面向通感一体化的FBMC-OTFS波形设计

华坤义; 宋晨; 梁伟; 代领军

doi:10.11999/JEIT260845

面向通感一体化的FBMC-OTFS波形设计

doi: 10.11999/JEIT260845 cstr: 32379.14.JEIT260845

华坤义^{1, 2, 3,},
宋晨^{1, 2, 3, ,},
梁伟^{1, 2, 3},
代领军⁴

1.
微波成像全国重点实验室北京 100094
2.
中国科学院空天信息创新研究院北京 100094
3.
中国科学院大学电子电气与通信工程学院北京 100049
4.
西安电子科技大学杭州研究院杭州 311231

详细信息

作者简介:
华坤义：男，硕士生，研究方向为感一体化等。邮箱：　1789923190@qq.com

宋晨：男，博士，副研究员研究方向为低空目标探测处理技术等。邮箱：　songchen@aircas.ac.cn

梁伟：男，博士，副研究员研究方向为目标探测与识别技术

代领军：男，博士生，研究方向为雷达通信一体化信号处理

通讯作者:
宋晨　songchen@aircas.ac.cn

中图分类号: TN911.7
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出版历程
- 收稿日期: 2026-06-22
- 修回日期: 2026-10-11
- 录用日期: 2026-10-15
- 网络出版日期: 2026-10-22

FBMC-OTFS Waveform Design for Integrated Sensing and Communications

HUA Kunyi^{1, 2, 3
,},
SONG Chen^{1, 2, 3
, ,},
LIANG Wei^{1, 2, 3},
DAI Lingjun⁴

1.
National Key Laboratory of Microwave Imaging Technology, Beijing 100094, China
2.
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
3.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
4.
Hangzhou Institute of Technology, Xidian University, Hangzhou 311231, China

摘要

摘要: 随着6G技术的发展，通感一体化(ISAC)技术逐渐被广泛关注和研究，在这个领域中，正交时频空(OTFS)信号由于优秀的抗时变特性而具有很大的应用潜力。然而，OTFS易受分数时延和多普勒频移的影响，二者会产生弥散效应，造成通信数据和雷达导频的相互干扰；并且，在目标检测中，强目标的旁瓣可能会淹没弱目标，降低雷达检测概率和信道估计准确度。本文结合多载波滤波器组(FBMC)的低旁瓣特性，提出了一种FBMC-OTFS波形设计方法，并建立了包含分数时延和分数多普勒的信道模型。多载波滤波器组的原型滤波器可以有效降低OTFS波形的多普勒旁瓣，缓解多普勒弥散效应。在分数时延和多普勒频移联合信道模型上，结合恒虚警率(CFAR)算法实现对信道的估计，并通过最大比合并(MRC)算法优化信道估计结果。仿真结果表明，在强弱目标功率差为18.5 dB时，FBMC-OTFS波形仍可实现弱目标的有效检测，而传统OTFS波形无法检测；在信噪比为20 dB且检测到全部目标时，系统误码率显著低于传统OTFS波形。外场实验的结果进一步验证了FBMC-OTFS波形在实际ISAC场景中的可行性与优越性。
- 通感一体化 /
- 多载波滤波器组 /
- 正交时频空信号 /
- 无线通信 /
- 雷达感知
Abstract: Objective With the continuous advancement of 6G and integrated sensing and communication (ISAC) technologies, wireless communications are progressively moving towards high-mobility scenarios. In such environments, traditional orthogonal frequency division multiplexing (OFDM) signals are susceptible to Doppler shifts, which compromise the orthogonality of subcarriers and introduce inter-carrier interference, thereby degrading communication performance. OTFS signals, constructed on a discrete delay-Doppler two-dimensional grid, exhibit robust resilience to time-varying channels because each symbol experiences nearly the same channel effect during transmission. However, the limited delay and Doppler resolutions of OTFS waveforms inevitably lead to fractional delays and fractional Doppler shifts in practical applications, which cause dispersion effects that impair both communication capabilities and target detection performance in ISAC systems. This paper aims to mitigate the dispersion effects in OTFS signals and enhance the stability and reliability of ISAC systems through waveform and signal processing design. Methods This paper employs a low-sidelobe prototype filter from the filter bank multicarrier (FBMC) family to modulate the OTFS signal. The prototype filter effectively suppresses Doppler sidelobes and mitigates Doppler dispersion effects, while introducing only marginal mainlobe widening compared with an OTFS waveform carrying the same number of data symbols. A guard interval is established between communication data symbols and radar pilots in the delay-Doppler domain to prevent mutual interference, thereby establishing the FBMC-OTFS signal model. In channel modeling, fractional delays and fractional Doppler shifts are jointly considered to accurately characterize the practical channel. Furthermore, drawing on the constant false alarm rate (CFAR) algorithm widely used in radar detection, channel estimation is performed for the FBMC-OTFS system in the delay-Doppler domain, improving target detection accuracy while reducing computational complexity. Finally, the maximum ratio combining (MRC) algorithm is applied to signal detection, iteratively eliminating inter-symbol interference to reduce the bit error rate. Results and Discussions This paper presents both simulation and field experiment results in multi-path channel scenarios, comparing the proposed FBMC-OTFS waveform with traditional OTFS waveforms. The results show that when the power difference between the strong and weak targets is 18.5 dB, the FBMC-OTFS signal can still detect the weaker target, whereas the OTFS waveform fails to do so. When both waveforms successfully detect all targets (at a 9 dB strong-to-weak target power difference), FBMC-OTFS achieves a significantly lower bit error rate (BER) than OTFS at an SNR of 20 dB. Moreover, the Doppler sidelobes of the FBMC-OTFS signal are nearly imperceptible, while those of the OTFS signal are distinctly visible: the peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) of FBMC-OTFS are reduced to −29.82 dB and −22.15 dB, respectively. This sidelobe suppression is achieved at the cost of a reduced spectral efficiency, which is approximately one eighth of that of conventional OTFS. Field experiments further validate the feasibility of the FBMC-OTFS waveform in practical ISAC scenarios. Conclusions This paper proposes an FBMC-OTFS waveform tailored for ISAC applications, along with its corresponding signal processing methods. By modulating the OTFS waveform with the PHYDYAS prototype filter, the proposed approach effectively suppresses Doppler dispersion effects and mitigates the mutual interference between communication data and radar pilots, enabling reliable weak-target detection. The established channel model jointly accounts for fractional delays and fractional Doppler shifts. The CFAR algorithm, originally developed for radar detection, is applied to channel estimation, achieving robust path detection while reducing computational complexity, and is complemented by an MRC-based signal detector. Simulation and field experiments demonstrate that, compared with traditional OTFS, FBMC-OTFS significantly reduces Doppler sidelobes and can detect weak targets that OTFS fails to resolve, at the cost of a reduced spectral efficiency of about one eighth. The results provide a viable waveform solution for ISAC applications in 6G high-mobility scenarios.
- ISAC /
- FBMC /
- OTFS /
- wireless communication /
- radar sensing

