An antenna array is overloaded when the number of cochannel signals in its operating environment exceeds the number of elements. Conventional space-time array processing for narrow-band signals fails in overloaded environments. Overloaded array processing (OLAP) is most difficult when signals impinging on the array are near equal power, have tight excess bandwidth, and are of identical signal type. Despite the failure of conventional beamforming in such environments, OLAP becomes possible when a receiver exploits additional signal properties such as the finite-alphabet property and signal excess-bandwidth. This thesis proposes three approaches to signal extraction in overloaded environments, each providing a different tradeoff in performance and complexity. The first receiver architecture extracts signals from an overloaded environment through the use of MMSE interference rejection filtering embedded in a successive interference cancellation (SIC) architecture. The second receiver architecture enhances signal extraction performance by embedding a stronger interference rejection receiver, the reduced-state maximum aposteriori probability (RS-MAP) algorithm in a similar SIC architecture. The third receiver fine-tunes the performance of spatially reduced search joint detection (SRSJD) with the application of an energy focusing transform (EFT), a complexity reducing front-end linear pre-processor. A new type of EFT, the Energy Focusing Unitary Relaxed Transform (EFURT) is developed. This transform facilitates a continuous tradeoff between noise-enhancement and error-propagation in an SRSJD framework. EFURT is used to study the role of this tradeoff for SRSJD receivers in a variety of signal environments. It is found that for the environments studied in this thesis, SRSJD enjoys an aggressive reduction in interference at the expense of possible noise-enhancement. / Ph. D.

Ultra-Wideband technology has attracted interests of the researchers and commercial groups due to its advantage of high data rate, low complexity and low power consumption. The direct-sequence code division multiple access ultra wideband system (DS-CDMA UWB) is one of the proposal of IEEE 802.15.3a standard. By combing the power of both UWB and DS-CDMA techniques, the system could construct multiple access architecture using direct sequence method. In multi-user environment, the major problem of the receiver designing of conventional DS-CDMA system is multiple access interference(MAI). In DS-CDMA UWB system, the transmitted signal were interfered by inter-symbol interference(ISI) and neighbor symbol interference because of the multi-path channel characteristic. In this thesis, we use the training method to get the spreading waveform influenced by multi-path. Based on the information of spreading waveform, we use the block method to reformulate the received signal. We can separate the interference into multiple access interference and neighbor symbol interference. With Combining the interference cancellation, probabilistic data association (PDA) filter and sliding window techniques, we could eliminate the interference. In the computer simulation section, we compare the detection performance of sliding window PDA detector with conventional detector, and the simulation result shows that the improved PDA detector has better performance than others.

A non-coherent PN code tracking loop with multi-user detection and simplified multi-path interference cancellation (MPIC) is proposed for direct sequence spread spectrum communications system. A decorrelator decision-feedback detector (DDFD) is first applied on the incoming signal to mitigate the multi-user interference. Then, a simplified multi-path interference cancellation (MPIC) is further used to increase signal quality. Finally, a modified code tracking loop (MCTL) is adopted for non-coherent PN code tracking. Mathematical expressions of the S-curve and tracking jitter are derived. Mean time to lose lock is also compared with traditional tracking loops. From the numerical results, we know the proposed PN code tracking loop can efficiently mitigate the interference from multi-user and multi-path and improve the performance of code tracking loop.

Motivated by potential applications in wireless sensor networks, this thesis considers the problem of communicating a large number of correlated analog sources over a Gaussian multiple-access channel using non-orthogonal code-division multiple-access (CDMA). A joint source-channel decoder is presented which can exploit the inter-source correlation for interference reduction in the CDMA channel. This decoder uses a linear minimum mean square error (MMSE) multi-user detector (MUD) in tandem with a MMSE joint source decoder (JSD) for multiple sources to achieve a computational complexity that scales with the number of sources. The MUD and the JSD, then iteratively exchange extrinsic information to improve the interference cancellation. Experimental results show that, compared to a non-iterative decoder, the proposed iterative decoder is more robust against potential performance degradation due to correlated channel interference and offers better near far resistance.

Motivated by potential applications in wireless sensor networks, this thesis considers the problem of communicating a large number of correlated analog sources over a Gaussian multiple-access channel using non-orthogonal code-division multiple-access (CDMA). A joint source-channel decoder is presented which can exploit the inter-source correlation for interference reduction in the CDMA channel. This decoder uses a linear minimum mean square error (MMSE) multi-user detector (MUD) in tandem with a MMSE joint source decoder (JSD) for multiple sources to achieve a computational complexity that scales with the number of sources. The MUD and the JSD, then iteratively exchange extrinsic information to improve the interference cancellation. Experimental results show that, compared to a non-iterative decoder, the proposed iterative decoder is more robust against potential performance degradation due to correlated channel interference and offers better near far resistance.

