Algorithms for wireless communication systems using SDR platform

Tezin basılısı İstanbul Şehir Üniversitesi Kütüphanesi'ndedir.This thesis presents a detailed study on software based channel emulators and a set of algorithms pertaining to the soft emulator. With the fact that several wireless communications technologies were released in the last decades, there are a lot of challenging issues emerging due to the need for faster and more reliable technologies. From these challenging issues, we have chosen to focus our research on two outstanding challenges: real-time software channel emulator and automatic modulation classification. Recently, there has been an increase in the demand for a reliable and low-cost channel emulator to study the effects of real wireless channels. Hence, in the first part of the thesis, wediscussanimplementationofareal-timesoftwarechannelemulator. Thereal-time fading channel emulator was implemented by using a software defined radio platform. In order to verify the model, the frequency spectrum specifications of the channel generated was checked with a double tone transmitter. Then as a second step of verification, bit error rate (BER) of a real-time Orthogonal Frequency Division Multiplexing system using the Universal Software Radio Peripheral (USRP) and LABVIEW software was compared with the BER floor calculated from the theoretical equations. It has been shown that the developed channel emulator can indeed emulate a fading wireless channel. In the second part of the thesis we focused on covering an issue related to blind estimation or classification of a parameter in wireless communications at the receiver. This problem appears in cognitive radios and some defense applications where the receivers needs to know the type of the modulation of an incoming signal. The efficient automatic modulation classification scheme proposed in this study can be utilized for a group of digitally modulated signals such as QPSK, 16-PSK, 64-PSK, 4-QAM, 16-QAM, and 64QAM. We performed the classification in two stages: first we classified the modulation between QAM and PSK signaling, and then we determined the M-ary order of the modulation by developing Kernel Density Estimation and analyzing the probability density distribution for the real and imaginary parts of the modulated signals. Simulations were carried out to evaluate the performance of the proposed scheme for flat channels. Thus, in this thesis first of all we were able to develop a software based channel emulator. The developed channel emulator can be a very useful tool for other researchers in testing their real-time systems on a verified Doppler channel. Moreover, the emulator can find other applications from education to wireless device developments due to its flexibility. On the other hand, with the automatic modulation classification, the unknown modulation of an incoming signal can be determined. Hence, the two issues can be combined to find applications in cognitive radio developments.Abstract iii Öz v Acknowledgments viii List of Figures xi Abbreviations xiii 1 Introduction and Literature Review 1 1.1 Channel Emulators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Automatic Modulation Classification . . . . . . . . . . . . . . . . . . . . . 4 1.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 Real Time Fading Channel Emulator using SDR 8 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 Implementation of fading channels . . . . . . . . . . . . . . . . . . . . . . 10 2.2.1 Implementation of Multipath Doppler Channel . . . . . . . . . . . 13 2.2.2 Specifications of the OFDM system used in verification . . . . . . 14 2.3 Theoretical BER curves . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.4.1 First verification phase . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.4.2 Second verification phase . . . . . . . . . . . . . . . . . . . . . . . 19 2.4.3 Multipath channel simulation results . . . . . . . . . . . . . . . . . 21 2.4.4 Sources of error and mismatch . . . . . . . . . . . . . . . . . . . . 22 2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 3 Automatic Modulation Classification based on Kernel Density Estimation 25 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.2 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.2.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.2.2 Signal model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.2.3 KDE for the Modulation estimation . . . . . . . . . . . . . . . . . 28 3.2.4 Filtering to improve modulation estimation . . . . . . . . . . . . . 29 3.2.5 AMC proposed flow diagram . . . . . . . . . . . . . . . . . . . . . 31 3.3 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.3.1 Choosing parameters . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.3.2 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.3.3 Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4 Conclusion and Future Work 40 4.1 Channel emulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.2 Automatic Modulation Classification . . . . . . . . . . . . . . . . . . . . . 41 4.3 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 A Proof for equation 2.4 used to calculate the BER for a given fading channel with certain fD 43 B LABVIEW diagram used to generate the curves in Figure 2.14 46 Bibliography 4

Performance evaluation of future wireless networks: node cooperation and aerial networks

