Multi-User and Multi-Target Constant Waveform Design of Dual-Function Radar and Communication System
-
摘要: 双功能雷达通信一体化系统可以使硬件和频谱资源得到有效利用，是解决当前无线频谱资源紧张问题的一种有效途径。该文针对同时多目标探测与多用户通信场景，以雷达接收回波的信干噪比(SINR)为指标保障雷达的探测性能，采用通信多用户干扰(MUI)作为通信指标保证通信传输性能。与此同时，为保证发射端功率放大器工作在饱和区域，增加了波形恒模的约束条件。该文通过对波形以及滤波器的联合优化，提出了一种在满足通信MUI功率一定的情况下，最大化雷达多目标探测回波最小信干噪比(SINR)的波形设计优化模型。针对此优化问题，采用了交替迭代优化的方法来求解此问题。仿真结果表明，所设计的波形在多目标探测以及多用户通信场景下，通过调整通信MUI功率门限，可以在保证通信MUI功率性能前提下，实现对多目标回波最小SINR的优化。Abstract: The Dual-Functional Radar-Communication (DFRC) system can effectively utilize hardware and spectrum resources, which is an effective way to solve the shortage of the wireless spectrum resource. In this paper, for the scenario of simultaneous multi-target detection and multi-user communication, the Signal-to-Interference-Noise Ratio (SINR) of the radar received echo is used as an index to guarantee the detection performance, and the Multi-User Interference (MUI) of the communication is used as a communication index to guarantee the transmission performance of communication. Meanwhile, constraints on the constant modulus of the waveform are added to ensure that the power amplifier at the transmitter operates in the saturation region. The paper proposes a mathematical model for waveform design that maximizes the minimum SINR of the radar multi-target echoes while satisfying a certain amount of the communication MUI energy by jointly optimizing the waveforms as well as the filters. For this optimization problem, the method of alternating iterative optimization is adopted to solve the problem. Simulation results show that the designed waveform ensures both radar and communication related performance in simultaneous multi-target detection and multi-user communication scenarios.
-
算法1 求解问题(21)算法流程 输入：初始化变量${{\boldsymbol{s}}^{(0)}}$, ${e^{(0)}}$, ${\beta ^{(0)}}$, ${\delta _s}$和$ {\delta _\beta } $。 输出：问题式(38)的解$s$； 第1步：$j = 0$； 第2步：${{\boldsymbol{s}}^{(j - 1)}}{\text{ = }}{{\boldsymbol{s}}^{(0)}},\;{e^{(j - 1)}}{\text{ = }}{e^{(0)}}$； 第3步：求解问题式(38)得到$ ({{\boldsymbol{s}}^{(j)}},{e^{(j)}},{\beta ^{(j)}}) $； 第4步：若${\left\| {{\beta ^{(j)}}} \right\|_1} < \tau $，则输出$ {\boldsymbol{s}} = {{\boldsymbol{s}}^{(j)}} $，否则继续下一步 第5步：${{\boldsymbol{s}}^{(0)}}{\text{ = }}{{\boldsymbol{s}}^{(j)}},\;{e^{(0)}}{\text{ = }}{e^{(j)}},\;j{\text{ = }}j + 1$返回第2步 
下载: 导出CSV
算法2 交替迭代优化算法流程 输入：初始化变量${s^{(0)}}$, ${e^{(0)}}$, ${\beta ^{(0)}}$, ${\delta _s}$, $ {\delta _\beta } $和$\kappa $。 输出：问题式(16)的解${s^{(*)}}$,$\left\{ {{\boldsymbol{w}}_m^*} \right\}_{m = 1}^M$。 第1步：$c = 0$，构$ {{\chi }_m}\left( {{{\boldsymbol{s}}^{(0)}}} \right) $, $ {{\boldsymbol{\varLambda}} _m}\left( {{{\boldsymbol{s}}^{(0)}}} \right) $； 第2步：求解问题式(19)得到$\left\{ {{\boldsymbol{w}}_m^{(0)}} \right\}_{m = 1}^M$； 第3步：$c = c + 1$； 第4步：构造$ {{{\boldsymbol{\varOmega}} }_m}\left( {{\boldsymbol{w}}_m^{(c - 1)}} \right) $, $ {{\boldsymbol{\varGamma}}_m}\left( {{\boldsymbol{w}}_m^{(c - 1)}} \right) $，求解问题式(21)
得到${{\boldsymbol{s}}^{(c)}}$；第5步：构造$ {{\chi }_m}\left( {{{\boldsymbol{s}}^{(c)}}} \right) $, $ {{\boldsymbol{\varLambda}} _m}\left( {{{\boldsymbol{s}}^{(c)}}} \right) $ ，求解问题式(19)，得到
