Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix
The joint optimization of the hybrid transmit precoders (HTPCs) and reflective elements of a millimeter wave (mmWave) integrated sensing and communication (ISAC) system is considered. The system also incorporates a reconfigurable intelligent surface (RIS) relying on a non-diagonal RIS (NDRIS) phase...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Open Journal of the Communications Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11012749/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849469079835901952 |
|---|---|
| author | Jitendra Singh Aditya K. Jagannatham Lajos Hanzo |
| author_facet | Jitendra Singh Aditya K. Jagannatham Lajos Hanzo |
| author_sort | Jitendra Singh |
| collection | DOAJ |
| description | The joint optimization of the hybrid transmit precoders (HTPCs) and reflective elements of a millimeter wave (mmWave) integrated sensing and communication (ISAC) system is considered. The system also incorporates a reconfigurable intelligent surface (RIS) relying on a non-diagonal RIS (NDRIS) phase shift matrix. Specifically, we consider a hybrid architecture at the ISAC base station (BS) that serves multiple downlink communication users (CUs) via the reflected links from the RIS, while concurrently detecting multiple radar targets (RTs). We formulate an optimization problem that aims for maximizing the geometric mean (GM) rate of the CUs, subject to the sensing requirement for each RT. Additional specifications related to the limited transmit power and unit modulus (UM) constraints for both the HTPCs and the reflective elements of the NDRIS phase shift matrix make the problem challenging. To solve this problem, we first transform the intractable GM rate expression to a tractable weighted sum rate objective and next split the transformed problem into sub-problems. Consequently, we propose an iterative alternating optimization approach that leverages the majorization-minimization (MM) framework and block coordinate descent (BCD) method to solve each sub-problem. Furthermore, to tackle the UM constraints in the sub-problem of the HTPC design, we propose a penalty-based Riemannian manifold optimization (PRMO) algorithm, which optimizes the HTPCs on the Riemannian manifold. Similarly, the phases of the reflective elements of the NDRIS are optimized by employing the Riemannian manifold, and the locations of the non-zero entries of the NDRIS phase shift matrix are obtained by the maximal ratio combining (MRC) criterion. Finally, we present our simulation results, which show that deploying an NDRIS achieves additional gains for the CUs over a conventional RIS, further enhancing both the communication efficiency and sensing reliability. Furthermore, we compare the results to the pertinent benchmarks, which validate the effectiveness of our proposed algorithms. |
| format | Article |
| id | doaj-art-d3ef1caaecf34b7493e6a2b98a0475c8 |
| institution | Kabale University |
| issn | 2644-125X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Communications Society |
| spelling | doaj-art-d3ef1caaecf34b7493e6a2b98a0475c82025-08-20T03:25:38ZengIEEEIEEE Open Journal of the Communications Society2644-125X2025-01-0164756477110.1109/OJCOMS.2025.357319611012749Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift MatrixJitendra Singh0https://orcid.org/0000-0002-0951-4097Aditya K. Jagannatham1https://orcid.org/0000-0003-1594-5181Lajos Hanzo2https://orcid.org/0000-0002-2636-5214Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, IndiaDepartment of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, IndiaSchool of Electronics and Computer Science, University of Southampton, Southampton, U.K.The joint optimization of the hybrid transmit precoders (HTPCs) and reflective elements of a millimeter wave (mmWave) integrated sensing and communication (ISAC) system is considered. The system also incorporates a reconfigurable intelligent surface (RIS) relying on a non-diagonal RIS (NDRIS) phase shift matrix. Specifically, we consider a hybrid architecture at the ISAC base station (BS) that serves multiple downlink communication users (CUs) via the reflected links from the RIS, while concurrently detecting multiple radar targets (RTs). We formulate an optimization problem that aims for maximizing the geometric mean (GM) rate of the CUs, subject to the sensing requirement for each RT. Additional specifications related to the limited transmit power and unit modulus (UM) constraints for both the HTPCs and the reflective elements of the NDRIS phase shift matrix make the problem challenging. To solve this problem, we first transform the intractable GM rate expression to a tractable weighted sum rate objective and next split the transformed problem into sub-problems. Consequently, we propose an iterative alternating optimization approach that leverages the majorization-minimization (MM) framework and block coordinate descent (BCD) method to solve each sub-problem. Furthermore, to tackle the UM constraints in the sub-problem of the HTPC design, we propose a penalty-based Riemannian manifold optimization (PRMO) algorithm, which optimizes the HTPCs on the Riemannian manifold. Similarly, the phases of the reflective elements of the NDRIS are optimized by employing the Riemannian manifold, and the locations of the non-zero entries of the NDRIS phase shift matrix are obtained by the maximal ratio combining (MRC) criterion. Finally, we present our simulation results, which show that deploying an NDRIS achieves additional gains for the CUs over a conventional RIS, further enhancing both the communication efficiency and sensing reliability. Furthermore, we compare the results to the pertinent benchmarks, which validate the effectiveness of our proposed algorithms.https://ieeexplore.ieee.org/document/11012749/Reconfigurable intelligent surfaceintegrated sensing and communicationmillimeter waveand geometric mean rate |
| spellingShingle | Jitendra Singh Aditya K. Jagannatham Lajos Hanzo Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix IEEE Open Journal of the Communications Society Reconfigurable intelligent surface integrated sensing and communication millimeter wave and geometric mean rate |
| title | Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix |
| title_full | Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix |
| title_fullStr | Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix |
| title_full_unstemmed | Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix |
| title_short | Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix |
| title_sort | geometric mean rate maximization in ris aided mmwave isac systems relying on a non diagonal phase shift matrix |
| topic | Reconfigurable intelligent surface integrated sensing and communication millimeter wave and geometric mean rate |
| url | https://ieeexplore.ieee.org/document/11012749/ |
| work_keys_str_mv | AT jitendrasingh geometricmeanratemaximizationinrisaidedmmwaveisacsystemsrelyingonanondiagonalphaseshiftmatrix AT adityakjagannatham geometricmeanratemaximizationinrisaidedmmwaveisacsystemsrelyingonanondiagonalphaseshiftmatrix AT lajoshanzo geometricmeanratemaximizationinrisaidedmmwaveisacsystemsrelyingonanondiagonalphaseshiftmatrix |