Perhaps future historians will only refer to this era as the \emph{information age}, and will recognize it as a paramount milestone in mankind progress. One of the main pillars of this age is the ability to transmit and communicate information effectively and reliably, where wireless radio technology became one of the most vital enablers for such communication. A growth in radio communication demand is notably accelerating in a never-resting pace, pausing a great challenge not only on service providers but also on researches and innovators to explore out-of-the-box technologies. These challenges are mainly related to providing faster data communication over seamless, reliable and cost efficient wireless network, given the limited availability of physical radio resources, and taking into consideration the environmental impact caused by the increasing energy consumption. Traditional wireless communication is usually deployed in a cellular manner, where fixed base stations coordinate radio resources and play the role of an intermediate data handler. The concept of cellular networks and hotspots is widely adopted as the current stable scheme of wireless communication. However in many situations this fixed infrastructure could be impaired with severe damages caused by natural disasters, or could suffer congestions and traffic blockage. In addition to the fact that in the current networks any mobile-to-mobile data sessions should pass through the serving base station that might cause unnecessary energy consumption. In order to enhance the performance and reliability of future wireless networks and to reduce its environmental footprint, we explore two complementary concepts: the first is node cooperation and the second is aerial networks. With the ability of wireless nodes to cooperate lays two main possible opportunities; one is the ability of the direct delivery of information between the communicating nodes without relaying traffic through the serving base station, thus reducing energy consumption and alleviating traffic congestion. A second opportunity would be that one of the nodes helps a farther one by relaying its traffic towards the base station, thus extending network coverage and reliability. Both schemes can introduce significant energy saving and can enhance the overall availability of wireless networks in case of natural disasters. In addition to node cooperation, a complementary technology to explore is the \emph{aerial networks} where base stations are airborne on aerial platforms such as airships, UAVs or blimps. Aerial networks can provide a rapidly deployable coverage for remote areas or regions afflicted by natural disasters or even to patch surge traffic demand in public events. Where node cooperation can be implemented to complement both regular terrestrial coverage and to complement aerial networks. In this research, we explore these two complementary technologies, from both an experimental approach and from an analytic approach. From the experimental perspective we shed the light on the radio channel properties that is hosting terrestrial node cooperation and air-to-ground communication, namely we utilize both simulation results and practical measurements to formulate radio propagation models for device-to-device communication and for air-to-ground links. Furthermore we investigate radio spectrum availability for node cooperation in different urban environment, by conductive extensive mobile measurement survey. Within the experimental approach, we also investigate a novel concept of temporary cognitive femtocell network as an applied solution for public safety communication networks during the aftermath of a natural disaster. While from the analytical perspective, we utilize mathematical tools from stochastic geometry to formulate novel analytical methodologies, explaining some of the most important theoretical boundaries of the achievable enhancements in network performance promised by node cooperation. We start by determining the estimated coverage and rate received by mobile users from convectional cellular networks and from aerial platforms. After that we optimize this coverage and rate ensuring that relay nodes and users can fully exploit their coverage efficiently. We continue by analytically quantifying the cellular network performance during massive infrastructure failure, where some nodes play the role of low-power relays forming multi-hop communication links to assist farther nodes outside the reach of the healthy network coverage. In addition, we lay a mathematical framework for estimating the energy saving of a mediating relay assisting a pair of wireless devices, where we derive closed-form expressions for describing the geometrical zone where relaying is energy efficient. Furthermore, we introduce a novel analytic approach in analyzing the energy consumption of aerial-backhauled wireless nodes on ground fields through the assistance of an aerial base station, the novel mathematical framework is based on Mat\'{e}rn hard-core point process. Then we shed the light on the points interacting of these point processes quantifying their main properties. Throughout this thesis we relay on verifying the analytic results and formulas against computer simulations using Monte-Carlo analysis. We also present practical numerical examples to reflect the usefulness of the presented methodologies and results in real life scenarios. Most of the work presented in this dissertation was published in-part or as a whole in highly ranked peer-reviewed journals, conference proceedings, book chapters, or otherwise currently undergoing a review process. These publications are highlighted and identified in the course of this thesis. Finally, we wish the reader to enjoy exploring the journey of this thesis, and hope it will add more understanding to the promising new technologies of aerial networks and node cooperation

