Improved Sensing Accuracy using Enhanced Energy Detection Algorithm with Secondary User Cooperation in Cognitive Radios

Spectrum sensing is indispensable for cognitive radio to identify the available white spaces. Energy detection is considered as a preferred technique for spectrum sensing in cognitive radio networks. It is because of its simplicity, applicability and low computational complexity, energy detection is employed widely for spectrum sensing. This paper proposes an enhanced energy detection based spectrum sensing algorithm which incorporates the features of traditional energy detection and cooperative detection. The false alarm and detection probabilities of the proposed algorithm are derived theoretically under AWGN channel conditions. The performance of the proposed algorithm is evaluated analytically for various decision thresholds. The performance evaluations indicate that the proposed enhanced energy detection algorithm outshines the traditional energy detection algorithm and greatly improves the spectrum sensing accuracy under varying SNR conditions

Molecular studies on intraspecific diversity and phylogenetic position of Coniothyrium minitans

Simple sequence repeat (SSR)±PCR amplification using a microsatellite primer (GACA)% and ribosomal RNA gene sequencing were used to examine the intraspecific diversity in the mycoparasite Coniothyrium minitans based on 48 strains, representing eight colony types, from 17 countries world-wide. Coniothyrium cerealis, C. fuckelii and C. sporulosum were used for interspecific comparison. The SSR±PCR technique revealed a relatively low level of polymorphism within C. minitans but did allow some differentiation between strains. While there was no relationship between SSR±PCR profiles and colony type, there was some limited correlation between these profiles and country of origin. Sequences of the ITS 1 and ITS 2 regions and the 5±8S gene of rRNA genes were identical in all twenty-four strains of C. minitans examined irrespective of colony type and origin. These results indicate that C. minitans is genetically not very variable despite phenotypic differences. ITS and 5±8S rRNA gene sequence analyses showed that C. minitans had similarities of 94% with C. fuckelii and C. sporulosum (which were identical to each other) and only 64% with C. cerealis. Database searches failed to show any similarity with the ITS 1 sequence for C. minitans although the 5±8S rRNA gene and ITS 2 sequences revealed an 87% similarity with Aporospora terricola. The ITS sequence including the 5±8S rRNA gene sequence of Coniothyrium cerealis showed 91% similarity to Phaeosphaeria microscopica. Phylogenetic analyses using database information suggest that C. minitans, C. sporulosum, C. fuckelii and A. terricola cluster in one clade, grouping with Helminthosporium species and 'Leptosphaeria' bicolor. Coniothyrium cerealis grouped with Ampelomyces quisqualis and formed a major cluster with members of the Phaeosphaeriacae and Phaeosphaeria microscopica

Genome sequence of the biocontrol agent coniothyrium minitans conio (IMI 134523)

Coniothyrium minitans (synonym, Paraphaeosphaeria minitans) is a highly specific mycoparasite of the wide host range crop pathogen Sclerotinia sclerotiorum. The capability of C. minitans to destroy the sclerotia of S. sclerotiorum has been well recognized and it is available as a widely used biocontrol product Contans WG. We present the draft genome sequence of C. minitans Conio (IMI 134523), which has previously been used in extensive studies that formed part of a registration package of the commercial product. This work provides a distinctive resource for further research into the molecular basis of mycoparasitism to harness the biocontrol potential of C. minitans

AFLP Analysis of Trichoderma spp. from India Compared with Sequence and Morphological-based Diagnostics

Trichoderma species offer considerable potential for controlling aflatoxin contamination in groundnut and other crops. Initial classification of 48 Trichoderma isolates, derived from four different groundnut cultivation sites in India was based on alignment of 28S rDNA sequences to GenBank sequences of ex-type strains. This was found to be substantially more reliable than our routine morphological characterization, but did not provide a comprehensive diagnostic solution, as unique single nucleotide polymorphism (SNP) haplotypes could not be identified for all species. However, all the Trichoderma isolates could be readily distinguished by amplified fragment length polymorphism (AFLP) analysis, based on six primer pair combinations, which generated 234 polymorphic bands. In addition, individual AFLP bands were identified which differentiate closely related species. Similarly, AFLP bands were identified that correlated with different types of antagonism to Aspergillus flavus. The implications of these results for the development of simple polymerase chain reaction (PCR)-based diagnostic assays for antagonistic isolates of Trichoderma is discussed

Biology and biotechnology of Trichoderma

Fungi of the genus Trichoderma are soilborne, green-spored ascomycetes that can be found all over the world. They have been studied with respect to various characteristics and applications and are known as successful colonizers of their habitats, efficiently fighting their competitors. Once established, they launch their potent degradative machinery for decomposition of the often heterogeneous substrate at hand. Therefore, distribution and phylogeny, defense mechanisms, beneficial as well as deleterious interaction with hosts, enzyme production and secretion, sexual development, and response to environmental conditions such as nutrients and light have been studied in great detail with many species of this genus, thus rendering Trichoderma one of the best studied fungi with the genome of three species currently available. Efficient biocontrol strains of the genus are being developed as promising biological fungicides, and their weaponry for this function also includes secondary metabolites with potential applications as novel antibiotics. The cellulases produced by Trichoderma reesei, the biotechnological workhorse of the genus, are important industrial products, especially with respect to production of second generation biofuels from cellulosic waste. Genetic engineering not only led to significant improvements in industrial processes but also to intriguing insights into the biology of these fungi and is now complemented by the availability of a sexual cycle in T. reesei/Hypocrea jecorina, which significantly facilitates both industrial and basic research. This review aims to give a broad overview on the qualities and versatility of the best studied Trichoderma species and to highlight intriguing findings as well as promising applications

SPECTRUM SENSING IN COGNITIVE RADIOS UNDER NOISE UNCERTAINTY: DECISION MAKING USING GAME THEORY

Energy detection is best suited for the detection of licensed users when prior knowledge about them is unavailable. However, the presence of noise uncertainty refrains the use of energy detection for spectrum sensing. In this paper, we propose a refined energy detection (RED) which used dual threshold in the presence of noise uncertainty, and combine the concepts from game theory to achieve further performance improvements. The secondary user payoff is defined based on the primary user activity and the strategy adopted by the secondary user. The pure strategy Nash equilibrium and the best response for the mixed strategy Nash equilibrium are analyzed for all the possible strategies adopted by the secondary user. Simulations results show the effectiveness of the proposed algorithm in terms of greater secondary user payoff and robustness against noise uncertainty