Distributed Adaptation Techniques for Connected Vehicles

In this PhD dissertation, we propose distributed adaptation mechanisms for connected vehicles to deal with the connectivity challenges. To understand the system behavior of the solutions for connected vehicles, we first need to characterize the operational environment. Therefore, we devised a large scale fading model for various link types, including point-to-point vehicular communications and multi-hop connected vehicles. We explored two small scale fading models to define the characteristics of multi-hop connected vehicles. Taking our research into multi-hop connected vehicles one step further, we propose selective information relaying to avoid message congestion due to redundant messages received by the relay vehicle. Results show that the proposed mechanism reduces messaging load by up to 75% without sacrificing environmental awareness. Once we define the channel characteristics, we propose a distributed congestion control algorithm to solve the messaging overhead on the channels as the next research interest of this dissertation. We propose a combined transmit power and message rate adaptation for connected vehicles. The proposed algorithm increases the environmental awareness and achieves the application requirements by considering highly dynamic network characteristics. Both power and rate adaptation mechanisms are performed jointly to avoid one result affecting the other negatively. Results prove that the proposed algorithm can increase awareness by 20% while keeping the channel load and interference at almost the same level as well as improve the average message rate by 18%. As the last step of this dissertation, distributed cooperative dynamic spectrum access technique is proposed to solve the channel overhead and the limited resources issues. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this work by using a computationally efficient numerical approach. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors. An interdisciplinary approach referred to as entropy-based weighting is used for defining the neighbor credibility. Once the vehicle accesses the channel, we propose a decision mechanism for channel switching that is inspired by the optimal flower selection process employed by bumblebees foraging. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero

Cooperative MIMO multicell networks

n/

Mobile to mobile channel modelling for wireless communications

Wireless communication has been experiencing many recent advances in mobile to mobile (M2M) applications. M2M communication systems differ from conventional fixed to mobile systems by having both transmitter and receiver in low elevation and in motion. This raises the need to come up with new channel models and perform statistical analysis on M2M communication channels looking from a different perspective. This need motivated us to perform the research outlined in this thesis. In reviewing the literature we found that though in general the M2M channel models are sparse, a major gap exists in the non geometrical stochastic based mathematical channel models. In filling this gap, we develop a novel mathematical non geometrical stochastic multiple input multiple output (MIMO) M2M channel model for two dimensional (2D) and three dimensional (3D) scattering environments. This model is based on the underlying physics of free space wave propagation and can be used as a framework for any environment by selecting suitable complex scattering gain functions. In addition, we extend this novel model to multicarrier M2M which is the first multicarrier channel model in the non geometrical stochastic M2M category. Based on our novel M2M channel model, we carry out an extensive analysis in space-time correlation, space-frequency correlation and second order channel statistics. With the choice of suitable parameters, this analysis and channel model can be used for any wireless environment. Thus, we claim that our novel channel model together with the analysis performed in this thesis can be taken as a generalized framework. A significant contribution of our analysis is the consideration of the impact of transmitter and receiver speed to space-time and space-frequency correlation, which is not available in the literature. Using a von Mises-Fisher distribution as the angular power distribution, the usefulness of the derived temporal correlation function is discussed. The simulation results corroborate the fact that both space-time and space-frequency correlations are reduced when transmitter or receiver speed increases. The rate of reduction of space-time correlation in von Mises-Fisher distribution scattering environment is more than in the isotropic environment. Under second order channel statistics, we consider Rice, Rayleigh and Nakagami fading channels in four different non-isotropic scattering environments with angle of departure (AoD) and angle of arrival (AoA) distributions given by (i) separable Truncated Gaussian, (ii) separable von-Mises, (iii) truncated Gaussian bivariate and (iv) truncated Laplacian bivariate distributions. We show that the major second order statistics, namely, the level crossing rate (LCR) and the average fade duration (AFD), in different fading channels can be expressed in terms of known scattering coefficients of the AoD and AoA distributions. As the channel models and their respective measurements provide reliable knowledge of the channel for the design and analysis of M2M systems, the proposed channel model and the corresponding analysis will be useful for the design, testing and performance evaluation of future M2M communication systems

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

MIMO channel modelling and simulation for cellular and mobile-to-mobile

Recently, mobile-to-mobile (M2M) communications have received much attention due to several emerging applications, such as wireless mobile ad hoc networks, relay-based cellular networks, and dedicated short range communications (DSRC) for intelligent transportation systems (e.g., IEEE 802.11p standard). Different from conventional fixed-to-mobile (F2M) cellular systems, in M2M systems both the transmitter (Tx) and receiver (Rx) are in motion and often equipped with low elevation antennas. Multiple-input-multiple-output (MIMO) technologies, employing multiple antennas at both the Tx and Rx, have widely been adopted for the third generation (3G) and beyond-3G (B3G) F2M cellular systems due to their potential benefits of improving coverage, link reliability, and overall system capacity. More recently, MIMO has been receiving more and more attention for M2M systems as well. Reliable knowledge of the propagation channel obtained from channel measurements and corresponding channel models serve as the enabling foundation for the design and analysis of MIMO F2M and M2M systems. Furthermore, the development of accurate MIMO F2M and M2M channel simulation models plays a major role in the practical simulation and performance evaluation of these systems. These form the primary motivation behind our research on MIMO channel modelling and simulation for F2M cellular and M2M communication systems. In this thesis, we first propose a new wideband theoretical multiple-ring based MIMO regular-shaped geometry-based stochastic model (RS-GBSM) for non-isotropic scattering F2M macro-cell scenarios and then derive a generic space-time-frequency (STF) correlation function (CF). The proposed theoretical reference wideband model can be reduced to a narrowband one-ring model, a new closed-form STF CF of which is derived as well. Narrowband and wideband sum-of-sinusoids (SoS) simulation models are then developed, demonstrating a good agreement with the corresponding reference models in terms of correlation functions. Secondly, based on a well-known narrowband two-ring single-input single-output (SISO) M2M channel reference model, we propose new deterministic and stochastic SoS simulation models for non-isotropic scattering environments. The proposed deterministic simulator is the first SISO M2M deterministic simulator with good performance, while the proposed stochastic simulator outperforms the existing one in terms of fitting the desired statistical properties of the corresponding reference model. Thirdly, a new adaptive narrowband MIMO M2M RS-GBSM is proposed for nonisotropic scattering environments. To the best of our knowledge, the proposed M2M model is the first RS-GBSM that has the ability to study the impact of the vehicular traffic density on channel statistics. From the proposed theoretical reference model, we comprehensively investigate some important M2M channel statistics including the STF CF, space-Doppler-frequency power spectral density, envelope level crossing rate, and average fade duration. A close agreement between some channel statistics obtained from the proposed reference model and measurement data is observed, confirming the utility of our model. Finally, we extend the above narrowband model to a new wideband MIMO M2M RSGBSM with respect to the frequency-selectivity. The proposed wideband reference model is validated by observing a good match between some statistical properties of the theoretical model and available measurement data. From the wideband reference model, we further design new wideband deterministic and stochastic SoS simulation models. The proposed wideband simulators can be easily reduced to narrowband ones. The utilities of the newly derived narrowband and wideband simulation models are validated by comparing their statistical properties with those of the corresponding reference models. The proposed channel reference models and simulators are expected to be useful for the design, testing, and performance evaluation of future MIMO cellular and M2M communication systems.Scottish Funding Counci