The majority of communication systems need the previous knowledge of the channel, which is usually estimated by means of a training sequence. However, the transmission of pilot symbols provokes a reduction in bandwidth efficiency, which precludes the system from reaching the limits predicted by the Information Theory. This problem has motivated the development of a large number of blind channel estimation and equalization techniques, which are able to obtain the channel or the source without the need of transmitting a training signal. Usually, these techniques are based on the previous knowledge of certain properties of the signal, such as its belonging to a finite alphabet, or its higher-order statistics. However, in the case of multiple-input multipleoutput (MIMO) systems, it has been proven that the second-order statistics of the observations provide the sufficient information for solving the blind problem. The aim ...

Recently, many works have been accomplished on transmit diversity for a high-speed data transmission through the wireless channel. A Multiple Input Multiple Output (MIMO) system which employs multiple antennas at transmitter and receiver has been shown to be able to improve transmission data rate and capacity of the system. When the channel state information (CSI) is unknown at the transmitter, an multiple input single output (MISO) system combined with the transmit diversity of space time coding modulation known as space-time block coding (STBC) has taken a great attention. However, the performance of STBC is deteriorated under frequency selective fading due to inter symbol interference (ISI). An STBC employing tapped delay line adaptive array (STBC-TDLAA) is known as a solution for this problem since it utilizes the delayed signals to enhance the desired signal instead of excluding them as interferences. However, ...

Wireless communication systems rely on a multiple-access technique, i.e., a mechanism to divide the common transmission medium among di erent users. Code-division multiple-access (CDMA) is a multiple-access technique that has received considerable attention in recent years. In a CDMA system, each user spreads his information-bearing signal into a wideband signal, using speci c code information. All users then transmit their wideband signal within the same frequency and time channel. This thesis deals with the development of receivers for various CDMA systems. Digital signal processing plays a central role in this development. In recent literature, so-called multi-user receivers have become very popular. These receivers take into account the full structure of the multi-user interfer- ence (MUI), i.e., the interference originating from the other users. However, they have a rather high computational complexity. In the rst part of this the- sis, we ...

Code division multiple access (CDMA) techniques have been widely employed by different wireless systems with many advantages. However, the performance of these systems is limited by interference. A number of different interference suppression techniques have been proposed, including multiuser detection, beamforming, adaptive supervised and blind algorithms, and transmit processing techniques requiring a limited feedback channel. Recently, CDMA techniques have also been combined with multicarrier and multiantenna schemes to further increase the system capacity and performance. This thesis investigates the existing algorithms and structures and proposes novel interference suppression algorithms for spread spectrum systems. Firstly we investigate blind constrained constant modulus (CCM) stochastic gradient (SG) receivers with a low-complexity variable step-size mechanism for downlink direct sequence CDMA (DS-CDMA) systems. This algorithm provides better performance than existing blind schemes in non-stationary scenarios. Convergence and tracking analyses of the proposed adaptation techniques are ...

In order to improve communication over a dispersive channel in a CDMA system, we have to re-establish the orthogonally of codes which are used when combining input signals from many users onto a single communication path, as otherwise the performance of such system is limited significantly by inter-symbol interference (ISI) and multiuser access interference (MAI). In order to achieve this, adaptive filters are employed. A variety of adaptive schemes to remove ISI and MAI have been reported in the literature, some of which rely on training sequences, such as the Least Mean Squares (LMS) and Recursive Least Squares (RLS) algorithms, or on blind adaptation, such as the Constant Modulus Algorithm (CMA) or the Decision Directed algorithm (DD), which has similar convergence properties as the LMS in the absence of decision errors, the CMA is relatively slow compared to the DD ...

This thesis deals with the synchronization of one or several replicas of a known signal received in a scenario with multipath propagation and directional interference. A connecting theme along this work is the systematic application of the maximum likelihood (ML) principle together with a signal model in which the spatial signatures are unstructured and the noise term is Gaussian- distributed with an unknown correlation matrix. This last assumption is key in obtaining estimators that are capable of mitigating the disturbing signals that exhibit a certain structure, and this is achieved without resorting to the estimation of the parameters of those signals. On the other hand, the assumption of unstructured spatial signatures is interesting from a practical standpoint and facilitates the estimation problem since the estimates of these signatures can be obtained in closed form. This constitutes a first step towards ...

The thriving development of wireless communications calls for innovative and advanced signal processing techniques targeting at an enhanced performance in terms of reliability, throughput, robustness, efficiency, flexibility, etc.. This thesis addresses such a compelling demand and presents new and intriguing progress towards fulfilling it. We mainly concentrate on two advanced multi-dimensional signal processing challenges for wireless systems that have attracted tremendous research attention in recent years, multi-carrier Multiple-Input Multiple-Output (MIMO) systems and multi-dimensional harmonic retrieval. As the key technologies of wireless communications, the numerous benefits of MIMO and multi-carrier modulation, e.g., boosting the data rate and improving the link reliability, have long been identified and have ignited great research interest. In particular, the Orthogonal Frequency Division Multiplexing (OFDM)-based multi-user MIMO downlink with Space-Division Multiple Access (SDMA) combines the twofold advantages of MIMO and multi-carrier modulation. It is the essential element ...

We investigate two aspects of multiple-antenna wireless communication systems in this thesis: 1) deployment of an adaptive beamformer array at the receiver; and 2) space-time coding for arrays at the transmitter and the receiver. In the first part of the thesis, we establish sufficient conditions for the convergence of a popular least mean squares (LMS) algorithm known as the sequential Partial Update LMS Algorithm for adaptive beamforming. Partial update LMS (PU-LMS) algorithms are reduced complexity versions of the full update LMS that update a subset of filter coefficients at each iteration. We introduce a new improved algorithm, called Stochastic PU-LMS, which selects the subsets at random at each iteration. We show that the new algorithm converges for a wider class of signals than the existing PU-LMS algorithms. The second part of this thesis deals with the multiple-input multiple-output (MIMO) Shannon ...

