This thesis investigates and analyses the performance of terrestrial free-space optical communication (FSO) system based on the phase shift keying pre-modulated subcarrier intensity modulation (SIM). The results are theoretically and experimentally compared with the classical On-Off keying (OOK) modulated FSO system in the presence of atmospheric turbulence. The performance analysis is based on the bit error rate (BER) and outage probability metrics. Optical signal traversing the atmospheric channel suffers attenuation due to scattering and absorption of the signal by aerosols, fog, atmospheric gases and precipitation. In the event of thick fog, the atmospheric attenuation coefficient exceeds 100 dB/km, this potentially limits the achievable FSO link length to less than 1 kilometre. But even in clear atmospheric conditions when signal absorption and scattering are less severe with a combined attenuation coefficient of less than 1 dB/km, the atmospheric turbulence significantly impairs ...

The widespread use of mobile internet and smart applications has led to an explosive growth in mobile data traffic. With the rise of smart homes, smart buildings, and smart cities, this demand is ever growing since future communication systems will require the integration of multiple networks serving diverse sectors, domains and applications, such as multimedia, virtual or augmented reality, machine-to-machine (M2M) communication / the Internet of things (IoT), automotive applications, and many more. Therefore, in the future, the communication systems will not only be required to provide Gbps wireless connectivity but also fulfill other requirements such as low latency and massive machine type connectivity while ensuring the quality of service. Without significant technological advances to increase the system capacity, the existing telecommunications infrastructure will be unable to support these multi-dimensional requirements. This poses an important demand for suitable waveforms with ...

The fabrication of miniature electronics and sensors has encouraged the creation of a wide range of wireless enabled devices designed to be worn on the human body. This has led to the prominence of so-called wearable communications, which have emerged to satisfy the demand for wireless connectivity between these devices and with external networks. The work in this thesis has focused on the characterization of the composite fading (i.e combined multipath and shadowing) observed in wearable communications channels. It has also investigated the mitigation of the deleterious effects of both of these propagation phenomena in wearable communications. In order to accurately characterize the behaviour of the composite fading signal observed in wearable communications channels, new fading models such as F, $\kappa$-$\mu$ / inverse gamma and $\eta$-$\mu$ / inverse gamma composite fading models, have been proposed. The generality and utility of ...

Massive multiple-input multiple-output (MIMO) evolved to a key enabling physical layer (PHY) technology for the fifth generation (5G) of mobile communication systems and beyond. While the envisioned use cases of such communications systems are diverse, so are the challenges to meet their respective requirements. As a large-scale evolution of already well-established MIMO communications technologies, massive MIMO promises benefits with respect to all possible use cases. Theoretical works on massive MIMO, however, typically assumes i.i.d. Rayleigh fading channels without spatial channel correlation. The application of this model is justified through the assumption of rich scattering environments, which is claimed to hold, for example, in indoor environments. Spatial correlation of wireless channels leads to inter-stream interference in single-user MIMO communications systems and to inter-user interference in multi-user MIMO systems with linear precoding. Channel correlation is therefore crucial for the performance of such ...

Base station cooperation is recognized as a key technology for future wireless cellular communication networks. Considering antennas of distributed base stations and those of multiple terminals within those cells as a distributed multiple-input multiple-output (MIMO) system, this technique has the potential to eliminate inter-cell interference by joint signal processing and to enhance spectral efficiency in this way. Although the theoretical gains are meanwhile well-understood, it still remains challenging to realize the full potential of such cooperative schemes in real-world systems. Among other factors, such as the limited overhead for pilot symbols and for the feedback and backhaul, these performance limitations are related to channel and synchronization impairments, such as channel estimation, feedback quantization and channel aging, as well as imperfect carrier and sampling synchronization among the base stations. Because of these impairments, joint data precoding results to be mismatched with ...

Speech communication frequently suffers from transmitted background noises. Numerous speech enhancement algorithms have thus been proposed to obtain a speech signal with a reduced amount of background noise and better speech quality. In most cases they are analytically derived as spectral weighting rules for given error criteria along with statistical models of the speech and noise spectra. However, as these spectral distributions are indeed not easy to be measured and modeled, such algorithms achieve in practice only a suboptimal performance. In the development of state-of-the-art algorithms, speech and noise training data is commonly exploited for the statistical modeling of the respective spectral distributions. In this thesis, the training data is directly applied to train data-driven speech enhancement algorithms, avoiding any modeling of the spectral distributions. Two applications are proposed: (1) A set of spectral weighting rules is trained from noise ...

Recent academic developments have initiated a paradigm shift in the way spatial sensor data can be acquired. Traditional localized and regularly arranged sensor arrays are replaced by sensor nodes that are randomly distributed over the entire spatial field, and which communicate with each other or with a master node through wireless communication links. Together, these nodes form a so-called ‘wireless sensor network’ (WSN). Each node of a WSN has a local sensor array and a signal processing unit to perform computations on the acquired data. The advantage of WSNs compared to traditional (wired) sensor arrays, is that many more sensors can be used that physically cover the full spatial field, which typically yields more variety (and thus more information) in the signals. It is likely that future data acquisition, control and physical monitoring, will heavily rely on this type of ...

