PERFORMANCE ANALYSIS OF SINGLE CARRIER-FREQUENCY DOMAIN EQUALIZATION OVER ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING USING MATLAB

The driving force in today's wireless market is the excellent internet services and growing demand for wireless multimedia. OFDM has been widely accepted as a solution for high-speed broadband applications. In this paper, we have attempted to present a comprehensive overview of a promising alternative solution, SC-FDE, which has been historically shadowed by OFDM. Although the basic ideas behind SC-FDE can be traced back to Walzman and Schwartz's work on adaptive equalizers in 1973, the recent surge of interest in SC-FDE was subsequent to the work of Sari. SC-FDE enjoys a comparable complexity to OFDM due to the similar transceiver architecture based on efficient FFT/IFFT operations. Because of the single-carrier implementation, SC-FDE also avoids the inherent drawbacks of OFDM such as amplifier nonlinearities, carrier frequency offsets, and phase noise. OFDM is commonly used in practice in conjunction with coding. The comparative performance analysis of SC-FDE, coded OFDM, and adaptive OFDM schemes reveals that SC-FDE achieves comparable (or even better in some scenarios) performance compared to its OFDM counterpart. this paper has compared the two schemes SC-FDE and OFDM, especially the BER performance of OFDM & SC-FDE Zero forcing, SC-FDE(MMSE). Both schemes involve frequency-domain processing, and their complexity is similar, in BER curve for ZF and OFDM is OFDM performs better than SC-FDE with zero forcing equalizer. The Zero forcing equalizer runs almost parallel to OFDM BER curve though above it. The reason being whenever there are deep fades in the channel noise gets amplified and results in degradation of the performance & in the BER curve for MMSE equalizer shows better performance compared to OFDM beyond certain Signal to Noise ratio. Unlike ZF equalizer, MMSE coefficients takes into account the effect of channel noise. Also this equalizer can potentially exploit the full diversity available in the channel

Assessment of Soil Fertility Status under the Barren Land Soil of the Central Plain Zone of Uttar Pradesh, India

Soil fertility evaluation of barren land is the most basic decision-making tool for an effective sustainable plan for a particular area. Thus, the present study was carried out to evaluate the soil fertility status in session variation of the two blocks of Kanpur Dehat (Akabrpur and Maitha). The soil samples were randomly collected based on the variability of land at a depth of 0-15 cm, 15-30 cm, and 30-60 cm in 5-5 sites in the both blocks. A GPS device was used to identify the location of the soil sampling points. Soil samples were analyzed for texture, pH, OC, EC, N, P, K, S, Fe, Zn, Cu, Mn, and exchangeable cations status following standard analytic methods in the laboratory of Soil Science and Agricultural Chemistry, C.S.A. University of Agriculture and Technology, Kanpur, UP. The soil organic carbon ranged from 0.18 to 0.34% of both blocks. Available nitrogen ranged from 102.78 to 138.39 kg ha-1, available phosphorous ranged from 9.89 to 16.47 kg ha-1 and available potassium ranged from 230.65 to 276.38 kg ha-1 in the surface soil of Maitha, all of which showed a decrease in value with increase in depth. Exchangeable calcium ranged from 4.58 to 6.34 (cmol (p+) kg-1), exchangeable magnesium ranged from 2.20 to 4.40 (cmol (p+) kg-1), and the pH of the soil in both blocks was highly alkaline in nature, all of which varied significantly with site and depth. The results indicated that soils are not good for the cultivation of various crops. Farmers are required to maintain Soil Health Card which helps them to adopt suitable management practices and provide proper nutrition to soil

Bioprospecting of plant growth promoting psychrotrophic Bacilli from the cold desert of north western Indian Himalayas

142-150<span style="font-size:11.0pt;font-family: " times="" new="" roman";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;mso-ansi-language:en-gb;mso-fareast-language:en-in;mso-bidi-language:="" hi"="" lang="EN-GB">The plant growth promoting psychrotrophic<span style="font-size:11.0pt; font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;mso-ansi-language:en-gb;mso-fareast-language:en-in;="" mso-bidi-language:hi"="" lang="EN-GB"> <span style="font-size:11.0pt; font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;mso-ansi-language:en-gb;mso-fareast-language:en-in;="" mso-bidi-language:hi"="" lang="EN-GB">Bacilli were investigated from different sites in north<span style="font-size:11.0pt; font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;="" mso-bidi-language:hi"="" lang="EN-GB"> <span style="font-size:11.0pt; font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;="" mso-bidi-language:hi"="" lang="EN-GB">western Indian Himalayas. A total of 247 morphotypes were obtained from different soil and water samples and were grouped into 43 clusters based on 16S rDNA-RFLP analysis with three restriction endonucleases. Sequencing of representative isolates has revealed that these 43 Bacilli belonged to different species of 11 genera viz.<span style="mso-bidi-font-style: italic">, Desemzia, Exiguobacterium,<i style="mso-bidi-font-style: normal"> Jeotgalicoccus, Lysinibacillus, Paenibacillus, Planococcus,<i style="mso-bidi-font-style: normal"> Pontibacillus, Sinobaca, Sporosarcina,<i style="mso-bidi-font-style: normal"> Staphylococcus and Virgibacillus. With an aim to develop microbial inoculants that can perform efficiently at low temperatures, all representative isolates were screened for different plant growth promoting traits at low temperatures (5-15<span style="font-size:11.0pt; font-family:Symbol;mso-ascii-font-family:" times="" new="" roman";mso-fareast-font-family:="" "times="" roman";mso-hansi-font-family:"times="" roman";mso-bidi-font-family:="" mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;mso-bidi-language:="" hi;mso-char-type:symbol;mso-symbol-font-family:symbol"="" lang="EN-GB">°C). Among the strains, variations were observed for production (%) of indole-3-acetic acid (20), ammonia (19), siderophores (11), gibberellic acid (4) and hydrogen cyanide (2); <span style="font-size: 11.0pt;font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;="" mso-bidi-language:hi"="" lang="EN-GB">solubilisation (%) of zinc (14), phosphate (13) and potassium (7); 1-aminocyclopropane-1-carboxylate deaminase activity (6%) and biocontrol activity (4%) against <span style="font-size:11.0pt; font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;="" mso-bidi-language:hi;mso-bidi-font-weight:bold"="" lang="EN-GB">Rhizoctonia solani and Macrophomina phaseolina. Among all the strains, <span style="font-size:11.0pt; font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;="" mso-bidi-language:hi"="" lang="EN-GB">Bacillus licheniformis,<i style="mso-bidi-font-style: normal"> Bacillus muralis, Desemzia incerta, <span style="mso-bidi-font-weight: bold;mso-bidi-font-style:italic">Paenibacillus tylopili and Sporosarcina globispora were found to be potent candidates to be developed as inoculants as they exhibited multiple PGP traits at low temperature.</span

Effect of Inorganic Fertilizers, Organic Manure and Bioinoculant on Production and Economics of Wheat (Triticum aestivum L.)

Field experiments were conducted to Studies effect integrated nutrient management on yield and economics of wheat during Rabi season of 2020-21 and 2021-22 at student’s instructional farm, Chandra Shekhar Azad University of Agriculture &amp; Technology, Kanpur. The experiment consists of 10 treatments combinations in randomized block design with three replications consisted of three replications consisted of different combination of inorganic fertilizer, organic and biofertilizer .Wheat variety HD-2967 was grown with the recommended agronomic practices. On the basis of results emanated from investigation it can be concluded that among the productivity parameters viz. maximum grain yield was 53.79 and 54.21 q ha-1, straw yield was 80.76 and 81.35 q ha-1 and biological yield was 134.55 and 135.56 q ha-1 during the both years of experimentation are associated with the treatment T10 [100%NPK + FYM + S30+ Zn5 +Azotobacter + PSB]. Similarly straw yield during first year is 80.6 q ha-1 and second year is 81.35 q ha-1 was associated with the treatment T10 [100%NPK + FYM + S30+ Zn5 +Azotobacter + PSB]. Maximum gross return INR 158043 and INR 156367, net return INR 94499 and INR 97635 and benefit cost ratio (B:C ratio) 1.57 and 1.62 during the first year (2020-21) and second year (2021-22) of experimentation were recorded under treatment T10 [100%NPK + FYM + S30+ Zn5 +Azotobacter + PSB] similarly the maximum cost of cultivation during first year is INR 60192 and second year is INR 60408 were recorded under treatment T10 [100%NPK + FYM + S30+ Zn5 +Azotobacter + PSB]

