalization Techniques for MIMO-CDMA Systems

Researchers have shown that by combining multiple input multiple output (MIMO) techniques with CDMA then higher gains in capacity, reliability and data transmission speed can be attained. But a major drawback of MIMO-CDMA systems is multiple access interference (MAI) which can reduce the capacity and increase the bit error rate (BER), so statistical analysis of MAI becomes a very important factor in the performance analysis of these systems. In this thesis, a detailed analysis of MAI is performed for binary phase-shift keying (BPSK) signals with random signature sequence in Raleigh fading environment and closed from expressions for the probability density function of MAI and MAI with noise are derived. Further, probability of error is derived for the maximum Likelihood receiver. These derivations are verified through simulations and are found to reinforce the theoretical results. Since the performance of MIMO suffers significantly from MAI and inter-symbol interference (ISI), equalization is needed to mitigate these effects. It is well known from the theory of constrained optimization that the learning speed of any adaptive filtering algorithm can be increased by adding a constraint to it, as in the case of the normalized least mean squared (NLMS) algorithm. Thus, in this work both linear and non-linear decision feedback (DFE) equalizers for MIMO systems with least mean square (LMS) based constrained stochastic gradient algorithm have been designed. More specifically, an LMS algorithm has been developed , which was equipped with the knowledge of number of users, spreading sequence (SS) length, additive noise variance as well as MAI with noise (new constraint) and is named MIMO-CDMA MAI with noise constrained (MNCLMS) algorithm. Convergence and tracking analysis of the proposed algorithm are carried out in the scenario of interference and noise limited systems, and simulation results are presented to compare the performance of MIMO-CDMA MNCLMS algorithm with other adaptive algorithms

Multi-User Signal and Spectra Coordination for Digital Subscriber Lines

The appetite amongst consumers for ever higher data-rates seems insatiable. This booming market presents a huge opportunity for telephone and cable operators. It also presents a challenge: the delivery of broadband services to millions of customers across sparsely populated areas. Fully fibre-based networks, whilst technically the most advanced solution, are prohibitively expensive to deploy. Digital subscriber lines (DSL) provide an alternative solution. Seen as a stepping-stone to a fully fibre-based network, DSL operates over telephone lines that are already in place, minimizing the cost of deployment. The basic principle behind DSL technology is to increase data-rate by widening the transmission bandwidth. Unfortunately, operating at high frequencies, in a medium originally designed for voice-band transmission, leads to crosstalk between the different DSLs. Crosstalk is typically 10-15 dB larger than the background noise and is the dominant source of performance degradation in DSL. This thesis develops practical multi-user techniques for mitigating crosstalk in DSL. The techniques proposed have low complexity, low latency, and are compatible with existing customer premises equipment (CPE). In addition to being practical, the techniques also yield near-optimal performance, operating close to the theoretical multi-user channel capacity. Multi-user techniques are based on the coordination of the different users in a network, and this can be done on either a spectral or signal level

Space-time-frequency block codes for MIMO-OFDM in next generation wireless systems

In this thesis the use of space-frequency block codes (SFBC) and space-time-frequency block codes (STFBC) in wireless systems are investigated. A variety of SFBC and STFBC schemes are proposed for particular propagation scenarios and system settings where each has its own advantages and disadvantages. The objective is to pro-pose coding strategies with improved flexibility, feasibility and spectral efficiency,and reduce the decoding complexity in an MIMO-OFDM system. Firstly an efficient SFBC with improved system performance is proposed for MIMO-OFDM systems. The proposed SFBC incorporates the concept of matched rotation precoding (MRP) to achieve full transmit diversity and optimal system performance foran arbitrary numberoftransmitantennas,subcarrierinterval andsubcarriergrouping. The MRP is proposed to exploit the inherent rotation and repetition properties of SFBC, arising from the channel power delay profile, in order to fully capture both space and frequency diversity of SFBC in a MIMO-OFDM system. It is able to relax restrictions on subcarrier interval and subcarrier grouping, making it ideal for adaptive/time-varying systems or multiuser systems. The SFBC without an optimization process is unstable in terms of achievable system performance and diversity order, and also risks diversity loss within a specific propagation scenario. Such loss or risk is prominent while wireless propagation channel has a limited number of dominant paths, e.g. relatively close to transmitters or relatively flat topography. Hence in orderto improve the feasibility of SFBC in dynamic scenarios, the lower bound of the coding gain for MRP is derived. The SFBC with MRP is proposed for more practical scenarios when only partial channel power delay profile information is known at the transmit end, for example the wireless channel has dominant propagation paths. The proposed rate one MRP has a relatively simple optimization process that can be transformed into an explicit diagram and hence an optimal result can be derived intuitively without calculations. Next, a multi-rate transmission strategy is proposed for both SFBCand STFBC to balance the system performance and transmission rate. A variety of rate adaptive coding matrices are obtained by a simple truncation of the coding matrix, or by parameter optimization for coding matrices for a given transmission rate and constellation. Pro-posed strategy can easily and gradually adjust the achievable diversity order. As a result it is capable of achieving a relatively smooth balance between system performance and transmission rate in both SFBC and STFBC, without a significant change of coding structure or constellation size. Such tradeoff would be useful to maintain stable Quality of Service (QoS) for users by providing more scalability of achievable performance in a time-varying channel. Finally the decoding procedure of space-time block code (STBC), SFBCand STFBC is discussed. The decoding of all existing STBC/SFBC/STFBC is unified at first, in order to show a concise procedure and make fair comparisons. Then maximum likelihood decoding (MLD) and arbitrary sphere decoding (SD) can be adopted. To reduce the complexity of decoding further, a novel decoding method called compensation de-coding (CD) is presented for a given space-time-frequency coding scheme. By taking advantage of the simplicity of zero-forcing decoding (ZFD) we are able to calculate a compensation vector for the output of ZFD. After modification by utilizing the com-pensation vector, the BER performance can be improved significantly. The decoding procedure is relatively simple and is independent of the constellation size. The per-formance of the proposed decoding method is close to maximum-likelihood decoding for low to medium SNR. A low complexity detection scheme, classifier based decoding (CBD), is further proposed for MIMO systems incorporating spatial multiplexing. The CBD is a hybrid of an equalizer-based technique and an algorithmic search stage. Based on an error matrix and its probability density functions for different classes of error, a particular search region is selected for the algorithmic stage. As the probability of occurrence of error classes with larger search regions is small, overall complexity of the proposed technique remains low, whilst providing a significant improvement in the bit error rate performance