Cognitive radio networks (CRNs) have emerged as a solution for the looming spectrum crunch caused by the rapid adoption of wireless devices over the previous decade. This technology enables efficient spectrum utility by dynamically reusing existing spectral bands. A CRN achieves this by requiring its users – called secondary users (SUs) – to measure and opportunistically utilise the band of a legacy broadcaster – called a primary user (PU) – in a process called spectrum sensing. Sensing requires the distribution and fusion of measurements from all SUs, which is facilitated by a variety of architectures and topologies. CRNs possessing a central computation node are called centralised networks, while CRNs composed of multiple computation nodes are called decentralised networks. While simpler to implement, centralised networks are reliant on the central node – the entire network fails if this node is compromised. In contrast, decentralised networks require more sophisticated protocols to implement, while offering greater robustness to node failure. Relay-based networks, a subset of decentralised networks, distribute the computation over a number of specialised relay nodes – little research exists on spectrum sensing using these networks. CRNs are vulnerable to unique physical layer attacks targeted at their spectrum sensing functionality. One such attack is the Byzantine attack; these attacks occur when malicious SUs (MUs) alter their sensing reports to achieve some goal (e.g. exploitation of the CRN’s resources, reduction of the CRN’s sensing performance, etc.). Mitigation strategies for Byzantine attacks vary based on the CRN’s network architecture, requiring defence algorithms to be explored for all architectures. Because of the sparse literature regarding relay-based networks, a novel algorithm – suitable for relay-based networks – is proposed in this work. The proposed algorithm performs joint MU detection and secure sensing by large-scale probabilistic inference of a statistical model. The proposed algorithm’s development is separated into the following two parts. • The first part involves the construction of a probabilistic graphical model representing the likelihood of all possible outcomes in the sensing process of a relay-based network. This is done by discovering the conditional dependencies present between the variables of the model. Various candidate graphical models are explored, and the mathematical description of the chosen graphical model is determined. • The second part involves the extraction of information from the graphical model to provide utility for sensing. Marginal inference is used to enable this information extraction. Belief propagation is used to infer the developed graphical model efficiently. Sensing is performed by exchanging the intermediate belief propagation computations between the relays of the CRN. Through a performance evaluation, the proposed algorithm was found to be resistant to probabilistic MU attacks of all frequencies and proportions. The sensing performance was highly sensitive to the placement of the relays and honest SUs, with the performance improving when the number of relays was increased. The transient behaviour of the proposed algorithm was evaluated in terms of its dynamics and computational complexity, with the algorithm’s results deemed satisfactory in this regard. Finally, an analysis of the effectiveness of the graphical model’s components was conducted, with a few model components accounting for most of the performance, implying that further simplifications to the proposed algorithm are possible. / Dissertation (MEng)--University of Pretoria, 2020. / Electrical, Electronic and Computer Engineering / MEng / Unrestricted

abstract: In the artificial intelligence literature, three forms of reasoning are commonly employed to understand agent behavior: inductive, deductive, and abductive.  More recently, data-driven approaches leveraging ideas such as machine learning, data mining, and social network analysis have gained popularity. While data-driven variants of the aforementioned forms of reasoning have been applied separately, there is little work on how data-driven approaches across all three forms relate and lend themselves to practical applications. Given an agent behavior and the percept sequence, how one can identify a specific outcome such as the likeliest explanation? To address real-world problems, it is vital to understand the different types of reasonings which can lead to better data-driven inference.   This dissertation has laid the groundwork for studying these relationships and applying them to three real-world problems. In criminal modeling, inductive and deductive reasonings are applied to early prediction of violent criminal gang members. To address this problem the features derived from the co-arrestee social network as well as geographical and temporal features are leveraged. Then, a data-driven variant of geospatial abductive inference is studied in missing person problem to locate the missing person. Finally, induction and abduction reasonings are studied for identifying pathogenic accounts of a cascade in social networks. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

