Massive MIMO Joint Communications and Sensing with MRT Beamforming
Nguyen, Nhan T.; Nguyen, V. Dinh; Nguyen, Hieu V.; Ngo, Hien Q.; Swindlehurst, A. L.; Juntti, Markku (2024-06-13)
IEEE
13.06.2024
N. T. Nguyen, V. . -D. Nguyen, H. V. Nguyen, H. Q. Ngo, A. L. Swindlehurst and M. Juntti, "Massive MIMO Joint Communications and Sensing with MRT Beamforming," 2024 IEEE Radar Conference (RadarConf24), Denver, CO, USA, 2024, pp. 1-6, doi: 10.1109/RadarConf2458775.2024.10549340
https://rightsstatements.org/vocab/InC/1.0/
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202409175895
https://urn.fi/URN:NBN:fi:oulu-202409175895
Tiivistelmä
Abstract
Joint communications and sensing (JCAS) is en-visioned as a key feature in future wireless communications networks. In massive MIMO-JCAS systems, the very large number of antennas causes excessively high computational complexity in beamforming designs. In this work, we investigate a low-complexity massive multiple-input-multiple-output (MIMO)-JCAS system employing the maximum-ratio transmission (MRT) scheme for both communications and sensing. We first derive closed-form expressions for the achievable communications rate and Cramer-Rao bound (CRB) as functions of the large-scale fading channel coefficients. Then, we develop a power allocation strategy based on successive convex approximation to maximize the communications sum rate while guaranteeing the CRB con-straint and transmit power budget. Our analysis shows that the introduction of sensing functionality increases the beamforming uncertainty and inter-user interference on the communications side. However, these factors can be mitigated by deploying a very large number of antennas. The numerical results verify our findings and demonstrate the power allocation efficiency.
Joint communications and sensing (JCAS) is en-visioned as a key feature in future wireless communications networks. In massive MIMO-JCAS systems, the very large number of antennas causes excessively high computational complexity in beamforming designs. In this work, we investigate a low-complexity massive multiple-input-multiple-output (MIMO)-JCAS system employing the maximum-ratio transmission (MRT) scheme for both communications and sensing. We first derive closed-form expressions for the achievable communications rate and Cramer-Rao bound (CRB) as functions of the large-scale fading channel coefficients. Then, we develop a power allocation strategy based on successive convex approximation to maximize the communications sum rate while guaranteeing the CRB con-straint and transmit power budget. Our analysis shows that the introduction of sensing functionality increases the beamforming uncertainty and inter-user interference on the communications side. However, these factors can be mitigated by deploying a very large number of antennas. The numerical results verify our findings and demonstrate the power allocation efficiency.
Kokoelmat
- Avoin saatavuus [34589]