Interference Exploitation in ISAC Systems: Finite-Alphabet Precoding With Low Resolution DACs and PSs

In this paper, we investigate the precoding design for multi-input multi-output (MIMO) integrated sensing and communication (ISAC) systems based on the concept of exploiting constructive interference (CI). Considering low-resolution digital-to-analog converter (DAC) and low-resolution phase shifter (PS) as two efficient hardware options, we propose corresponding finite-alphabet precoding schemes. The formulated optimization problem aims at maximizing a weighted objective function consisting of two parts: the minimum CI scaling factor for communications and target illumination power for radar sensing. The cross-entropy optimization (CEO) framework is employed to effectively solve this discrete non-convex optimization problem. Moreover, an “indirect power scaling” method is proposed for the precoding design based on DAC quantization to enhance the ISAC performance. From the simulation results, we can observe that the proposed precoding schemes can achieve satisfactory ISAC performance with low complexity. In the considered ISAC systems, increasing the quantization bits for DAC and PS quantizations can improve the ISAC performance, and the gain for DAC quantization is more pronounced.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Wireless Communications
Published
2025-08-12
DOI
https://doi.org/10.1109/twc.2025.3595731
Citations
1
Primary Topic
Advanced Data Compression Techniques
Type
article
Field-Weighted Citation Impact
1.28

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Interference Exploitation in ISAC Systems: Finite-Alphabet Precoding With Low Resolution DACs and PSs

Kai‐Kit Wong, Christos Masouros, Yiran Wang, Ang Li et al.
1 citations
IEEE Transactions on Wireless Communications
Advanced Data Compression Techniques
1.28
article

Interference Exploitation in ISAC Systems: Finite-Alphabet Precoding With Low Resolution DACs and PSs

Kai‐Kit Wong, Christos Masouros, Yiran Wang, Ang Li, Kun Yang, Xiaoyan Hu
article en
1 citations

Abstract

In this paper, we investigate the precoding design for multi-input multi-output (MIMO) integrated sensing and communication (ISAC) systems based on the concept of exploiting constructive interference (CI). Considering low-resolution digital-to-analog converter (DAC) and low-resolution phase shifter (PS) as two efficient hardware options, we propose corresponding finite-alphabet precoding schemes. The formulated optimization problem aims at maximizing a weighted objective function consisting of two parts: the minimum CI scaling factor for communications and target illumination power for radar sensing. The cross-entropy optimization (CEO) framework is employed to effectively solve this discrete non-convex optimization problem. Moreover, an “indirect power scaling” method is proposed for the precoding design based on DAC quantization to enhance the ISAC performance. From the simulation results, we can observe that the proposed precoding schemes can achieve satisfactory ISAC performance with low complexity. In the considered ISAC systems, increasing the quantization bits for DAC and PS quantizations can improve the ISAC performance, and the gain for DAC quantization is more pronounced.

IEEE Transactions on Wireless CommunicationsVol. 25
Torrington Hospital (GB), University College London (GB), Xi'an Jiaotong University (CN), Nanjing University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 17%
Advanced Data Compression Techniques
1.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.