Modelling and Analysis of Non-Stationary Mobile Fading Channels Using Brownian Random Trajectory Models

Doktorgradsavhandling i informasjons- og kommunikasjonsteknologi, Universitetet i Agder, Grimstad, 2014The demanding mobility features of communication technologies call for the need to advance channel models (among other needs), in which non-stationary aspects of the channel are carefully taken into consideration. Owing to the mathematical complexity imposed by mobility features of the mobile station (MS), the number of non-stationary channel models proposed in the literature is very limited. The absence of a robust trajectory model for capturing the mobility features of the MS also adds to the depth of this gap. Not only statistically non-stationary channels, but also physically non-stationary channels, such as vehicle-to-vehicle channels in the presence of moving scatterers, have been rarely investigated. In the literature, there exist two fundamental channel modelling approaches, namely deterministic and stochastic approaches. Deterministic approaches, such as measurement-based channel modelling, are known to be accurate, but site-specific and economically expensive. The stochastic approaches, such as geometry-based channel modelling, are known to be economically inexpensive, computationally fair, but not as accurate as the deterministic approach. Among these approaches, the geometry-based stochastic approach is the best to capture the non-stationary aspects of the channel. In this dissertation, we employ the geometry-based stochastic approach for the development of three types of channel models, namely stationary, physically nonstationary, and statistically non-stationary channel models. We geometrically track the plane waves emitted from the transmitter over the local scatterers up to the receiver, which is assumed to be in motion. Under the assumptions that the scatterers are fixed and the observation time is short enough, we develop the stationary channel models. In this regard, we propose a unified disk scattering model (UDSM), which unifies several well-established geometry-based channel models into one robust channel model. We show that the UDSM is highly flexible and outperforms several other geometric models in the sense of matching empirical data. In addition, we provide a new approach to develop stationary channel models based on delay-angle joint distribution functions. Under the assumption that the scatterers are in motion and the observation time is again short enough, we develop a physically non-stationary channel model. In this connection, we model vehicle-to-vehicle (V2V) channels in the presence of moving scatterers. Proper distributions for explaining the speed of relatively fast and relatively slow moving scatterers are provided. The statistical properties of the proposed channel model are also derived and validated by measured channels. It is shown that relatively fast moving scatterers have a major impact on both V2V and fixed-to-fixed (F2F) communication links, as they are significant sources of the Doppler spread. However, relatively slow moving scatterers can be neglected in V2V channels, but not in F2F channels. Under the assumption that the scatterers are fixed and the observation time is not necessarily short anymore, we develop the statistically non-stationary channel models. To this aim, we first introduce a new approach for generating fully spatial random trajectories, which are supposed to capture the mobility features of the MS. By means of this approach, we develop a highly flexible trajectory model based on the primitives of Brownian fields (BFs). We show that the flexibility of the proposed trajectory is threefold: 1) its numerous configurations; 2) its smoothness control mechanism; and 3) its adaptivity to different speed scenarios. The statistical properties of the trajectory model are also derived and validated by data collected from empirical studies. We then introduce a new approach to develop stochastic non-stationary channel models, the randomness of which originates from a random trajectory of the MS, rather than from the scattering area. Based on the new approach, we develop and analyze a non-stationary channel model using the aforementioned Brownian random trajectory model. We show that the channel models developed by this approach are very robust with respect to the number of scatterers, such that highly reported statistical properties can be obtained even if the propagation area is sparsely seeded with scatterers. We also show that the proposed non-stationary channel model superimposes large-scale fading and small-scale fading. Moreover, we show that the proposed model captures the path loss effect. More traditionally, we develop and analyze two non-stationary channel models, the randomness of which originates from the position of scatterers, but not from the trajectory of the MS. Nevertheless, the travelling path of the MS is still determined by a sample function of a Brownian random trajectory. It is shown that the proposed channel models result in a twisted version of the Jakes power spectral density (PSD) that varies in time. Accordingly, it is demonstrated that non-stationarity in time is not in line with the common isotropic propagation assumption on the channel

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