$\left\{ {{\boldsymbol{w}}_m^{(c)}} \right\}_{m = 1}^M$第6步：计算${\min _{\forall m}}{\text{SIN}}{{\text{R}}_m}\left( {{\boldsymbol{s}},{{\boldsymbol{w}}_m}} \right)$ 若$ |\min _{_{\forall m}}^j{{{\mathrm{SINR}}} _m}\left( {{{\boldsymbol{s}}^{(c)}},{\boldsymbol{w}}_m^{(c)}} \right) - \min _{_{\forall m}}^{(c - 1)}{{{\mathrm{SINR}}} _m}$
$\left( {{{\boldsymbol{s}}^{({c} - 1)}},{\boldsymbol{w}}_m^{(c - 1)}} \right)|{\text{ }} < {\text{ }}\kappa $，输出${s^{(*)}}$=${s^{(c)}}$, $\left\{ {{\boldsymbol{w}}_m^*} \right\}_{m = 1}^M = \left\{ {{\boldsymbol{w}}_m^{(c)}} \right\}_{m = 1}^M$，否则返回第3步。
下载: 导出CSV
-
[1] LIU Rang, LI Ming, LIU Qian, et al. Dual-functional radar-communication waveform design: A symbol-level precoding approach[J]. IEEE Journal of Selected Topics in Signal Processing, 2021, 15(6): 1316–1331. doi: 10.1109/JSTSP.2021.3111438 [2] LIU Fan, CUI Yuanhao, MASOUROS C, et al. Integrated sensing and communications: Toward dual-functional wireless networks for 6G and beyond[J]. IEEE Journal on Selected Areas in Communications, 2022, 40(6): 1728–1767. doi: 10.1109/JSAC.2022.3156632 [3] KENNEY J B. Dedicated short-range communications (DSRC) standards in the United States[J]. Proceedings of the IEEE, 2011, 99(7): 1162–1182. doi: 10.1109/JPROC.2011.2132790 [4] KUMARI P, CHOI J, GONZALEZ-PRELCIC N, et al. IEEE 802.11ad-based radar: An approach to joint vehicular communication-radar system[J]. IEEE Transactions on Vehicular Technology, 2018, 67(4): 3012–3027. doi: 10.1109/TVT.2017.2774762 [5] WYMEERSCH H, SECO-GRANADOS G, DESTINO G, et al. 5G mmWave positioning for vehicular networks[J]. IEEE Wireless Communications, 2017, 24(6): 80–86. doi: 10.1109/MWC.2017.1600374 [6] GROSSI E, LOPS M, VENTURINO L, et al. Opportunistic Radar in IEEE 802.11ad networks[J]. IEEE Transactions on Signal Processing, 2018, 66(9): 2441–2454. doi: 10.1109/TSP.2018.2813300 [7] HAN Liang and WU Ke. Joint wireless communication and radar sensing systems – state of the art and future prospects[J]. IET Microwaves, Antennas & Propagation, 2013, 7(11): 876–885. doi: 10.1049/iet-map.2012.0450. [8] SHI Chenguang, WANG Fei, SELLATHURAI M, et al. Power minimization-based robust OFDM Radar waveform design for radar and communication systems in coexistence[J]. IEEE Transactions on Signal Processing, 2018, 66(5): 1316–1330. doi: 10.1109/TSP.2017.2770086 [9] SADDIK G N, SINGH R S, and BROWN E R. Ultra-wideband multifunctional communications/radar system[J]. IEEE Transactions on Microwave Theory and Techniques, 2007, 55(7): 1431–1437. doi: 10.1109/TMTT.2007.900343 [10] 杨慧婷, 周宇, 谷亚彬, 等. 参数调制多载波雷达通信共享信号设计[J]. 雷达学报, 2019, 8(1): 54–63. doi: 10.12000/JR18001YANG Huiting, ZHOU Yu, GU Yabin, et al. Design of integrated radar and communication signal based on multicarrier parameter modulation signal[J]. Journal of Radars, 2019, 8(1): 54–63. doi: 10.12000/JR18001 [11] BHAT S S, NARAYANAN R M, and RANGASWAMY M. Bandwidth sharing and scan scheduling in multimodal radar with communications and tracking[J]. IETE Journal of Research, 2013, 59(5): 551–562. doi: 10.4103/0377-2063.123761 [12] TEMIZ M, ALSUSA E, and BAIDAS M W. A dual-functional massive MIMO OFDM communication and radar transmitter architecture[J]. IEEE Transactions on Vehicular