Transmit diversity is a powerful technique for enhancing the channel capacity and reliability of multiple-input and multiple-output (MIMO) wireless systems. This thesis considers extended orthogonal space-time block coding (EO-STBC) with beamsteering angles, which have previously been shown to potentially achieve full diversity and array gain with four transmit and one receive antenna. The optimum setting of beamsteering angles applied in the transmitter, which has to be calculated based on channel state information (CSI) at the receiver side, must be quantised and feed back to the transmitter via a reverse feedback link. When operating in a fading scenario, channel coefficients vary smoothly with time. This smooth evolution of channel coefficients motivates the investigation of differential feedback, which can reduce the number of feedback bits, while potentially maintaining near optimum performance. The hypothesis that the smooth evolution of channel coefficients translates into ...

Multi-input multi-output (MIMO) channels are known to increase the capacity of a transmission link. This can be exploited to increase either the multiplexing gain or the diversity gain, which leads to a higher data throughput or a better resilience of the link to fading, respectively. This thesis is concerned with the diversity gain, which, in a flat fading channel, can be maximised by Alamouti’s space-time block coding (STBC) scheme and a number of derivative techniques. For frequency selective fading, i.e. dispersive, MIMO channels, a few solutions have been reported in the literature including MIMO-OFDM, where the channel is decomposed into a number of narrowband problems, and a technique known as time-reversal STBC. For the latter, a number of blind adaptive algorithms have been derived, implemented and tested in order to avoid the requirement of explicit knowledge of the channel. The ...

The widespread use of mobile internet and smart applications has led to an explosive growth in mobile data traffic. With the rise of smart homes, smart buildings, and smart cities, this demand is ever growing since future communication systems will require the integration of multiple networks serving diverse sectors, domains and applications, such as multimedia, virtual or augmented reality, machine-to-machine (M2M) communication / the Internet of things (IoT), automotive applications, and many more. Therefore, in the future, the communication systems will not only be required to provide Gbps wireless connectivity but also fulfill other requirements such as low latency and massive machine type connectivity while ensuring the quality of service. Without significant technological advances to increase the system capacity, the existing telecommunications infrastructure will be unable to support these multi-dimensional requirements. This poses an important demand for suitable waveforms with ...

During the past years wireless communications have been exhibiting an increased growth rendering them the most common way for communication. The continuously increasing demand for wireless services resulted in limited availability of the wireless spectrum. To this end, Cognitive Radio (CR) techniques have been proposed in literature during the past years. The concept of CR approach is to utilize advanced radio and signal-processing technology along with novel spectrum allocation policies to enable new unlicensed wireless users to operate in the existing occupied spectrum areas without degrading the performance of the existing licensed ones. Moreover, the broadcast and fading nature of the wireless channel results in severe degradation on the performance of wireless transmissions. A solution to the problem is the use of multiple-antenna systems so as to achieve spatial diversity. However, in many cases, the communication devices' nature permit the ...

In this thesis several aspects of space-time processing and equalization for wireless communications are treated. We discuss several different methods of improving estimates of space-time channels, such as temporal parametrization, spatial parametrization, reduced rank channel estimation, bootstrap channel estimation, and joint estimation of an FIR channel and an AR noise model. In wireless communication the signal is often subject to intersymbol interference as well as interference from other users. We here discuss space-time decision feedback equalizers and space-time maximum likelihood sequence estimators, which can alleviate the impact of these factors. In case the wireless channel does not experience a large amount of coupled delay and angle spread, sufficient performance may be obtained by an equalizer with a less complex structure. We therefore discuss various reduced complexity equalizers and symbol sequence estimators. We also discuss re-estimating the channel and/or re-tuning the ...

Multi-input multi-output (MIMO) wireless networks and distributed MIMO relaying wireless networks have attracted significant attention in current generation of wireless communication networks, and will play a key role in the next generation of wireless net- works. The improvement of network capacity, data rate and reliability can be achieved at the cost of increasing computational complexity of employing space-time coding (STC) and distributed STC (DSTC) in MIMO and distributed MIMO relaying networks, respectively. Efficient designs and algorithms to achieve high diversity and coding gains with low computational complexity in encoding and decoding of STC and DSTC schemes are essential. In this thesis, DSTC designs with high diversity and coding gains and efficient detection and code matrices optimization algorithms in cooperative MIMO networks are proposed. Firstly, adaptive power allocation (PA) algorithms with different criteria for a coop- erative MIMO network equipped with ...

Blind channel identication and equalisation are the processes by which a channel impulse response can be identified and proper equaliser filter coeffcients can be obtained, without knowledge of the transmitted signal. Techniques that exploit cyclostationarity can reveal information about systems which are nonminimum phase, nonminimum phase channels cannot be identied using only second-order statistics (SOS), because these do not contain the necessary phase information. Cyclostationary blind equalisation methods exploit the fact that, sampling the received signal at a rate higher than the transmitted signal symbol rate, the received signal becomes cyclostationary. In general, cyclostationary blind equalisers can identify a channel with less data than higher-order statistics (HOS) methods, and unlike these, noconstraint is imposed on the probability distribution function of the input signal. Nevertheless, cyclostationary methods suffer from some drawbacks, such as the fact that some channels are unidentiable when ...