Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost Platforms
The computational complexity of the multiple-input and multiple-output (MIMO) based least square algorithm is very high and it cannot be run on processing-inefficient low-cost platforms. To overcome complexity-related problems, a parallel distributed adaptive signal processing (PDASP) architecture i...
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MDPI AG
2022-12-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/23/4600 |
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| author | Hasan Raza Ishtiaq Ahmad Noor M. Khan Waseem Abbasi Muhammad Shahid Anwar Sadique Ahmad Mohammed A. El-Affendi |
| author_facet | Hasan Raza Ishtiaq Ahmad Noor M. Khan Waseem Abbasi Muhammad Shahid Anwar Sadique Ahmad Mohammed A. El-Affendi |
| author_sort | Hasan Raza |
| collection | DOAJ |
| description | The computational complexity of the multiple-input and multiple-output (MIMO) based least square algorithm is very high and it cannot be run on processing-inefficient low-cost platforms. To overcome complexity-related problems, a parallel distributed adaptive signal processing (PDASP) architecture is proposed, which is a distributed framework used to efficiently run the adaptive filtering algorithms having high computational cost. In this paper, a communication load-balancing procedure is introduced to validate the PDASP architecture using low-cost wireless sensor nodes. The PDASP architecture with the implementation of a multiple-input multiple-output (MIMO) based Recursive Least Square (RLS) algorithm is deployed on the processing-inefficient low-cost wireless sensor nodes to validate the performance of the PDASP architecture in terms of computational cost, processing time, and memory utilization. Furthermore, the processing time and memory utilization provided by the PDASP architecture are compared with sequentially operated RLS-based MIMO channel estimator on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2</mn><mo>×</mo><mn>2</mn></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mo>×</mo><mn>3</mn></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4</mn><mo>×</mo><mn>4</mn></mrow></semantics></math></inline-formula> MIMO communication systems. The measurement results show that the sequentially operated MIMO RLS algorithm based on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mo>×</mo><mn>3</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4</mn><mo>×</mo><mn>4</mn></mrow></semantics></math></inline-formula> MIMO communication systems is unable to work on a single unit; however, these MIMO systems can efficiently be run on the PDASP architecture with reduced memory utilization and processing time. |
| first_indexed | 2024-03-09T17:41:11Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T17:41:11Z |
| publishDate | 2022-12-01 |
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| spelling | doaj.art-f6f417910d064328ac386073dc8041ce2023-11-24T11:36:18ZengMDPI AGMathematics2227-73902022-12-011023460010.3390/math10234600Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost PlatformsHasan Raza0Ishtiaq Ahmad1Noor M. Khan2Waseem Abbasi3Muhammad Shahid Anwar4Sadique Ahmad5Mohammed A. El-Affendi6Department of Electrical Engineering, Hamdard University, Islamabad 44000, PakistanDepartment of Electrical Engineering, Capital University of Science and Technology, Islamabad 44000, PakistanDepartment of Electrical Engineering, Capital University of Science and Technology, Islamabad 44000, PakistanDepartment of Electrical Engineering, MY University, Islamabad 46000, PakistanDepartment of AI Software, Gachon University, Seongnam-si 13120, Republic of KoreaEIAS: Data Science and Blockchain Laboratory, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi ArabiaEIAS: Data Science and Blockchain Laboratory, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi ArabiaThe computational complexity of the multiple-input and multiple-output (MIMO) based least square algorithm is very high and it cannot be run on processing-inefficient low-cost platforms. To overcome complexity-related problems, a parallel distributed adaptive signal processing (PDASP) architecture is proposed, which is a distributed framework used to efficiently run the adaptive filtering algorithms having high computational cost. In this paper, a communication load-balancing procedure is introduced to validate the PDASP architecture using low-cost wireless sensor nodes. The PDASP architecture with the implementation of a multiple-input multiple-output (MIMO) based Recursive Least Square (RLS) algorithm is deployed on the processing-inefficient low-cost wireless sensor nodes to validate the performance of the PDASP architecture in terms of computational cost, processing time, and memory utilization. Furthermore, the processing time and memory utilization provided by the PDASP architecture are compared with sequentially operated RLS-based MIMO channel estimator on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2</mn><mo>×</mo><mn>2</mn></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mo>×</mo><mn>3</mn></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4</mn><mo>×</mo><mn>4</mn></mrow></semantics></math></inline-formula> MIMO communication systems. The measurement results show that the sequentially operated MIMO RLS algorithm based on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mo>×</mo><mn>3</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4</mn><mo>×</mo><mn>4</mn></mrow></semantics></math></inline-formula> MIMO communication systems is unable to work on a single unit; however, these MIMO systems can efficiently be run on the PDASP architecture with reduced memory utilization and processing time.https://www.mdpi.com/2227-7390/10/23/4600distributed MIMO channel estimationlow computational complexityparallel processing |
| spellingShingle | Hasan Raza Ishtiaq Ahmad Noor M. Khan Waseem Abbasi Muhammad Shahid Anwar Sadique Ahmad Mohammed A. El-Affendi Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost Platforms Mathematics distributed MIMO channel estimation low computational complexity parallel processing |
| title | Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost Platforms |
| title_full | Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost Platforms |
| title_fullStr | Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost Platforms |
| title_full_unstemmed | Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost Platforms |
| title_short | Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost Platforms |
| title_sort | validation of parallel distributed adaptive signal processing pdasp framework through processing inefficient low cost platforms |
| topic | distributed MIMO channel estimation low computational complexity parallel processing |
| url | https://www.mdpi.com/2227-7390/10/23/4600 |
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