NOVEL OFDM SYSTEM BASED ON DUAL-TREE COMPLEX WAVELET TRANSFORM

The demand for higher and higher capacity in wireless networks, such as cellular, mobile and local area network etc, is driving the development of new signaling techniques with improved spectral and power efficiencies. At all stages of a transceiver, from the bandwidth efficiency of the modulation schemes through highly nonlinear power amplifier of the transmitters to the channel sharing between different users, the problems relating to power usage and spectrum are aplenty. In the coming future, orthogonal frequency division multiplexing (OFDM) technology promises to be a ready solution to achieving the high data capacity and better spectral efficiency in wireless communication systems by virtue of its well-known and desirable characteristics. Towards these ends, this dissertation investigates a novel OFDM system based on dual-tree complex wavelet transform (D

Etude et caractérisation d'un capteur en silicium amorphe hydrogéné déposé sur circuit intégré pour la détection de particules et de rayonnements

Next generation experiments at the European laboratory of particle physics (CERN) require particle detector alternatives to actual silicon detectors. This thesis presents a novel detector technology, which is based on the deposition of a hydrogenated amorphous silicon sensor on top of an integrated circuit. Performance and limitations of this technology have been assessed for the first time in this thesis in the context of particle detectors. Specific integrated circuits have been designed and the detector segmentation, the interface sensor â chip and the sensor leakage current have been studied in details. The signal induced by the track of an ionizing particle in the sensor has been characterized and results on the signal speed, amplitude and on the sensor resistance to radiation are presented. The results are promising regarding the use of this novel technology for radiation detection, though limitations have been shown for particle physics application

Nutritional Value extraction of food exploiting computer vision and near infrared Spectrometry

The population growth in the last few decades has led to the development of urban areas, which induced an increased difficulty in finding quality food. The difficulty in finding quality nourishment and a growing offer in the fast-food industry due to the fast pace at which life is lived in big cities has caused increasing obesity and sedentary lifestyle. In 2016 more than 1.9 billion adults aged 18 years and older were overweight[1]. However, this tendency has started to reverse, and with the increasing concern for diseases such as obesity and diabetes, people started return to shopping in farmers mar kets and choosing wisely the locals where they eat, which led to the development of more healthy fast food chains. This new tendency has made new technologies appear that were created to help improve customer choices and facilitate choosing the best food items that have the best quality. This dissertation will analyse the different devices and solutions in the market, such as near-infrared sensors and computer vision. The objective of this dissertation is to build a system that can detect which type of food item we choose and obtain nutritional information. The development begins with researching the different options of small devices that already exist in the market and with which a person can take shopping and assist them by obtaining the nutritional information, such as SCIO or Tellspec. This device cannot detect which type of food is being analysed, so human interaction it is still needed to obtain the best results possible. However, it can return the nutritional information necessary for the first part of this dissertation’s development. Besides being small (palm-handed), these sensors are also cheap and faster compared to equivalent laboratory equipment. The second objective of this dissertation was developed to solve the lack of detection of which type of food is present in the module. To solve this problem and taking into account the objective, it was decided to use computer vision and, more specifically, image recognition and deep machine learning applied in food databases. This dissertation’s main objective is to create a module that can classify and obtain the nutritional information of different types of food. It also serves as a helping hand in the kitchen to control the quality and quantity of the food that the user ingests daily. There will be an exhaustive testing session for the near-infrared sensors using different types of fruits to prove the concept. For the computer vision, it will be applied a deep learning algorithm with supervised training to obtain a high accuracy result

4G Technology Features and Evolution towards IMT-Advanced

Kiinteiden- ja mobiilipalveluiden kysyntä kasvaa nopeasti ympäri maailmaa. Älykkäiden päätelaitteiden, kuten iPhone:n ja Nokia N900:n markkinoilletulo yhdistettynä näiden korkeaan markkinapenetraatioon ja korkealuokkaiseen käyttäjäkokemukseen lisäävät entisestään palveluiden kysyntää ja luovat tarpeen jatkuvalle innovoinnille langattomien teknologioiden alalla tavoitteena lisäkapasiteetin ja paremman palvelunlaadun tarjoaminen. Termi 4G (4th Generation) viittaa tuleviin neljännen sukupolven mobiileihin langattomiin palveluihin, jotka International Telecommunications Union:in Radiocommunication Sector (ITU-R) on määritellyt ja nimennyt International Mobile Telecommunications-Advanced (IMT-Advanced). Nämä ovat järjestelmiä, jotka pitävät sisällään IMT:n ne uudet ominaisuudet, jotka ylittävät IMT-2000:n vaatimukset. Long Term Evolution-Advanced (LTE-Advanced) ja IEEE 802.16m ovat IMT-A sertifiointiin lähetetyt kaksi pääasiallista kandidaattiteknologiaa. Tässä diplomityössä esitellään kolmannen sukupolven järjestelmien kehityspolku LTE:hen ja IEEE 802.16e-2005 asti. Lisäksi työssä esitetään LTE-Advanced:n ja IEEE 802.16m:n uudet vaatimukset ja ominaisuudet sekä vertaillaan näiden lähestymistapoja IMT-A vaatimusten täyttämiseksi. Lopuksi työssä luodaan katsaus LTE ja IEEE 802.16e-2005 (markkinointinimeltään Mobile WiMAX) -järjestelmien markkinatilanteeseen.The demand for affordable bandwidth in fixed and mobile services is growing rapidly around the world. The emergence of smart devices like the iPhone and Nokia N900, coupled with their high market penetration and superior user experience is behind this increased demand, inevitably driving the need for continued innovations in the wireless data technologies industry to provide more capacity and higher quality of service. The term "4G" meaning the 4th Generation of wireless technology describes mobile wireless services which have been defined by the ITU's Radiocommunication Sector (ITU-R) and titled International Mobile Telecommunications-Advanced (IMT-Advanced). These are mobile systems that include the new capabilities of IMT that go beyond those of IMT-2000. Long Term Evolution-Advanced (LTE-Advanced) and IEEE 802.16m are the two main candidate technologies submitted for IMT-Advanced certification. This thesis reviews the technology roadmap up to and including current 3G systems LTE from the 3rd Generation Partnership Project (3GPP) and IEEE 802.16e-2005 from the Institute of Electrical and Electronics Engineers (IEEE). Furthermore, new requirements and features for LTE-Advanced and IEEE 802.16m as well as a comparative approach towards IMT-Advanced certification are presented. Finally, the thesis concludes with a discussion on the market status and deployment strategies of LTE and IEEE 802.16e-2005, or Mobile WiMAX as it is being marketed

