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A 2.92-Gb/s/W and 0.43-Gb/s/MG Flexible and Scalable CGRA-Based Baseband Processor for Massive MIMO Detection
Communication systems' development requires service customization in aspects, such as standards, multiple-input multiple-output (MIMO) scales, and algorithms. The existing hardware designs for massive MIMO detection have difficulty in achieving both high flexibility and scalability with high ha...
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Published in: | IEEE journal of solid-state circuits 2020-02, Vol.55 (2), p.505-519 |
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description | Communication systems' development requires service customization in aspects, such as standards, multiple-input multiple-output (MIMO) scales, and algorithms. The existing hardware designs for massive MIMO detection have difficulty in achieving both high flexibility and scalability with high hardware efficiency. This article proposes a baseband processor based on a dynamic coarse-grained reconfigurable array (CGRA) for massive MIMO detection. To efficiently support various algorithm features and requirements, three optimization techniques are proposed to achieve high flexibility and scalability. First, an on-demand matrix-vector systolic array is proposed to enable flexible and scalable matrix and vector operations, reducing memory accesses by 82%. Second, distributed multi-interaction data storage is designed for flexible data access and reusability. Finally, a continuable adaptive context information format is proposed to support different bit widths, operations, and extensions of MIMO systems, reducing context information by 67%. These techniques achieve the improvements of 1.33×, 1.34×, and 1.29× in energy efficiency and 1.21×, 1.18×, and 1.18× in area efficiency, evaluated by removing one technique at a time from the proposed architecture. Fabricated in a 28-nm CMOS technology, the chip achieves high flexibility and scalability in supporting various detection algorithms; various MIMO scales, such as 4 × 4, 32 × 32, and 128 × 8; and baseband processing tasks, such as filtering and fast Fourier transformation. When benchmarked on various detection algorithms, the processor achieves 1.64-2.92-Gb/s/W energy efficiency and 0.25-0.43-Gb/s/MG area efficiency, which are 2.78-28.54× and 2.05-14.43× those of state-of-the-art programmable designs, respectively. To our knowledge, this is the first flexible and scalable CGRA-based baseband processor for massive MIMO detection. |
doi_str_mv | 10.1109/JSSC.2019.2952839 |
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The existing hardware designs for massive MIMO detection have difficulty in achieving both high flexibility and scalability with high hardware efficiency. This article proposes a baseband processor based on a dynamic coarse-grained reconfigurable array (CGRA) for massive MIMO detection. To efficiently support various algorithm features and requirements, three optimization techniques are proposed to achieve high flexibility and scalability. First, an on-demand matrix-vector systolic array is proposed to enable flexible and scalable matrix and vector operations, reducing memory accesses by 82%. Second, distributed multi-interaction data storage is designed for flexible data access and reusability. Finally, a continuable adaptive context information format is proposed to support different bit widths, operations, and extensions of MIMO systems, reducing context information by 67%. These techniques achieve the improvements of 1.33×, 1.34×, and 1.29× in energy efficiency and 1.21×, 1.18×, and 1.18× in area efficiency, evaluated by removing one technique at a time from the proposed architecture. Fabricated in a 28-nm CMOS technology, the chip achieves high flexibility and scalability in supporting various detection algorithms; various MIMO scales, such as 4 × 4, 32 × 32, and 128 × 8; and baseband processing tasks, such as filtering and fast Fourier transformation. When benchmarked on various detection algorithms, the processor achieves 1.64-2.92-Gb/s/W energy efficiency and 0.25-0.43-Gb/s/MG area efficiency, which are 2.78-28.54× and 2.05-14.43× those of state-of-the-art programmable designs, respectively. To our knowledge, this is the first flexible and scalable CGRA-based baseband processor for massive MIMO detection.</description><identifier>ISSN: 0018-9200</identifier><identifier>EISSN: 1558-173X</identifier><identifier>DOI: 10.1109/JSSC.2019.2952839</identifier><identifier>CODEN: IJSCBC</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Baseband ; CMOS ; Coarse-grained reconfigurable architecture (CGRA) ; Communications systems ; Computer architecture ; Context ; Data storage ; Detection algorithms ; energy and area efficiencies ; Energy efficiency ; Fast Fourier transformations ; Flexibility ; flexibility and scalability ; Hardware ; massive multiple-input multiple-output (MIMO) detection ; Mathematical analysis ; Matrix algebra ; Matrix methods ; Microprocessors ; MIMO (control systems) ; Optimization ; Optimization techniques ; Power efficiency ; reconfigurable baseband processor ; Scalability</subject><ispartof>IEEE