An analysis of the ergonomic quality of the current standards for the visual display quality leads to a number of recommendations for the development of new international standards: - Separation for different types of users, esp. display designers, purchasers, and end users, -Independence of display technology to allow comparison, -Modular construction with several quality grades to allow benchmarking for different types of applications, -A test method for the end user standard that can be performed at the place of work, to take into account the effects of wear and drift of components and to be able to correct suboptimal configurations. The separate parameters that exert influence on the image quality of a broad category of images in the context of use, and their mutual coherence within the cycle of evaluation and adaptation of image quality are presented in the "Image ...

Wireless sensor networks has been one of the major research topics in recent years because of its great potential for a wide range of applications. In some application scenarios, sensor nodes intend to report the sensing data to a far-field destination, which cannot be realized by traditional transmission techniques. Due to the energy limitations and the hardware constraints of sensor nodes, distributed transmit beamforming is considered as an attractive candidate for long-range communications in such scenarios as it can reduce energy requirement of each sen-sor node and extend the communication range. However, unlike conventional beamforming, which is performed by a centralized antenna array, distributed beamforming is performed by a virtual antenna array composed of randomly located sensor nodes, each of which has an independent oscillator. Sensor nodes have to coordinate with each other and adjust their transmitting signals to collaboratively ...

Radio Frequency Identification (RFID) is a very fast emerging technology that wirelessly transmits the identity of a tag attached to an object or a person. It usually operates in a dense tag environment. My work is focused on passive Ultra High Frequency (UHF) tags whose transmission on the Medium Access Control (MAC) layer is scheduled by Framed Slotted Aloha (FSA). In this thesis, I propose the use of multiple antennas at the reader side in order to recover from collision. By exploiting the fact that a tag signal is real-valued while all other components of a received signal are complexed-valued, I have separated real and imaginary part and in that way I have achieved a recovery from a collision that contains a two times higher number of tags than the number of the receive antennas at the reader, under perfect ...

Device-to-Device (D2D) is one of the important proposed solutions to increase the capacity, offload the traffic, and improve the energy effciency in next generation cellular networks. D2D communication is known as a direct communication between two users without using cellular infrastructure networks. Despite of large expected bene fits in terms of capacity in D2D, the coexistence of D2D and cellular networks in the same spectrum creates new challenges in interference management and network design. To limit the interference power control schemes on cellular networks and D2D networks are typically adopted. Even though power control is introduced to limit the interference level, it does not prevent cellular and D2D users from experiencing coverage limitation when sharing the same radio resources. Therefore, the design of such networks requires the availability of suitable methods able to properly model the eff ect of interference ...

This thesis introduces new learning algorithms for Radial Basis Function (RBF) networks. RBF networks is a feed-forward two-layer neural network used for functional approximation or pattern classification applications. The proposed training algorithms are based on robust statistics. Their theoretical performance has been assessed and compared with that of classical algorithms for training RBF networks. The applications of RBF networks described in this thesis consist of simultaneously modeling moving object segmentation and optical flow estimation in image sequences and 3-D image modeling and segmentation. A Bayesian classifier model is used for the representation of the image sequence and 3-D images. This employs an energy based description of the probability functions involved. The energy functions are represented by RBF networks whose inputs are various features drawn from the images and whose outputs are objects. The hidden units embed kernel functions. Each kernel ...

The thriving development of wireless communications calls for innovative and advanced signal processing techniques targeting at an enhanced performance in terms of reliability, throughput, robustness, efficiency, flexibility, etc.. This thesis addresses such a compelling demand and presents new and intriguing progress towards fulfilling it. We mainly concentrate on two advanced multi-dimensional signal processing challenges for wireless systems that have attracted tremendous research attention in recent years, multi-carrier Multiple-Input Multiple-Output (MIMO) systems and multi-dimensional harmonic retrieval. As the key technologies of wireless communications, the numerous benefits of MIMO and multi-carrier modulation, e.g., boosting the data rate and improving the link reliability, have long been identified and have ignited great research interest. In particular, the Orthogonal Frequency Division Multiplexing (OFDM)-based multi-user MIMO downlink with Space-Division Multiple Access (SDMA) combines the twofold advantages of MIMO and multi-carrier modulation. It is the essential element ...

The cumulative impact of co-channel interferers, commonly referred to as aggregate network interference, is one of the main performance limiting factors in today’s mobile cellular networks. Thus, its careful statistical description is decisive for system analysis and design. A system model for interference analysis is required to capture essential network variation effects, such as base station deployment- and signal propagation characteristics. Furthermore it should be simple and tractable so as to enable first-order insights on design fundamentals and rapid exchange of new ideas. Interference modeling has posed a challenge ever since the establishment of traditional macro cellular deployments. The recent emergence of heterogeneous network topologies complicates matters by contesting many established aspects of time-honored approaches. This thesis presents user-centric system models that enable to investigate scenarios with an asymmetric interference impact. The first approach simplifies the interference analysis in a ...

This PhD thesis considers the problem of locating some target nodes in different wireless infrastructures such as wireless cellular radio networks and wireless sensor networks. To be as realistic as possible, mixed line-of-sight and non-line-of-sight (LOS/NLOS) localization environment is introduced. Both the conventional non-cooperative localization and the new emerging cooperative localization have been studied thoroughly. Owing to the random nature of the measurements, probabilistic methods are more advanced as compared to the old-fashioned geometric methods. The gist behind the probabilistic methods is to infer the unknown positions of the target nodes in an estimation process, given a set of noisy position related measurements, a probabilistic measurement model, and a few known reference positions. In contrast to the majority of the existing methods, harsh but practical constraints are taken into account: neither offline calibration nor non-line-of-sight state identification is equipped in ...