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图 1 弥散效应及其影响

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图 2 PHYDYAS滤波器和矩形窗归一化频域响应

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图 3 FBMC-OTFS波形模型

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图 4 FBMC-OTFS波形的调制解调框图

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图 5 仿真与实验场景安排示意图

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图 6 强弱目标信噪比差值为18.5 dB/9 dB时OTFS波形与FBMC-OTFS波形目标检测和误码率曲线

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图 7 三种波形雷达回波对比图

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图 8 三种波形多普勒频移对比图

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图 9 外场实验示意图

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图 10 系统通信性能

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图 11 系统雷达性能

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表 1 频域下PHYDYAS滤波器的参数H_k取值

$ K $	$ {H}_{0} $	$ {H}_{1} $	$ {H}_{2} $	$ {H}_{3} $
2	1	$ \sqrt{2}/2 $
3	1	0.9114	0.4114
4	1	0.9719	$ \sqrt{2}/2 $	0.2351

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1 MRC算法

输入：时延-时域估计数据初始值 $ {\hat{Z}}^{0}[m,n] $；信道响应估计值　$ {\hat{v}}_{m,l}(n) $；最大迭代次数 $ {i}_{\max } $
输出：时延-时域检测结果$ A[m,n] $
1：$ g[m,n]=\displaystyle\sum\nolimits_{l}\,\hat{v}_{m+l,l}^{†}(n){\hat{v}}_{m+l,l}(n) $
2：$ \Delta {Z}^{0}[m,n]=Z[m,n]-\displaystyle\sum\nolimits_{l}\,{\hat{v}}_{m,l}(n){\hat{Z}}^{0}[m-l,n] $
3：for $ i=1,i< {i}_{\max };i++,do $
4：　$ {f}^{i}[m,n]=\displaystyle\sum\nolimits_{l}\,\hat{v}_{m+l,l}^{*}(n)\Delta {Z}^{i-1}[m+l,n] $
5：　$ {\hat{Z}}^{i}[m,n]={\hat{Z}}^{i-1}[m,n]+\dfrac{{f}^{i}[m,n]}{g[m,n]} $
6：　$ \begin{array}{cc}\Delta {Z}^{i}\left[m+l,n\right]=\Delta {Z}^{i}\left[m+l,n\right]-\displaystyle\sum\nolimits_{l}\,{\hat{v}}_{m+l,l}\left(n\right)\\\left({\hat{Z}}^{i}\left[m,n\right]-{\hat{Z}}^{i-1}\left[m,n\right]\right)\end{array} $
7：　if $ \Delta {Z}^{i}[m,n]\geq \Delta {Z}^{i-1}[m,n] $ then
8：　　break
9：　end if
10：end for
11：$ A[m,n]={\hat{Z}}^{i}[m,n] $

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表 2 仿真参数设置

参数名称	取值
Matlab版本	R2024a
载波频率	6 GHz
子载波间隔	30 KHz
FBMC-OTFS符号数$ N $	64
OTFS符号数$ N $	256
子载波数$ M $	512
MRC算法迭代次数	8
路径/目标时延抽头	[1.0, 4.3, 4.3]
路径/目标多普勒抽头	[0.0, 1.2, 9.2]
路径/目标增益	[0.6, 1.0, 0.35]

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表 3 系统通信性能仿真结果

目标信噪比差	波形	弱目标	BER (SNR=20 dB)
18.5 dB	OTFS	未检出	-
	FBMC-OTFS	检出	0.0010
9 dB	OTFS	检出	0.0741
	FBMC-OTFS	检出	0.0092

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表 4 系统雷达性能仿真结果

波形	峰值旁瓣比	积分旁瓣比	3 dB主瓣宽度
FBMC-OTFS波形 ($ N $=64)	–29.82 dB	–22.15 dB	3.93×1/(256$ T $)
OTFS波形($ N $=64)	–12.76 dB	–9.57 dB	3.61×1/(256$ T $)
OTFS波形($ N $=256)	–13.77 dB	–10.79 dB	0.91×1/(256$ T $)

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表 5 外场实验参数设置

参数名称	取值
载波频率$ {f}_{c} $	6 GHz
子载波间隔$ \Delta f $	30 KHz
符号持续时间$ T $	33.3 us
带宽$ B $	30.72 MHz
符号数$ N $	512
子载波数$ M $	1024
MRC算法迭代次数	8

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