Detection of Signals in MC–CDMA Using a Novel Iterative Block Decision Feedback Equalizer

This paper presents a technique to mitigate multiple access interference (MAI) in multicarrier code division multiple access (MC-CDMA) wireless communications systems. Although under normal circumstances the MC-CDMA system can achieve high spectral efficiency and resistance towards inter symbol interference (ISI) however when exposed to substantial nonlinear distortion the issue of MAI manifests. Such distortion results when the power amplifiers are driven into saturation or when the transmit signal experiences extreme adverse channel conditions. The proposed technique uses a modified iterative block decision feedback equalizer (IB-DFE) that uses a minimal mean square error (MMSE) receiver in the feed-forward path to nullify the residual interference from the IB-DFE receiver. The received signal is re-filtered in an iterative process to significantly improve the MC-CDMA system’s performance. The effectiveness of the proposed modified IB-DFE technique in MC-CDMA systems has been analysed under various harsh nonlinear conditions, and the results of this analysis presented here confirm the effectiveness of the proposed technique to outperform conventional methodologies in terms of the bit error rate (BER) and lesser computational complexity

Projektovanje višenivoskih konstelacija signala za komunikacione sisteme sa ograničenom snagom

In modern digital communication systems, a huge amount of data is transmitted, so that research aimed at achieving more efficient transmission is necessary, which makes the topic of this doctoral dissertation relevant and important. The subject of research in this doctoral dissertation is how to improve the power efficiency of multilevel PAM (Pulse Amplitude Modulation) and APSK (Amplitude Phase Shift Keying) constellations in power-limited communication systems, such as optical communications, satellite communications, wireless communications, multiple-input multiple-output systems. A constellation is defined by the geometric-space partition and probabilities of constellation points. Therefore, under constellation designing or constellation shaping the methods that optimize modulation format by adjusting the geometric-space location and/or probabilities of constellation points are assumed. All these methods are categorized within three constellation shaping schemes: geometric constellation shaping, probabilistic constellation shaping and hybrid probabilistic-geometric constellation shaping. Constellation shaping has been usually performed by optimizing some metric that characterize a channel or by optimizing the minimum Euclidean distance. Instead of this, in this dissertation constellation shaping is performed by applying designing techniques from quantization theory. Namely, the existence of similarity in the geometric-space representation ofconstellation and quantization motivates us to apply the quantization designing methods in constellation shaping. Special attention is paid to reducing the constellation complexity, that is to designing the piecewise-uniform constellations in terms of the geometric-space partition and probability distribution of constellation points. Methods for designing constellation inspired by piecewise-linear companding quantization have been proposed. Also, a novel designing concept that employs the companding technique in constellation shaping on a totally different manner has been proposed. Power efficiency is the ability of a modulation technique to preserve the fidelity/quality of digital data at low values of the signal-to-noise ratio, and is expressed as the signal-to-noise ratio per bit required to achieve a given error probability. In the dissertation we deal with designing power-efficient multilevel constellations for channels dominated by the additive white Gaussian noise, and the metric for constellation performance evaluation is a functional dependence of symbol error probability on signal-to-noise ratio per bit for uncoded constellation in channel with additive white Gausssian noise. The accuracy of analyzes and achieved results has been verified by performing simulations