The Scope for Using Proximal Soil Sensing by the Farmers of India

Knowledge about spatial distribution patterns of soil attributes is very much needed for site-specific soil nutrient management (SSSNM) under precision agriculture. High spatial heterogeneity exists in the agricultural soils of India due to various reasons. The present practice of assessing the spatial variability of the vast cultivated landscape of India by using traditional soil sampling and analysis is costly and time consuming. Hence, proximal soil sensing (PSS) is an attractive option to assess the plot-scale spatial variability pattern (SVP) of soil attributes for SSSNM. A PSS system, either in a fixed position or mounted on a vehicle (on-the-go), can be used to obtain measurements by having direct contact with soil. PSS measurements provide low-cost and high-density data pertaining to the SVPs of soil attributes. These data can be used to generate digital elevation and soil attribute variability maps at the field scale in a crop production environment. Based on the generated variability maps, locally available and economically feasible agricultural inputs can be applied using variable rate application strategies for sustainable cropping and enhanced farm profit. This overview presents the potential of adopting PSS in India and other developing countries. The scope, challenges, and probable solutions are also proposed. There is ample scope for adoption of PSS in India in view of diverse soil types, climatic conditions, cropping patterns, crop management practices, and ultimately, the ever-increasing demand for higher agricultural production. However, the successful adoption of the PSS technique in India will be dependent on the proper design and adoption of strategies which require adequate planning and analysis. There are several studies that have highlighted the usefulness of soil sensing technologies in Indian soils. There are also certain challenges and limitations associated with PSS in India, which could be addressed. The available proximal soil sensing technologies will be of great help in improving the understanding of soil heterogeneity for adopting SSSNM in order to optimize crop production in India and other developing countries

The Scope for Using Proximal Soil Sensing by the Farmers of India

Knowledge about spatial distribution patterns of soil attributes is very much needed for site-specific soil nutrient management (SSSNM) under precision agriculture. High spatial heterogeneity exists in the agricultural soils of India due to various reasons. The present practice of assessing the spatial variability of the vast cultivated landscape of India by using traditional soil sampling and analysis is costly and time consuming. Hence, proximal soil sensing (PSS) is an attractive option to assess the plot-scale spatial variability pattern (SVP) of soil attributes for SSSNM. A PSS system, either in a fixed position or mounted on a vehicle (on-the-go), can be used to obtain measurements by having direct contact with soil. PSS measurements provide low-cost and high-density data pertaining to the SVPs of soil attributes. These data can be used to generate digital elevation and soil attribute variability maps at the field scale in a crop production environment. Based on the generated variability maps, locally available and economically feasible agricultural inputs can be applied using variable rate application strategies for sustainable cropping and enhanced farm profit. This overview presents the potential of adopting PSS in India and other developing countries. The scope, challenges, and probable solutions are also proposed. There is ample scope for adoption of PSS in India in view of diverse soil types, climatic conditions, cropping patterns, crop management practices, and ultimately, the ever-increasing demand for higher agricultural production. However, the successful adoption of the PSS technique in India will be dependent on the proper design and adoption of strategies which require adequate planning and analysis. There are several studies that have highlighted the usefulness of soil sensing technologies in Indian soils. There are also certain challenges and limitations associated with PSS in India, which could be addressed. The available proximal soil sensing technologies will be of great help in improving the understanding of soil heterogeneity for adopting SSSNM in order to optimize crop production in India and other developing countries