Evolution of wireless services enabled the development of the advanced applications and shifted the paradigms of research in this field from voice to data centric. Such services are spreading like wildfire between users and hence, increasing the demand for large bandwidth. However, the frequency spectrum that is suitable for wireless mobile communications is already assigned to particular services from 400 MHz to several GHz. Also, allocating a large chunk of band continuously from the same part of the spectrum may not be possible due to spectral crowd. Therefore, meeting the demand for high data rate requiring wireless services within the accessible spectrum range becomes a challenging problem. The spectrum allocation policies are discussed by regulatory authorities and academia, and the idea of spectrum sharing systems are addressed as a solution. For instance, heterogeneous networks (HetNets) increase the number of available resources and improve the spectrum accessing capabilities of the wireless communication systems. To achieve this, HetNet nodes are deployed within the coverage of the macrocell regions. Thus, spectral efficiency is boosted via spatial reuse of the same spectral resources. On the contrary, HetNets preclude to fully exploit the resources because of serious interference problems between macrocell and HetNet nodes. Thus, wireless networks of the future will observe interference from even a larger number of sources. Due to co-channel HetNet deployment and denser frequency reuse, interference cancellation is expected to have significant importance for future wireless communication systems. The occupied resources can also be reused as a solution by conducting advanced signal processing algorithms at the receiver to increase the spectral efficiency. While doing so, the proposed approaches are expected to be easily integrated with the existing complementary approaches to improve the capacity further. Besides, new deployment strategies that allow spectrum access for non-licensed users to achieve larger bandwidth become important to increase the spectral efficiency of the HetNets. Within the scope of the dissertation, new solutions are developed for the aforementioned problems of the next-generation wireless communication systems. First, an interference cancellation receiver that exploits the unique characteristics of current waveforms is developed in Chapter 2. Also the unknown model of interference is converted to a known model and new algorithms are proposed to recover the desired signal. Then, another perspective is brought into the subject by transforming the interference problem to an interference advantage in Chapter 3. The idea of co-existence of different types of signals are analyzed to bring another degree of freedom as a solution. The proposed approaches are integrated to the existing complementary approaches, such as interference coordination and power control, to improve the capacity further. Finally, a cooperation mechanism is suggested to facilitate the transmission of signal which has a large bandwidth by integrating the idle bands in Chapter 4. By this way, geo-spatially idle bands within the coverage area are utilized and spectral efficiency is increased.

Recently, a novel technique for multi-user spread-spectrum mobile systems, the called interleave-division multiple-access (IDMA) scheme, was proposed by L. Ping etc. The advantage of IDMA is that it inherits many special features from code-division multiple-access (CDMA) such as diversity against fading and mitigation of the other-cell user interference. Moreover, it¡¦s capable of employing a very simple chip-by-chip iterative multi-user detection strategy. In this thesis, we investigate the performance of combining IDMA and orthogonal frequency-division multiplexing (OFDM) scheme. In order to improve the bit error rate performance, we applied low-density parity-check (LDPC) coding to the proposed scheme, named by LDPC Coded OFDM-IDMA Systems. Based on the aid of iterative multi-user detection algorithm, the multiple-access interference (MAI) and inter-symbol interference (ISI) could be canceling efficiently. In short, the proposed scheme provides an efficient solution to high-rate multiuser communications over multipath fading channels.

While radio frequency identification tags (RFIDs) have been widely used for identifying objects (and some people), their primary use has been for access control, inventory, and other similar purposes. In this thesis we will use the detection of an RFID to indicate that a user is present in a given location.  This will be used to extend a Session Initiation Protocol (SIP) system with user presence. A typical HF RFID reader is able to read a tag from a range of 8-10 cm. In this application we wish to read tags from a range of 50 to 100 cm (the width of a doorway or narrow hallway). One of the challenges is how to increase the reading range while staying below the maximum RF power limits (for reasons of safety). Providing an RFID based presence indication can be used to automatically adjust the heating, ventilation, and air conditioning system of a room, etc. This thesis presents several different antennas which were analyzed and simulated using FEKO to obtain a suitable antenna for this target application. The thesis shows that fractal patterns are the best for the intended application based upon the results of simulations. These antennas were implemented and tested. The prototype establishes that such antennas are a suitable design and can be used with current RFID systems to achieve long ranges. The thesis also suggests some future enhancements to these antennas. / Identifiering av radiofrekvenstaggar (RFID) har använts i stor utsträckning för att identifiera objekt (och vissa människor). De primära användningsområdena har varit åtkomstkontroll, inventering, och andra liknande ändamål. I denna avhandling kommer vi att använda närvaroupptäckten av en RFID-tagg för att ange att en användare befinner sig påen given plats. Detta kommer att användas för att utöka ett Session Initiation Protocol-system med användarnärvaro. En typisk HF RFID-läsare kan läsa en tagg från ett avstånd av 8-10 cm. I denna appliceringen vill vi läsa RFID-taggar från ett avstånd av 50 till 100 cm (bredden påen dörröppning eller en smal korridor). En av utmaningarna är hur man kan öka läsavståndet och samtidigt hålla sig under de maximala RF-effektgränserna (av säkerhetsskäl). En RFIDbaserad närvaroindikering kan användas för att automatiskt justera värme, ventilation och luftkonditionering av ett rum, osv. I denna avhandling kommer vi att presentera olika antenner som analyserades och simulerades med hjälp av FEKO, för att erhålla en lämplig antenn. Avhandlingen visar att de bästa resultaten från simuleringarna för det huvudsakliga målet, är att använda fraktala mönster. Genomförandet och testerna av dessa antenner leder till en prototyp av en gynnsam antennutformning, som en bas för framtida förbättringar. Dessutom beskriver vi skälen till varför fraktalantenner ofta används i nuvarande RFID-system för att uppnålånga läsavstånd.