Cloud Transmission: System Performance and Application Scenarios

[EN] Cloud Transmission (Cloud Txn) System is a flexible multi-layer system that uses spectrum overlay technology to simultaneously deliver multiple program streams with different characteristics and robustness for different services (mobile TV, HDTV and UHDTV) in one RF channel. The transmitted signal is formed by superimposing a number of independent signals at desired power levels, to form a multilayered signal. The signals of different layers can have different coding, bit rate, and robustness. For the top layer, system parameters are chosen to provide very robust transmission that can be used for high speed mobile broadcasting service to portable devices. The bit rate is traded for more powerful error correction coding and robustness so that the Signal to Noise Ratio (SNR) threshold at the receiver is a negative value in the range of -2 to -3 dB. The top layer is designed to withstand combined noise, co-channel interference and multipath distortion power levels higher than the desired signal power. The lowerlayer signal can be DVB-T2 signal or other newly designed system to deliver HDTV/UHDTV to fixed receivers. The system concept is open to technological advances that might come in the future: all new technologies, BICM/Non Uuniform-QAM, rotated constellations, Time Frequency Slicing or MIMO techniques can be implemented in the Cloud Txn lower (high data) rate layer. The main focus of this paper is to thoroughly describe the performance of this newly presented Cloud Transmission broadcasting system.This work has been financially supported in part by the University of the Basque Country UPV/EHU (UFI 11/30), by the Basque Government (IT-683- 13 and SAIOTEK), by the Spanish Ministry of Science and Innovation under the project NG-RADIATE (TEC2009-14201), and by the Spanish Ministry of Economy and Competitiveness under the project HEDYT-GBB (TEC2012- 33302

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

Models and optimisation methods for interference coordination in self-organising cellular networks

A thesis submitted for the degree of Doctor of PhilosophyWe are at that moment of network evolution when we have realised that our telecommunication systems should mimic features of human kind, e.g., the ability to understand the medium and take advantage of its changes. Looking towards the future, the mobile industry envisions the use of fully automatised cells able to self-organise all their parameters and procedures. A fully self-organised network is the one that is able to avoid human involvement and react to the fluctuations of network, traffic and channel through the automatic/autonomous nature of its functioning. Nowadays, the mobile community is far from this fully self-organised kind of network, but they are taken the first steps to achieve this target in the near future. This thesis hopes to contribute to the automatisation of cellular networks, providing models and tools to understand the behaviour of these networks, and algorithms and optimisation approaches to enhance their performance. This work focuses on the next generation of cellular networks, in more detail, in the DownLink (DL) of Orthogonal Frequency Division Multiple Access (OFDMA) based networks. Within this type of cellular system, attention is paid to interference mitigation in self-organising macrocell scenarios and femtocell deployments. Moreover, this thesis investigates the interference issues that arise when these two cell types are jointly deployed, complementing each other in what is currently known as a two-tier network. This thesis also provides new practical approaches to the inter-cell interference problem in both macro cell and femtocell OFDMA systems as well as in two-tier networks by means of the design of a novel framework and the use of mathematical optimisation. Special attention is paid to the formulation of optimisation problems and the development of well-performing solving methods (accurate and fast)

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems