Experimental investigation of RF fading channels and receiver detection

This thesis includes experimental investigation of Multiple Input Multiple Output (MIMO) Radio Frequency (RF) fading channels and detection of superregenerative receivers. Details of experiment design and hardware implementation, data acquisition and analysis, and results for both studies are chronicled into two papers. The first paper investigates the validity of the discrete time triply selective fading channel model for fixed mobile-to-mobile MIMO channels. A 2x2 MIMO-OFDM testbed using the Altera Stratix III EP3SL150F field programmable gate array (FPGA) DSP development kit is used for acquiring experimental data. Subsequent offline signal processing and analysis are done in MATLAB. The Channel Impulse Response (CIR) is estimated using the Time domain Least Squares (LS) method. The channel coefficient covariance matrix is decomposed into its Kronecker factors - the spatial correlation matrix, inter-tap correlation matrix, and temporal correlation matrix. This study verifies the theoretical hypothesis and simulation results. The second paper proposes a novel method for detection of the superregnerative RF receivers. The algorithm is based on active stimulation and correlation of long pseudonoise (PN) sequences. An experimental setup is established using the Universal Software Radio Peripheral (USRP) as the primary component. Simulation results show that the maximum length PN sequences exhibit the best correlation properties among different potential stimulation signals. Proposed method improves range and accuracy of detection as compared to the passive detection and power detection methods --Abstract, page iv

Channel Acquisition for Massive MIMO-OFDM with Adjustable Phase Shift Pilots

We propose adjustable phase shift pilots (APSPs) for channel acquisition in wideband massive multiple-input multiple-output (MIMO) systems employing orthogonal frequency division multiplexing (OFDM) to reduce the pilot overhead. Based on a physically motivated channel model, we first establish a relationship between channel space-frequency correlations and the channel power angle-delay spectrum in the massive antenna array regime, which reveals the channel sparsity in massive MIMO-OFDM. With this channel model, we then investigate channel acquisition, including channel estimation and channel prediction, for massive MIMO-OFDM with APSPs. We show that channel acquisition performance in terms of sum mean square error can be minimized if the user terminals' channel power distributions in the angle-delay domain can be made non-overlapping with proper phase shift scheduling. A simplified pilot phase shift scheduling algorithm is developed based on this optimal channel acquisition condition. The performance of APSPs is investigated for both one symbol and multiple symbol data models. Simulations demonstrate that the proposed APSP approach can provide substantial performance gains in terms of achievable spectral efficiency over the conventional phase shift orthogonal pilot approach in typical mobility scenarios.Comment: 15 pages, 4 figures, accepted for publication in the IEEE Transactions on Signal Processin

Distributed space-time block coding in cooperative relay networks with application in cognitive radio

Spatial diversity is an effective technique to combat the effects of severe fading in wireless environments. Recently, cooperative communications has emerged as an attractive communications paradigm that can introduce a new form of spatial diversity which is known as cooperative diversity, that can enhance system reliability without sacrificing the scarce bandwidth resource or consuming more transmit power. It enables single-antenna terminals in a wireless relay network to share their antennas to form a virtual antenna array on the basis of their distributed locations. As such, the same diversity gains as in multi-input multi-output systems can be achieved without requiring multiple-antenna terminals. In this thesis, a new approach to cooperative communications via distributed extended orthogonal space-time block coding (D-EO-STBC) based on limited partial feedback is proposed for cooperative relay networks with three and four relay nodes and then generalized for an arbitrary number of relay nodes. This scheme can achieve full cooperative diversity and full transmission rate in addition to array gain, and it has certain properties that make it alluring for practical systems such as orthogonality, flexibility, low computational complexity and decoding delay, and high robustness to node failure. Versions of the closed-loop D-EO-STBC scheme based on cooperative orthogonal frequency division multiplexing type transmission are also proposed for both flat and frequency-selective fading channels which can overcome imperfect synchronization in the network. As such, this proposed technique can effectively cope with the effects of fading and timing errors. Moreover, to increase the end-to-end data rate, this scheme is extended for two-way relay networks through a three-time slot framework. On the other hand, to substantially reduce the feedback channel overhead, limited feedback approaches based on parameter quantization are proposed. In particular, an optimal one-bit partial feedback approach is proposed for the generalized D-O-STBC scheme to maximize the array gain. To further enhance the end-to-end bit error rate performance of the cooperative relay system, a relay selection scheme based on D-EO-STBC is then proposed. Finally, to highlight the utility of the proposed D-EO-STBC scheme, an application to cognitive radio is studied

