Analysing energy detector diversity receivers for spectrum sensing

The analysis of energy detector systems is a well studied topic in the literature: numerous models have been derived describing the behaviour of single and multiple antenna architectures operating in a variety of radio environments. However, in many cases of interest, these models are not in a closed form and so their evaluation requires the use of numerical methods. In general, these are computationally expensive, which can cause difficulties in certain scenarios, such as in the optimisation of device parameters on low cost hardware. The problem becomes acute in situations where the signal to noise ratio is small and reliable detection is to be ensured or where the number of samples of the received signal is large. Furthermore, due to the analytic complexity of the models, further insight into the behaviour of various system parameters of interest is not readily apparent. In this thesis, an approximation based approach is taken towards the analysis of such systems. By focusing on the situations where exact analyses become complicated, and making a small number of astute simplifications to the underlying mathematical models, it is possible to derive novel, accurate and compact descriptions of system behaviour. Approximations are derived for the analysis of energy detectors with single and multiple antennae operating on additive white Gaussian noise (AWGN) and independent and identically distributed Rayleigh, Nakagami-m and Rice channels; in the multiple antenna case, approximations are derived for systems with maximal ratio combiner (MRC), equal gain combiner (EGC) and square law combiner (SLC) diversity. In each case, error bounds are derived describing the maximum error resulting from the use of the approximations. In addition, it is demonstrated that the derived approximations require fewer computations of simple functions than any of the exact models available in the literature. Consequently, the regions of applicability of the approximations directly complement the regions of applicability of the available exact models. Further novel approximations for other system parameters of interest, such as sample complexity, minimum detectable signal to noise ratio and diversity gain, are also derived. In the course of the analysis, a novel theorem describing the convergence of the chi square, noncentral chi square and gamma distributions towards the normal distribution is derived. The theorem describes a tight upper bound on the error resulting from the application of the central limit theorem to random variables of the aforementioned distributions and gives a much better description of the resulting error than existing Berry-Esseen type bounds. A second novel theorem, providing an upper bound on the maximum error resulting from the use of the central limit theorem to approximate the noncentral chi square distribution where the noncentrality parameter is a multiple of the number of degrees of freedom, is also derived.

An investigation on the use of SNR distributions for the optimisation of coarse-fine spectrum sensing for cognitive radio

This thesis investigates the optimisation of Coarse-Fine (CF) spectrum sensing architectures under a distribution of SNRs for Dynamic Spectrum Access (DSA). Three different detector architectures are investigated: the Coarse-Sorting Fine Detector (CSFD), the Coarse-Deciding Fine Detector (CDFD) and the Hybrid Coarse-Fine Detector (HCFD). To date, the majority of the work on coarse-fine spectrum sensing for cognitive radio has focused on a single value for the SNR. This approach overlooks the key advantage that CF sensing has to offer, namely that high powered signals can be easily detected without extra signal processing. By considering a range of SNR values, the detector can be optimised more effectively and greater performance gains realised. This work considers the optimisation of CF spectrum sensing schemes where the security and performance are treated separately. Instead of optimising system performance at a single, constant, low SNR value, the system instead is optimised for the average operating conditions. The security is still provided such that at the low SNR values the safety specifications are met. By decoupling the security and performance, the system’s average performance increases whilst maintaining the protection of licensed users from harmful interference. The different architectures considered in this thesis are investigated in theory, simulation and physical implementation to provide a complete overview of the performance of each system. This thesis provides a method for estimating SNR distributions which is quick, accurate and relatively low cost. The CSFD is modelled and the characteristic equations are found for the CDFD scheme. The HCFD is introduced and optimisation schemes for all three architectures are proposed. Finally, using the Implementing Radio In Software (IRIS) test-bed to confirm simulation results, CF spectrum sensing is shown to be significantly quicker than naive methods, whilst still meeting the required interference probability rates and not requiring substantial receiver complexity increases.

Identification and analysis of mechanisms involved in a broad-spectrum disease resistant mutant of the winter wheat cv. Guardian

M66 an X-ray induced mutant of winter wheat (Triticum aestivum) cv. Guardian exhibits broad-spectrum resistance to powdery mildew (Blumeria graminis f. sp. tritici), yellow rust (Puccinia striiformis f. sp. tritici), and leaf rust (Puccinia recondita f. sp. tritici), along with partial resistance to stagnonospora nodorum blotch (caused by the necrotroph Stagonosporum nodorum) and septoria tritici blotch (caused by the hemibiotroph Mycosphaerella graminicola) compared to the parent plant ‘Guardian’. Analysis revealed that M66 exhibited no symptoms of infection following artificial inoculation with Bgt in the glasshouse after adult growth stage (GS 45). Resistance in M66 was associated with widespread leaf flecking which developed during tillering. Flecking also occurred in M66 leaves without Bgt challenge; as a result grain yields were reduced by approximately 17% compared to ‘Guardian’ in the absence of disease. At the seedling stage, M66 exhibited partial resistance. M66, along with Tht mutants (Tht 12, Tht13), also exhibit increased tolerance to environmental stresses (abiotic), such as drought and heat stress at seedling and adult growth stages, However, adult M66 exhibited increased susceptibility to the aphid Schizaphis graminum compared to ‘Guardian’. Resistance to Bgt in M66 was characterized with increased and earlier H2O2 accumulation at the site of infection which resulted in increased papilla formation in epidermal cells, compared to ‘Guardian’. Papilla formation was associated with reduced pathogen ingress and haustorium formation, indicating that the primary cause of resistance in M66 was prevention of pathogen penetration. Heat treatment at 46º C prior to challenge with Bgt also induced partial disease resistance to Blumeria graminis f. sp. tritici in ‘Guardian’ and M66 seedlings. This was characterized by a delay in primary infection, due to increased production of ROS species, such as hydrogen peroxide, ROS-scavenging enzymes and Hsp70, resulting in cross-linking of cell wall components prior to inoculation. This actively prevented the fungus from penetrating the epidermal cell wall. Proteomics analysis using 2-D gel electrophoresis identified primary and secondary disease resistance effects in M66 including detection of ROS scavenging enzymes (4, 24 hai), such as ascorbate peroxidase and a superoxidase dismutase isoform (CuZnSOD) in M66 which were absent from ‘Guardian’. Chitinase (PR protein) was also upregulated (24 hai) in M66 compared to ‘Guardian’.Monosomic and ditelosomic analysis of M66 revealed that the mutation in M66 is located on the long arm of chromosome 2B (2BL). Chromosome 2BL is known to have key genes involved in resistance to pathogens such as those causing stripe rust and powdery mildew. The TaMloB1 gene, an orthologue of the barley Mlo gene, is also located on chromosome 2BL. Sanger sequencing of part of the coding sequence revealed no deletions in the TaMloB1 gene between ‘Guardian’ and M66.

