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Doctorate thesis defense of Mouna SGHAIER

Doctorate thesis defense on December 14th 2016 at 11H00 AM ,in Amphi I, Sup’Com.

Entitled :Efficient Embedded Signaling for Emerging Systems

Presented by : Mouna SGHAIER 



Ridha Bouallegue

Professor at Sup'Com, Tunisia






Professor at ENIS, Tunisia


Abdeldjalil AISSA EL BEY

Professor at Telecom Bretagne, France




Associate Professor at FSB, Tunisia



Mohamed Siala

Professor at Sup'Com, Tunisia



Associate Professor at Sup’Com



The extensive use of new information and communication technologies in all fields of life has created an explosive demand in terms of high data rate and energy. The objective throughout this thesis is to provide blind and optimal methods in terms of reliability using different forms of embedded signaling which presents a key tool to efficiently estimate several parameters of different wireless communication system in blind manner. Thus, the solutions proposed along this thesis work aim to avoid the transmission of explicit information between devices in different communication systems including Orthogonal Frequency Division Multiplexing (OFDM), Long Term Evolution (LTE), Filter bank multi-carrier (FBMC) and Multi-band cognitive radio (MB-RC) systems.

In the first part, we propose semi-blind and blind algorithms to reduce energy consumption in Orthogonal Frequency Division Multiplexing (OFDM) systems. In fact, the OFDM suffers from a major drawback, namely high Peak to Average Power Ratio (PAPR) of the modulated signals, which causes a high wastage in terms of energy efficiency, especially for mobile devices. Several methods, which require the transmission of Side Information (SI), have been proposed in the literature to overcome the PAPR issue. Unfortunately, the transmitted SI bits must be channel-encoded as they are particularly critical to the error performances of the OFDM system, which highly increases the system complexity and decreases the system performance. Therefore, the main objective of this first part is to overcome the PAPR issue by avoiding the use of SI bits under the use of semi-blind and blind detection algorithms of the pre-coding sequence used at the transmitter. Accordingly, we propose blind PAPR reduction algorithms for the Single Input Single Output (SISO) and Multiple Input Multiple Output (MIMO) systems. The suggested methods exploit several forms of embedded signaling such as the Alamouti coding, the pre-coding matrix, and the position of reference signals.

In the second part of this work, we propose new cooperative techniques for spectrum sensing in the case of Multi-Band Cognitive Radio (MB-CR) systems. Specifically, we focus on the enhancement of the performance of MB-CR systems by using embedded signaling. In this context, we investigate a new application of embedded signaling in MB-CR systems, where we exploit the Selected Mapping (SLM) principal and the one pixel camera (SPC) paradigm. Thus, in our sensing system, we put forward a non-uniform MB scheme where each secondary user (SU) exploits a special matrix and senses L sub-bands from the total sub-channels. These masks will be considered as an embedded signaling used to efficiently sensing the spectrum. We show that the proposed embedded signaling can turn out to be useful for boosting the system performance.


Embedded signaling, Side Information (SI), Blind algorithms, PAPR, Selected Mapping (SLM), Partial Transmit Sequence (PTS), OFDM, OFDMA, FBMC, Alamouti, Space Time Block Codes (STBC), Max-Log-Maximum A Posteriori (MAP), Alamouti coding, MIMO, Reference signals, Multi-Band Cognitive Radio (MB-CR), Spectrum Sensing.