Off-Grid Blind Near-Field Integrated Sensing and Communication: Algorithm Design and Lower Bound

YUAN Zhengdao; GUO Qinghua; HUANG Chongwen; GAO Dawei; MEI Fengtong; LIAO Guisheng

doi:10.11999/JEIT260404

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YUAN Zhengdao, GUO Qinghua, HUANG Chongwen, GAO Dawei, MEI Fengtong, LIAO Guisheng. Off-Grid Blind Near-Field Integrated Sensing and Communication: Algorithm Design and Lower Bound[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260404

Citation:

YUAN Zhengdao, GUO Qinghua, HUANG Chongwen, GAO Dawei, MEI Fengtong, LIAO Guisheng. Off-Grid Blind Near-Field Integrated Sensing and Communication: Algorithm Design and Lower Bound[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260404

Citation:

YUAN Zhengdao, GUO Qinghua, HUANG Chongwen, GAO Dawei, MEI Fengtong, LIAO Guisheng. Off-Grid Blind Near-Field Integrated Sensing and Communication: Algorithm Design and Lower Bound[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260404

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Off-Grid Blind Near-Field Integrated Sensing and Communication: Algorithm Design and Lower Bound

doi: 10.11999/JEIT260404 cstr: 32379.14.JEIT260404

1.
School of Information Engineering, Henan Open University, Zhengzhou, Henan 450008, China
2.
University of Wollongong, Wollongong, NSW 2522, Australia
3.
College of Information Science , Zhejiang University, Hangzhou 310027, China
4.
Hangzhou Institute of Technology, Xidian University, Hangzhou, 311200, China

Funds: National Natural Science Foundation of China(62301394, 62331023, 62394292), Science and Technology Research Project of Henan (262102211109), China National Key R and D Program (2021YFA1000500, 2023YFB2904804)

Received Date: 2026-04-05
Accepted Date: 2026-06-17
Rev Recd Date: 2026-06-17

Available Online: 2026-06-23

Abstract

Abstract

Objective With the widespread deployment of extra-large scale antenna arrays in 6G networks, user terminals are mostly located in the near-field region. Existing near-field integrated sensing and communication (NF-ISAC) algorithms face critical challenges including off-grid power leakage, severe model mismatch, and strong dependence on pilot signals, which cannot meet the requirements of 6G low-overhead and high-performance transmission. This paper aims to design a novel off-grid blind NF-ISAC algorithm, and derive the theoretical performance bound for near-field sensing. Methods To overcome the inherent limitations of analytical geometric steering vectors and accommodate more accurate electromagnetic propagation characteristics without closed-form expressions. First, an amplitude-phase separation method is proposed to decompose the nonlinear near-field steering vector into amplitude and phase terms, which enables high-precision characterization of the steering vector with a single-hidden-layer neural network. Second, the NF-ISAC problem is formulated as a constrained matrix factorization problem, and the corresponding factor graph model is constructed. The trained neural network is embedded into the factor graph as a function node, and the penetration calculation of the neural network is realized via message passing algorithm, to complete joint blind coordinate sensing, channel estimation and signal detection without pilot assistance. Finally, the Cramér-Rao Lower Bound (CRLB) for multi-user near-field joint distance and angle sensing in polar coordinates is derived based on the neural network-fitted steering vector. Results and Discussions Extensive Monte Carlo simulations are conducted to evaluate the performance of the proposed algorithm. Simulation results show that the proposed algorithm achieves millimeter-level high-precision position sensing, and obtains significant performance improvements in both communication bit error rate (BER) and sensing accuracy compared with existing mainstream algorithms. It achieves 2～3dB performance gain in sensing accuracy over the state-of-the-art near-field off-grid method, and its performance is closest to the derived theoretical CRLB, which effectively mitigates off-grid power leakage and model mismatch. Conclusions The proposed off-grid blind NF-ISAC algorithm breaks through the pilot dependency and model mismatch limitations of existing NF-ISAC schemes, and realizes integrated high-precision sensing and reliable communication for near-field users in a pilot-free manner. The derived CRLB provides a theoretical benchmark for performance evaluation of near-field ISAC systems. This work can offer key technical support for the design of 6G near-field ISAC systems.
- Near-field communication,
- Integrated sensing and communication,
- Off-grid estimation algorithm,
- Blind signal detection,
- Factor graph.

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References(24)

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