Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access
User activity detection in grant-free random access massive machine type communication (mMTC) using pilot-hopping sequences can be formulated as solving a non-negative least squares (NNLS) problem. In this work, two architectures using different algorithms to solve the NNLS problem is proposed. The...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
|
| Series: | IEEE Open Journal of Circuits and Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9336347/ |
| _version_ | 1818876736591364096 |
|---|---|
| author | Narges Mohammadi Sarband Ema Becirovic Mattias Krysander Erik G. Larsson Oscar Gustafsson |
| author_facet | Narges Mohammadi Sarband Ema Becirovic Mattias Krysander Erik G. Larsson Oscar Gustafsson |
| author_sort | Narges Mohammadi Sarband |
| collection | DOAJ |
| description | User activity detection in grant-free random access massive machine type communication (mMTC) using pilot-hopping sequences can be formulated as solving a non-negative least squares (NNLS) problem. In this work, two architectures using different algorithms to solve the NNLS problem is proposed. The algorithms are implemented using a fully parallel approach and fixed-point arithmetic, leading to high detection rates and low power consumption. The first algorithm, fast projected gradients, converges faster to the optimal value. The second algorithm, multiplicative updates, is partially implemented in the logarithmic domain, and provides a smaller chip area and lower power consumption. For a detection rate of about one million detections per second, the chip area for the fast algorithm is about 0.7 mm<sup>2</sup> compared to about 0.5 mm<sup>2</sup> for the multiplicative algorithm when implemented in a 28 nm FD-SOI standard cell process at 1 V power supply voltage. The energy consumption is about 300 nJ/detection for the fast projected gradient algorithm using 256 iterations, leading to a convergence close to the theoretical. With 128 iterations, about 250 nJ/detection is required, with a detection performance on par with 192 iterations of the multiplicative algorithm for which about 100 nJ/detection is required. |
| first_indexed | 2024-12-19T13:47:08Z |
| format | Article |
| id | doaj.art-152e9e972e3441d1803a56af92e221f5 |
| institution | Directory Open Access Journal |
| issn | 2644-1225 |
| language | English |
| last_indexed | 2024-12-19T13:47:08Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Circuits and Systems |
| spelling | doaj.art-152e9e972e3441d1803a56af92e221f52022-12-21T20:18:50ZengIEEEIEEE Open Journal of Circuits and Systems2644-12252021-01-01225326410.1109/OJCAS.2020.30436439336347Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random AccessNarges Mohammadi Sarband0Ema Becirovic1https://orcid.org/0000-0002-6841-3405Mattias Krysander2Erik G. Larsson3https://orcid.org/0000-0002-7599-4367Oscar Gustafsson4https://orcid.org/0000-0003-3470-3911Department of Electrical Engineering, Linköping University, Linköping, SwedenDepartment of Electrical Engineering, Linköping University, Linköping, SwedenDepartment of Electrical Engineering, Linköping University, Linköping, SwedenDepartment of Electrical Engineering, Linköping University, Linköping, SwedenDepartment of Electrical Engineering, Linköping University, Linköping, SwedenUser activity detection in grant-free random access massive machine type communication (mMTC) using pilot-hopping sequences can be formulated as solving a non-negative least squares (NNLS) problem. In this work, two architectures using different algorithms to solve the NNLS problem is proposed. The algorithms are implemented using a fully parallel approach and fixed-point arithmetic, leading to high detection rates and low power consumption. The first algorithm, fast projected gradients, converges faster to the optimal value. The second algorithm, multiplicative updates, is partially implemented in the logarithmic domain, and provides a smaller chip area and lower power consumption. For a detection rate of about one million detections per second, the chip area for the fast algorithm is about 0.7 mm<sup>2</sup> compared to about 0.5 mm<sup>2</sup> for the multiplicative algorithm when implemented in a 28 nm FD-SOI standard cell process at 1 V power supply voltage. The energy consumption is about 300 nJ/detection for the fast projected gradient algorithm using 256 iterations, leading to a convergence close to the theoretical. With 128 iterations, about 250 nJ/detection is required, with a detection performance on par with 192 iterations of the multiplicative algorithm for which about 100 nJ/detection is required.https://ieeexplore.ieee.org/document/9336347/5G mobile communicationbase stationsInternet of Thingsmachine-to-machine communicationsMIMO |
| spellingShingle | Narges Mohammadi Sarband Ema Becirovic Mattias Krysander Erik G. Larsson Oscar Gustafsson Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access IEEE Open Journal of Circuits and Systems 5G mobile communication base stations Internet of Things machine-to-machine communications MIMO |
| title | Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access |
| title_full | Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access |
| title_fullStr | Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access |
| title_full_unstemmed | Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access |
| title_short | Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access |
| title_sort | massive machine type communication pilot hopping sequence detection architectures based on non negative least squares for grant free random access |
| topic | 5G mobile communication base stations Internet of Things machine-to-machine communications MIMO |
| url | https://ieeexplore.ieee.org/document/9336347/ |
| work_keys_str_mv | AT nargesmohammadisarband massivemachinetypecommunicationpilothoppingsequencedetectionarchitecturesbasedonnonnegativeleastsquaresforgrantfreerandomaccess AT emabecirovic massivemachinetypecommunicationpilothoppingsequencedetectionarchitecturesbasedonnonnegativeleastsquaresforgrantfreerandomaccess AT mattiaskrysander massivemachinetypecommunicationpilothoppingsequencedetectionarchitecturesbasedonnonnegativeleastsquaresforgrantfreerandomaccess AT erikglarsson massivemachinetypecommunicationpilothoppingsequencedetectionarchitecturesbasedonnonnegativeleastsquaresforgrantfreerandomaccess AT oscargustafsson massivemachinetypecommunicationpilothoppingsequencedetectionarchitecturesbasedonnonnegativeleastsquaresforgrantfreerandomaccess |