A Site-Specific Indoor Wireless Propagation Model

In this thesis, we explore the fundamental concepts behind the emerging field of site-specific propagation modeling for wireless communication systems. The first three chapters of background material discuss, respectively, the motivation for this study, the context of the study, and signal behavior and modeling in the predominant wireless propagation environments. A brief survey of existing ray-tracing based site-specific propagation models follows this discussion, leading naturally to the work of new model development undertaken in our thesis project. Following the detailed description of our generalized wireless channel modeling, various interference cases incorporating with this model are thoroughly discussed and results presented at the end of this thesis

Deep Learning of Transferable MIMO Channel Modes for 6G V2X Communications

In the emerging high mobility vehicle-to-everything (V2X) communications using millimeter wave (mmWave) and sub-THz, multiple-input multiple-output (MIMO) channel estimation is an extremely challenging task. At mmWaves/sub-THz frequencies, MIMO channels exhibit few leading paths in the space-time (ST) domain (i.e., directions or arrival/departure and delays). Algebraic low-rank (LR) channel estimation exploits ST channel sparsity through the computation of position-dependent MIMO channel eigenmodes leveraging recurrent training vehicle passages in the coverage cell. LR requires vehicles' geographical positions and tens to hundreds of training vehicles' passages for each position, leading to significant complexity and control signaling overhead. Here, we design a deep-learning (DL)-based LR channel estimation method to infer MIMO channel eigenmodes in V2X urban settings, starting from a single least squares (LS) channel estimate and without needing vehicle's position information. Numerical results show that the proposed method attains comparable mean squared error (mse) performance as the position-based LR. Moreover, we show that the proposed model can be trained on a reference scenario and be effectively transferred to urban contexts with different ST channel features, providing comparable mse performance without an explicit transfer learning procedure. This result eases the deployment in arbitrary dense urban scenarios

Frequency Domain Autocorrelation Based Compressed Spectrum Sensing for Cognitive Radio

As wireless applications are growing rapidly in the modern world, this results in the shortage of radio spectrum due to the fixed allocation of spectrum by governmental agencies for different wireless technologies. This problem raises interest to utilize spectrum in a more efficient way, in order to provide spectrum access to other users when they need it. In wireless communications systems, cognitive radio (CR) is getting much attention due to its capability to combat with this scarcity problem. A CR senses the available spectrum band to check the activity of primary users (PU). It utilizes the unused spectral resources by providing access to secondary users (SU). Spectrum sensing (SS) is one of the most critical issues in cognitive radio, and there are various SS methods for the detection of PU signals. An energy detector (ED) based SS is the most common sensing method due to its simple implementation and low computational complexity. This method works well in ideal scenarios but its detection performance for PU signal degrades drastically under low SNR values in the presence of noise uncertainty. Eigenvalue-based SS method performs well with such real-life issues, but it has very high computational complexity. This raises a demand for such a detector which has less computational complexity and can perform well in practical wireless multipath channels as well as under noise uncertainty. This study focuses on a novel variant of autocorrelation detector operating in the frequency domain (FD-AC). The method is applicable to PUs using the OFDM waveform with the cyclic prefix (CP). The FD-AC method utilizes fast Fourier transform (FFT) and detects an active PU through the CP-induced correlation peak estimated from the FFT-domain samples. It detects the spectral holes in the available electromagnetic spectrum resources in an efficient way, in order to provide opportunistic access to SUs. The proposed method is also insensitive to the practical wireless channel effects. Hence, it works well in frequency selective channels. It also has the capability to mitigate the effects of noise uncertainty and therefore, it is robust to noise uncertainty. FD-AC facilitates partial band sensing which can be considered as a compressed spectrum sensing method. This allows sensing weak PU signals which are partly overlapped by other strong PU or CR transmissions. On the other hand, it helps in the reduction of computational complexity while sensing PU signal in the available spectrum band, depending on the targeted sensitivity. Moreover, it has highly increased flexibility and it is capable of facilitating robust wideband multi-mode sensing with low complexity. Its performance for the detection of PU signal does not depend on the known time lag, therefore, it can perform well in such conditions where the detailed OFDM signal characteristics are not known