Assessing the viability of studying motion indicators of autism spectrum disorders in infants at high and low risk for ASD using a passive motion capture system

Gemstone Team AMIRA

Challenges in the diagnosis and treatment of depression in autism spectrum disorders across the lifespan.

Diagnosis and treatment of comorbid neuropsychiatric illness is often a secondary focus of treatment in individuals with autism spectrum disorder (ASD), given that substantial impairment may be caused by core symptoms of ASD itself. However, psychiatric comorbidities, including depressive disorders, are common and frequently result in additional functional impairment, treatment costs, and burden on caregivers. Clinicians may struggle to appropriately diagnose depression in ASD due to communication deficits, atypical presentation of depression in ASD, and lack of standardized diagnostic tools. Specific risk and resilience factors for depression in ASD across the lifespan, including level of functioning, age, family history, and coping style, have been suggested, but require further study. Treatment with medications or psychotherapy may be beneficial, though more research is required to establish guidelines for management of symptoms. This review will describe typical presentations of depression in individuals with ASD, review current information on the prevalence, assessment, and treatment of comorbid depression in individuals with ASD, and identify important research gaps.

Clinical Spectrum, risk factors and outcome of immune reconstitution inflammatory syndrome in patients with tuberculosis-HIV coinfection.

info:eu-repo/semantics/published

First High-Resolution Analysis of the Absorption Spectrum of Propane in the 6.7-7.5 μm Spectral Region

info:eu-repo/semantics/published

Reply to the comment on 'The dispersed laser induced fluorescence spectrum of gas phase C60 at 308 nm'

info:eu-repo/semantics/published

Parallel dynamic graph-partitioning for unstructured meshes

A parallel method for the dynamic partitioning of unstructured meshes is described. The method introduces a new iterative optimization technique known as relative gain optimization which both balances the workload and attempts to minimize the interprocessor communications overhead. Experiments on a series of adaptively refined meshes indicate that the algorithm provides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more rapidly. Perhaps more importantly, the algorithm results in only a small fraction of the amount of data migration compared to the static partitioners.

A multilevel algorithm for force-directed graph drawing

We describe a heuristic method for drawing graphs which uses a multilevel technique combined with a force-directed placement algorithm. The multilevel process groups vertices to form clusters, uses the clusters to define a new graph and is repeated until the graph size falls below some threshold. The coarsest graph is then given an initial layout and the layout is successively refined on all the graphs starting with the coarsest and ending with the original. In this way the multilevel algorithm both accelerates and gives a more global quality to the force- directed placement. The algorithm can compute both 2 & 3 dimensional layouts and we demonstrate it on a number of examples ranging from 500 to 225,000 vertices. It is also very fast and can compute a 2D layout of a sparse graph in around 30 seconds for a 10,000 vertex graph to around 10 minutes for the largest graph. This is an order of magnitude faster than recent implementations of force-directed placement algorithms.

A multilevel algorithm for force-directed graph-drawing

We describe a heuristic method for drawing graphs which uses a multilevel framework combined with a force-directed placement algorithm. The multilevel technique matches and coalesces pairs of adjacent vertices to define a new graph and is repeated recursively to create a hierarchy of increasingly coarse graphs, G0, G1, …, GL. The coarsest graph, GL, is then given an initial layout and the layout is refined and extended to all the graphs starting with the coarsest and ending with the original. At each successive change of level, l, the initial layout for Gl is taken from its coarser and smaller child graph, Gl+1, and refined using force-directed placement. In this way the multilevel framework both accelerates and appears to give a more global quality to the drawing. The algorithm can compute both 2 & 3 dimensional layouts and we demonstrate it on examples ranging in size from 10 to 225,000 vertices. It is also very fast and can compute a 2D layout of a sparse graph in around 12 seconds for a 10,000 vertex graph to around 5-7 minutes for the largest graphs. This is an order of magnitude faster than recent implementations of force-directed placement algorithms.

A combined evolutionary search and multilevel optimisation approach to graph-partitioning

The graph-partitioning problem is to divide a graph into several pieces so that the number of vertices in each piece is the same within some defined tolerance and the number of cut edges is minimised. Important applications of the problem arise, for example, in parallel processing where data sets need to be distributed across the memory of a parallel machine. Very effective heuristic algorithms have been developed for this problem which run in real-time, but it is not known how good the partitions are since the problem is, in general, NP-complete. This paper reports an evolutionary search algorithm for finding benchmark partitions. A distinctive feature is the use of a multilevel heuristic algorithm to provide an effective crossover. The technique is tested on several example graphs and it is demonstrated that our method can achieve extremely high quality partitions significantly better than those found by the state-of-the-art graph-partitioning packages.