Multiple-Input Multiple-Output Detection Algorithms for Generalized Frequency Division Multiplexing

Since its invention, cellular communication has dramatically transformed personal lifes and the evolution of mobile networks is still ongoing. Evergrowing demand for higher data rates has driven development of 3G and 4G systems, but foreseen 5G requirements also address diverse characteristics such as low latency or massive connectivity. It is speculated that the 4G plain cyclic prefix (CP)-orthogonal frequency division multiplexing (OFDM) cannot sufficiently fulfill all requirements and hence alternative waveforms have been in-vestigated, where generalized frequency division multiplexing (GFDM) is one popular option. An important aspect for any modern wireless communication system is the application of multi-antenna, i.e. MIMO techiques, as MIMO can deliver gains in terms of capacity, reliability and connectivity. Due to its channel-independent orthogonality, CP-OFDM straightforwardly supports broadband MIMO techniques, as the resulting inter-antenna interference (IAI) can readily be resolved. In this regard, CP-OFDM is unique among multicarrier waveforms. Other waveforms suffer from additional inter-carrier interference (ICI), inter-symbol interference (ISI) or both. This possibly 3-dimensional interference renders an optimal MIMO detection much more complex. In this thesis, weinvestigate how GFDM can support an efficient multiple-input multiple-output (MIMO) operation given its 3-dimensional interference structure. To this end, we first connect the mathematical theory of time-frequency analysis (TFA) with multicarrier waveforms in general, leading to theoretical insights into GFDM. Second, we show that the detection problem can be seen as a detection problem on a large, banded linear model under Gaussian noise. Basing on this observation, we propose methods for applying both space-time code (STC) and spatial multiplexing techniques to GFDM. Subsequently, we propose methods to decode the transmitted signals and numerically and theoretically analyze their performance in terms of complexiy and achieved frame error rate (FER). After showing that GFDM modulation and linear demodulation is a direct application of Gabor expansion and transform, we apply results from TFA to explain singularities of the modulation matrix and derive low-complexity expressions for receiver filters. We derive two linear detection algorithms for STC encoded GFDM signals and we show that their performance is equal to OFDM. In the case of spatial multiplexing, we derive both non-iterative and iterative detection algorithms which base on successive interference cancellation (SIC) and minimum mean squared error (MMSE)-parallel interference cancellation (PIC) detection, respectively. By analyzing the error propagation of the SIC algorithm, we explain its significantly inferior performance compared to OFDM. Using feedback information from the channel decoder, we can eventually show that near-optimal GFDM detection can outperform an optimal OFDM detector by up to 3dB for high SNR regions. We conclude that GFDM, given the obtained results, is not a general-purpose replacement for CP-OFDM, due to higher complexity and varying performance. Instead, we can propose GFDM for scenarios with strong frequency-selectivity and stringent spectral and FER requirements

A review of gallium nitride LEDs for multi-gigabit-per-second visible light data communications

The field of visible light communications (VLC) has gained significant interest over the last decade, in both fibre and free-space embodiments. In fibre systems, the availability of low cost plastic optical fibre (POF) that is compatible with visible data communications has been a key enabler. In free-space applications, the availability of hundreds of THz of the unregulated spectrum makes VLC attractive for wireless communications. This paper provides an overview of the recent developments in VLC systems based on gallium nitride (GaN) light-emitting diodes (LEDs), covering aspects from sources to systems. The state-of-the-art technology enabling bandwidth of GaN LEDs in the range of >400 MHz is explored. Furthermore, advances in key technologies, including advanced modulation, equalisation, and multiplexing that have enabled free-space VLC data rates beyond 10 Gb/s are also outlined