Adaptive Spectrum Sensing in Cognitive Radio Employing Multitaper Method and Higher-Order STBC Techniques

Tue, 19 Nov 2024 00:00:00 +0800

The effects of the non-parametric multitaper method (MTM) and symmetrical higher-order space-time block-code (STBC) with full diversity techniques on the performance of spectrum sensing (SS) in cognitive radio (CR) systems are studied. The overall wireless link performance can be improved by using the STBC techniques to combat the multipath fading effects in wireless channels. The MTM is integrated with the STBC for spectrum estimation (SE), which will be termed multitaper spectrum estimation (MTSE)-STBC, and the given analysis of which is developed using the quadrature form approximation. Also, classical SE algorithms commonly focus on a fixed performance assessment method based on predefined false alarms or detection probabilities. Licensed users need to be protected against interference that opportunistic users might cause. An appropriate thresholding policy that varies concerning the designated values of false alarm and detection rates can achieve such protection. Utilization factors are instrumental in providing further protection for licensed users or occupied spectrum holes, and they need to be determined in advance and adopted in the detection policy. If utilization factors are not desirable, then a fine selection of appropriate threshold values will need to be decided as they have a major impact on the overall error probability performance. Using analytical and simulation methods, the assessment results revealed improved performance of the MTSE-STBC compared to other classical methods such as the Periodogram especially in the aspects of efficient transmission and less error probability. The proposed adaptive thresholding technique also proved useful in coping with different SE settings.

Evaluation of Key Performance Factors and Recommendation of Optimization Strategies of a Power Generation Company

Wed, 13 Nov 2024 00:00:00 +0800

This paper presents the analysis of key performance indicators and some effective improvement strategies of four gas turbine generators (GTG) of Nigeria's power plant company for four years (2019-2022). The investigation used the NERC/IEEE Standard 762 (2006) generator performance indices amongst other calculated key performance indices to evaluate the collected data. The research methodology was done through the collection of data using questionnaires, operational records, and plant data sheets recorded by operators in the power station and data analysis using Excel software, and then constructive optimization techniques were recommended for each key performance factor. From the result obtained, the operational performance shows an average energy generation of approximately 389.71 GWh. The equipment availability factor averaged 54.08%, indicating moderate reliability. The energy availability factor was notably lower, averaging 11.99%, suggesting significant room for improvement. The capacity factor averaged 9.39%, while the plant use factor was relatively high at 80.59%, demonstrating efficient operational usage. The load factor was low, with an average of 0.10, pointing to potential underutilization of capacity. The shortfall in performance levels is attributed to less plant availability due to overdue overhauling of some units resulting in frequent breakdowns/failures, obsolete technology, aging plant equipment, instability of the national grid system, and disruption in gas supply among others. The recommended strategic techniques are designed to address the specific challenges associated with each factor, thereby enhancing the overall operational performance of the power plant and other power generation companies for maximum productivity.

Engineering Science & Technology

Adaptive Spectrum Sensing in Cognitive Radio Employing Multitaper Method and Higher-Order STBC Techniques

Evaluation of Key Performance Factors and Recommendation of Optimization Strategies of a Power Generation Company