Gao, Zhen;
Wan, Ziwei;
Zheng, Dezhi;
Tan, Shufeng;
Masouros, Christos;
Ng, Derrick Wing Kwan;
Chen, Sheng;
(2022)
Integrated Sensing and Communication with mmWave Massive MIMO: A Compressed Sampling Perspective.
IEEE Transactions on Wireless Communications
10.1109/twc.2022.3206614.
(In press).
Preview |
PDF
Integrated_Sensing_and_Communication_with_mmWave_Massive_MIMO_A_Compressed_Sampling_Perspective.pdf - Accepted Version Download (3MB) | Preview |
Abstract
Integrated sensing and communication (ISAC) has opened up numerous game-changing opportunities for realizing future wireless systems. In this paper, we propose an ISAC processing framework relying on millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Specifically, we provide a compressed sampling (CS) perspective to facilitate ISAC processing, which can not only recover the high-dimensional channel state information or/and radar imaging information, but also significantly reduce pilot overhead. First, an energy-efficient widely spaced array (WSA) architecture is tailored for the radar receiver, which enhances the angular resolution of radar sensing at the cost of angular ambiguity. Then, we propose an ISAC frame structure for time-varying ISAC systems considering different timescales. The pilot waveforms are judiciously designed by taking into account both CS theories and hardware constraints induced by hybrid beamforming (HBF) architecture. Next, we design the dedicated dictionary for WSA that serves as a building block for formulating the ISAC processing as sparse signal recovery problems. The orthogonal matching pursuit with support refinement (OMP-SR) algorithm is proposed to effectively solve the problems in the existence of the angular ambiguity. We also provide a framework for estimating the Doppler frequencies during payload data transmission to guarantee communication performances. Simulation results demonstrate the good performances of both communications and radar sensing under the proposed ISAC framework.
| Type: | Article |
|---|---|
| Title: | Integrated Sensing and Communication with mmWave Massive MIMO: A Compressed Sampling Perspective |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/twc.2022.3206614 |
| Publisher version: | https://doi.org/10.1109/twc.2022.3206614 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Radar, Sensors, Radar imaging, Millimeter wave communication, Radar antennas, Array signal processing, Wireless communication |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10156875 |
Archive Staff Only
 |
View Item |