journal of solid-state circuits, 2020-02, Vol.55 (2), p.505-519</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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These techniques achieve the improvements of 1.33×, 1.34×, and 1.29× in energy efficiency and 1.21×, 1.18×, and 1.18× in area efficiency, evaluated by removing one technique at a time from the proposed architecture. Fabricated in a 28-nm CMOS technology, the chip achieves high flexibility and scalability in supporting various detection algorithms; various MIMO scales, such as 4 × 4, 32 × 32, and 128 × 8; and baseband processing tasks, such as filtering and fast Fourier transformation. When benchmarked on various detection algorithms, the processor achieves 1.64-2.92-Gb/s/W energy efficiency and 0.25-0.43-Gb/s/MG area efficiency, which are 2.78-28.54× and 2.05-14.43× those of state-of-the-art programmable designs, respectively. To our knowledge, this is the first flexible and scalable CGRA-based baseband processor for massive MIMO detection.</description><subject>Algorithms</subject><subject>Baseband</subject><subject>CMOS</subject><subject>Coarse-grained reconfigurable architecture (CGRA)</subject><subject>Communications systems</subject><subject>Computer architecture</subject><subject>Context</subject><subject>Data storage</subject><subject>Detection algorithms</subject><subject>energy and area efficiencies</subject><subject>Energy efficiency</subject><subject>Fast Fourier transformations</subject><subject>Flexibility</subject><subject>flexibility and scalability</subject><subject>Hardware</subject><subject>massive multiple-input multiple-output (MIMO) detection</subject><subject>Mathematical analysis</subject><subject>Matrix algebra</subject><subject>Matrix methods</subject><subject>Microprocessors</subject><subject>MIMO (control systems)</subject><subject>Optimization</subject><subject>Optimization techniques</subject><subject>Power efficiency</subject><subject>reconfigurable baseband processor</subject><subject>Scalability</subject><issn>0018-9200</issn><issn>1558-173X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNo9UF1LwzAUDaLgnP4A8SXgc7t8tE3yOKerk5WJU_QtJO0tdHTrTDrRf29rhw_3Xg7n48JB6JqSkFKiJk_r9SxkhKqQqZhJrk7QiMaxDKjgH6doRAiVgWKEnKML7zcdjCJJR2g7xSxULEjtxE_esdkVmIQRH3CW4nkN35Wt4Y9Z56Y2PZilL9PgzngocL9tTz67JgfvG4fLbjLjffUFOFtkK3wPLeRt1ewu0Vlpag9XxztGb_OH19ljsFyli9l0GeRM8TaIotgkUsjCSsZkbqyUkVG5SVhhCs5LaxQkieAFFMQSLoQwloOIygQKm1PgY3Q75O5d83kA3-pNc3C77qVmPFKUxiKOOxUdVLlrvHdQ6r2rtsb9aEp036ruW9V9q_rYaue5GTwVAPzrZRfJiOC_bPhwEw</recordid><startdate>20200201</startdate><enddate>20200201</enddate><creator>Peng, Guiqiang</creator><creator>Liu, Leibo</creator><creator>Zhou, Sheng</creator><creator>Yin, Shouyi</creator><creator>Wei, Shaojun</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The existing hardware designs for massive MIMO detection have difficulty in achieving both high flexibility and scalability with high hardware efficiency. This article proposes a baseband processor based on a dynamic coarse-grained reconfigurable array (CGRA) for massive MIMO detection. To efficiently support various algorithm features and requirements, three optimization techniques are proposed to achieve high flexibility and scalability. First, an on-demand matrix-vector systolic array is proposed to enable flexible and scalable matrix and vector operations, reducing memory accesses by 82%. Second, distributed multi-interaction data storage is designed for flexible data access and reusability. Finally, a continuable adaptive context information format is proposed to support different bit widths, operations, and extensions of MIMO systems, reducing context information by 67%. These techniques achieve the improvements of 1.33×, 1.34×, and 1.29× in energy efficiency and 1.21×, 1.18×, and 1.18× in area efficiency, evaluated by removing one technique at a time from the proposed architecture. Fabricated in a 28-nm CMOS technology, the chip achieves high flexibility and scalability in supporting various detection algorithms; various MIMO scales, such as 4 × 4, 32 × 32, and 128 × 8; and baseband processing tasks, such as filtering and fast Fourier transformation. When benchmarked on various detection algorithms, the processor achieves 1.64-2.92-Gb/s/W energy efficiency and 0.25-0.43-Gb/s/MG area efficiency, which are 2.78-28.54× and 2.05-14.43× those of state-of-the-art programmable designs, respectively. 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subjects | Algorithms Baseband CMOS Coarse-grained reconfigurable architecture (CGRA) Communications systems Computer architecture Context Data storage Detection algorithms energy and area efficiencies Energy efficiency Fast Fourier transformations Flexibility flexibility and scalability Hardware massive multiple-input multiple-output (MIMO) detection Mathematical analysis Matrix algebra Matrix methods Microprocessors MIMO (control systems) Optimization Optimization techniques Power efficiency reconfigurable baseband processor Scalability |
title | A 2.92-Gb/s/W and 0.43-Gb/s/MG Flexible and Scalable CGRA-Based Baseband Processor for Massive MIMO Detection |
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