Technology, 2020, 69(12): 14974–14988. doi: 10.1109/TVT.2020.3031686 [13] LIU Fan, MASOUROS C, LI Ang, et al. MU-MIMO communications with MIMO Radar: From Co-existence to joint transmission[J]. IEEE Transactions on Wireless Communications, 2018, 17(4): 2755–2770. doi: 10.1109/TWC.2018.2803045 [14] MA Dingyou, SHLEZINGER N, HUANG Tianyao, et al. Spatial modulation for joint radar-communications systems: Design, analysis, and hardware prototype[J]. IEEE Transactions on Vehicular Technology, 2021, 70(3): 2283–2298. doi: 10.1109/TVT.2021.3056408 [15] 石长安, 刘一民, 王希勤, 等. 基于帕累托最优的雷达-通信共享孔径研究[J]. 电子与信息学报, 2016, 38(9): 2351–2357. doi: 10.11999/JEIT151377SHI Chang’an, LIU Yimin, WANG Xiqin, et al. Optimal allocation of shared aperture in Radar-communication integrated system based on Pareto optimality[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2351–2357. doi: 10.11999/JEIT151377 [16] 单成兆, 马永奎, 赵洪林, 等. 基于时间调制阵列的多波束雷达通信一体化结构及算法研究[J]. 信号处理, 2020, 36(10): 1644–1653. doi: 10.16798/j.issn.1003-0530.2020.10.003SHAN Chengzhao, MA Yongkui, ZHAO Honglin, et al. Structure and algorithm of time-modulated array based multi-beam Radar-communications integration[J]. Journal of Signal Processing, 2020, 36(10): 1644–1653. doi: 10.16798/j.issn.1003-0530.2020.10.003 [17] HASSANIEN A, AMIN M G, ZHANG Y D, et al. Dual-function radar-communications: Information embedding using sidelobe control and waveform diversity[J]. IEEE Transactions on Signal Processing, 2016, 64(8): 2168–2181. doi: 10.1109/TSP.2015.2505667 [18] LIU Fan, ZHOU Longfei, MASOUROS C, et al. Toward dual-functional radar-communication systems: Optimal waveform design[J]. IEEE Transactions on Signal Processing, 2018, 66(16): 4264–4279. doi: 10.1109/TSP.2018.2847648 [19] LIU Xiang, HUANG Tianyao, SHLEZINGER N, et al. Joint transmit beamforming for multiuser MIMO communications and MIMO Radar[J]. IEEE Transactions on Signal Processing, 2020, 68: 3929–3944. doi: 10.1109/TSP.2020.3004739 [20] TIAN Tuanwei, ZHANG Tianxian, KONG Lingjiang, et al. Transmit/receive beamforming for MIMO-OFDM based dual-function radar and communication[J]. IEEE Transactions on Vehicular Technology, 2021, 70(5): 4693–4708. doi: 10.1109/TVT.2021.3072094 [21] SHI Chenguang, WANG Yijie, WANG Fei, et al. Joint optimization scheme for subcarrier selection and power allocation in multicarrier dual-function radar-communication system[J]. IEEE Systems Journal, 2021, 15(1): 947–958. doi: 10.1109/JSYST.2020.2984637 [22] ZHONG Kai, HU Jinfeng, PAN Cunhua, et al. Joint waveform and beamforming design for RIS-aided ISAC systems[J]. IEEE Signal Processing Letters, 2023, 30: 165–169. doi: 10.1109/LSP.2023.3242554 [23] MOHAMMED S K and LARSSON E G. Per-antenna constant envelope precoding for large multi-user MIMO systems[J]. IEEE Transactions on Communications, 2013, 61(3): 1059–1071. doi: 10.1109/TCOMM.2013.012913.110827 [24] YU Xianxiang, ALHUJAILI K, CUI Guolong, et al. MIMO Radar waveform design in the presence of multiple targets and practical constraints[J]. IEEE Transactions on Signal Processing, 2020, 68: 1974–1989. doi: 10.1109/TSP.2020.2979602 -
图(4) / 表(2)
计量
- 文章访问数: 871
- HTML全文浏览量: 310
- PDF下载量: 361
- 被引次数: 0
下载:
