Task-Based Quantizer Design for Sensing With Random Signals (2403.11187v1)
Abstract: In integrated sensing and communication (ISAC) systems, random signaling is used to convey useful information as well as sense the environment. Such randomness poses challenges in various components in sensing signal processing. In this paper, we investigate quantizer design for sensing in ISAC systems. Unlike quantizers for channel estimation in massive multiple-input-multiple-out (MIMO) communication systems, sensing in ISAC systems needs to deal with random nonorthogonal transmitted signals rather than a fixed orthogonal pilot. Considering sensing performance and hardware implementation, we focus on task-based hardware-limited quantization with spatial analog combining. We propose two strategies of quantizer optimization, i.e., data-dependent (DD) and data-independent (DI). The former achieves optimized sensing performance with high implementation overhead. To reduce hardware complexity, the latter optimizes the quantizer with respect to the random signal from a stochastic perspective. We derive the optimal quantizers for both strategies and formulate an algorithm based on sample average approximation (SAA) to solve the optimization in the DI strategy. Numerical results show that the optimized quantizers outperform digital-only quantizers in terms of sensing performance. Additionally, the DI strategy, despite its lower computational complexity compared to the DD strategy, achieves near-optimal sensing performance.
- F. Liu, Y. Cui, C. Masouros, J. Xu, T. X. Han, Y. C. Eldar, and S. Buzzi, “Integrated sensing and communications: Toward dual-functional wireless networks for 6g and beyond,” IEEE J. Sel. Areas Commun., vol. 40, no. 6, pp. 1728–1767, 2022.
- Z. Gao, Z. Wan, D. Zheng, S. Tan, C. Masouros, D. W. K. Ng, and S. Chen, “Integrated sensing and communication with mmWave massive MIMO: A compressed sampling perspective,” IEEE Trans. Wireless Commun., vol. 22, no. 3, pp. 1745–1762, 2022.
- S. Lu, F. Liu, F. Dong, Y. Xiong, J. Xu, Y.-F. Liu, and S. Jin, “Random ISAC signals deserve dedicated precoding,” arXiv preprint arXiv:2311.01822, 2023.
- J. A. Zhang, F. Liu, C. Masouros, R. W. Heath, Z. Feng, L. Zheng, and A. Petropulu, “An overview of signal processing techniques for joint communication and radar sensing,” IEEE J. Sel. Topics Signal Process., vol. 15, no. 6, pp. 1295–1315, 2021.
- Q. Xie, C. Liu, Z. Mo, and W. Li, “A novel pulse-agile waveform design based on random FM waveforms for range sidelobe suppression and range ambiguity mitigation,” IEEE Trans. Geosci. Remote Sensing, vol. 61, pp. 1–12, 2023.
- R. M. Gray and D. L. Neuhoff, “Quantization,” IEEE Trans. Inf. Theory, vol. 44, no. 6, pp. 2325–2383, 1998.
- N. Shlezinger, Y. C. Eldar, and M. R. Rodrigues, “Asymptotic task-based quantization with application to massive MIMO,” IEEE Trans. Signal Process., vol. 67, no. 15, pp. 3995–4012, 2019.
- D. Ma, N. Shlezinger, T. Huang, Y. Liu, and Y. C. Eldar, “Bit constrained communication receivers in joint radar communications systems,” in 2021 IEEE Int. Conf. Acoust. Speech Signal Process. IEEE, 2021, pp. 8243–8247.
- N. Shlezinger, Y. C. Eldar, and M. R. Rodrigues, “Hardware-limited task-based quantization,” IEEE Trans. Signal Process., vol. 67, no. 20, pp. 5223–5238, 2019.
- W. Weichselberger, M. Herdin, H. Ozcelik, and E. Bonek, “A stochastic MIMO channel model with joint correlation of both link ends,” IEEE Trans. Wireless Commun., vol. 5, no. 1, pp. 90–100, 2006.
- J.-P. Kermoal, L. Schumacher, K. I. Pedersen, P. E. Mogensen, and F. Frederiksen, “A stochastic MIMO radio channel model with experimental validation,” IEEE J. Sel. Areas Commun., vol. 20, no. 6, pp. 1211–1226, 2002.
- R. Gray and T. Stockham, “Dithered quantizers,” IEEE Trans. Inf. Theory, vol. 39, no. 3, pp. 805–812, 1993.
- B. Widrow, I. Kollar, and M.-C. Liu, “Statistical theory of quantization,” IEEE Trans. Instrum. Meas., vol. 45, no. 2, pp. 353–361, 1996.
- S. Kim, R. Pasupathy, and S. G. Henderson, “A guide to sample average approximation,” Handbook of Simulation Optimization, pp. 207–243, 2015.