Αποδοτικές τεχνικές εκτίμησης – ισοστάθμισης γενικευμένων ασύρματων καναλιών πολλαπλών εισόδων – πολλαπλών εξόδων

Abstract

Systems employing multiple antennas at the transmitter and the receiver, known as MIMO (multiinput multioutput) systems, as well as space time coding techniques developed for such systems, are two of the main technologies employed for the evolution of wireless communications. However, the application of MIMO technology to mobile networks, often faces the practical implementation problem of having too many antennas on a small mobile terminal. In an attempt to overcome such a severe limitation, cooperative communication schemes have been proposed. This PhD dissertation, described our work on the design and analysis of signal processing algorithms for the two aforementioned systems, as is described in detail next. Concerning MIMO systems, the pioneering work performed at Bell Labs in the middle of the nineties, proved that the use of multiple antennas can lead to a significant increase in wireless systems capacity. To exploit this potential, sophisticated MIMO receivers should be designed. To this end, a large amount of channel equalizers and, more specifically, decision feedback equalizers has been proposed. Because these assumptions are difficult to meet in high rate single carrier systems, we have focused our attention on decision feedback equalizers. . Our main goal is to derive algorithms for updating the MIMO DFE filters with the following characteristics: 1) convergence properties similar to these of the RLS 2) more computationally efficient than RLS and 3) numerically stable. It is known that adaptive algorithms based on the CG (conjugate gradient) have the above characteristics We initially studied this method as an iterative method for solving linear equations and we pointed out the main differences with the steepest descent method, on which the LMS algorithm is based. An extended search of adaptive DFE algorithms, based on the CG method was carried out. More specifically, a new block adaptive CG algorithm was developed. In the resulting algorithm, one CG iteration per block update is executed. In order to reduce even more the complexity, the algorithm was implemented in the Frequency Domain. The proposed equalizer offers a good performance - complexity trade off. Three new adaptive equalization algorithms for wireless systems operating over frequency selective MIMO channels, based on the CG method and the Galerkin projection method, are proposed. The problem of MIMO decision feedback equalizer (DFE) design is formulated as a set of linear equations with multiple righthand sides (RHSs) evolving in time. These schemes provide a flexible framework in MIMO adaptive equalization design to implement schemes with convergence properties comparable to the RLS, but of lower computational cost. Furthermore, we worked on channel estimation for cooperative communication networks, where the nodes either simply amplify and forward the received signal, or they decode and transmit the signal (DF). We first propose efficient channel estimation techniques for relay networks with N relays. The new methods are implemented in the frequency domain (FD). Initially, training based techniques are presented, where the training pilots are multiplexed with the data in the frequency domain. It is then shown that all the channels in the network can be estimated blindly provided that we know the phases of the frequency response of the (Source → Destination) channel. Thus, by making use of a small number of pilots in only one link (the sourcetodestination link) we can estimate all the other channels (Source→Relay i→Destination) in the network. A theoretical performance study of the proposed algorithms is presented and closed form expressions for the mean squared channel estimation error are provided. The presented theoretical analysis is verified by extensive Monte Carlo simulations. The application of the derived schemes to the DF case, and the impact of erroneous detection to their performance are also studied. Finally, we investigated experimentally four cooperative relaying schemes: amplify and forward (AF), detect and forward (DF), cooperative maximum ratio combining (CMRC) and distributed spacetime coding (DSTC), and one novel selection relaying (SR) scheme on a realtime DSP based testbed. The experimental results are fairly close to the ones predicted by theory