Empirical multi-band characterization of propagation with modelling aspects for communictions

Diese Arbeit präsentiert eine empirische Untersuchung der Wellenausbreitung für drahtlose Kommunikation im Millimeterwellen- und sub-THz-Band, wobei als Referenz das bereits bekannte und untersuchte sub-6-GHz-Band verwendet wird. Die großen verfügbaren Bandbreiten in diesen hohen Frequenzbändern erlauben die Verwendung hoher instantaner Bandbreiten zur Erfüllung der wesentlichen Anforderungen zukünftiger Mobilfunktechnologien (5G, “5G and beyond” und 6G). Aufgrund zunehmender Pfad- und Eindringverluste bei zunehmender Trägerfrequenz ist die resultierende Abdeckung dabei jedoch stark reduziert. Die entstehenden Pfadverluste können durch die Verwendung hochdirektiver Funkschnittstellen kompensiert werden, wodurch die resultierende Auflösung im Winkelbereich erhöht wird und die Notwendigkeit einer räumlichen Kenntnis der Systeme mit sich bringt: Woher kommt das Signal? Darüber hinaus erhöhen größere Anwendungsbandbreiten die Auflösung im Zeitbereich, reduzieren das small-scale Fading und ermöglichen die Untersuchung innerhalb von Clustern von Mehrwegekomponenten. Daraus ergibt sich für Kommunikationssysteme ein vorhersagbareres Bild im Winkel-, Zeit- und Polarisationsbereich, welches Eigenschaften sind, die in Kanalmodellen für diese Frequenzen widergespiegelt werden müssen. Aus diesem Grund wurde in der vorliegenden Arbeit eine umfassende Charakterisierung der Wellenausbreitung durch simultane Multibandmessungen in den sub-6 GHz-, Millimeterwellen- und sub-THz-Bändern vorgestellt. Zu Beginn wurde die Eignung des simultanen Multiband-Messverfahrens zur Charakterisierung der Ausbreitung von Grenzwert-Leistungsprofilen und large-scale Parametern bewertet. Anschließend wurden wichtige Wellenausbreitungsaspekte für die Ein- und Multibandkanalmodellierung innerhalb mehrerer Säulen der 5G-Technologie identifiziert und Erweiterungen zu verbreiteten räumlichen Kanalmodellen eingeführt und bewertet, welche die oben genannten Systemaspekte abdecken.This thesis presents an empirical characterization of propagation for wireless communications at mm-waves and sub-THz, taking as a reference the already well known and studied sub-6 GHz band. The large blocks of free spectrum available at these high frequency bands makes them particularly suitable to provide the necessary instantaneous bandwidths to meet the requirements of future wireless technologies (5G, 5G and beyond, and 6G). However, isotropic path-loss and penetration-loss are larger with increasing carrier frequency, hence, coverage is severely reduced. Path-loss can be compensated with the utilization of highly directive radio-interfaces, which increases the resolution in the angular domain. Nonetheless, this emphasizes the need of spatial awareness of systems, making more relevant the question “where does the signal come from?” In addition, larger application bandwidths increase the resolution in the time domain, reducing small-scale fading and allowing to observe inside of clusters of multi-path components (MPCs). Consequently, communication systems have a more deterministic picture of the environment in the angular, time, and polarization domain, characteristics that need to be reflected in channel models for these frequencies. Therefore, in the present work we introduce an extensive characterization of propagation by intensive simultaneous multi-band measurements in the sub-6 GHz, mm-waves, and sub-THz bands. Firstly, the suitability of the simultaneous multi-band measurement procedure to characterize propagation from marginal power profiles and large-scale parameters (LSPs) has been evaluated. Then, key propagation aspects for single and multi-band channel modelling in several verticals of 5G have been identified, and extensions to popular spatial channel models (SCMs) covering the aforementioned system aspects have been introduced and evaluated