Performance optimization and parameters estimation for MIMO-OFDM dual-functional communication-radar systems

Zhong Chen , Lou Mengting , Gu Chunrong , Tang Lan , Bai Yechao

›› 2025, Vol. 11 ›› Issue (2) : 387 -400.

PDF
›› 2025, Vol. 11 ›› Issue (2) : 387 -400. DOI: 10.1016/j.dcan.2023.12.006
Original article

Performance optimization and parameters estimation for MIMO-OFDM dual-functional communication-radar systems

Author information +
History +
PDF

Abstract

Dual-function communication radar systems use common Radio Frequency (RF) signals are used for both communication and detection. For better compatibility with existing communication systems, we adopt Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals. First, we analyze the Cramer-Rao Lower Bound (CRLB) of parameter estimation. Then, the transmit powers over different subcarriers are optimized to achieve the best tradeoff between the transmission rate and the estimation performance. Finally, we propose a more accurate estimation method that uses Canonical Polyadic Decomposition (CPD) of the third-order tensor to obtain the parameter matrices. Due to the characteristic of the column structure of the parameter matrices, we only need to use DFT / IDFT to recover the parameters of multiple targets. The simulation results show that tensor-based estimation method can achieve a performance close to CRLB, and the estimation performance can be improved by optimizing the transmit powers.

Keywords

Bistatic dual-function communication-radar systems / MIMO-OFDM / CRLB / Power allocation / CPD

Cite this article

Download citation ▾
Zhong Chen, Lou Mengting, Gu Chunrong, Tang Lan, Bai Yechao. Performance optimization and parameters estimation for MIMO-OFDM dual-functional communication-radar systems. , 2025, 11(2): 387-400 DOI:10.1016/j.dcan.2023.12.006

登录浏览全文

4963

注册一个新账户 忘记密码

CRediT authorship contribution statement

Chen Zhong: Formal analysis, Writing - original draft, Writing - review & editing. Mengting Lou: Funding acquisition. Chunrong Gu: Software, Writing - original draft. Lan Tang: Conceptualization, Methodology, Project administration, Supervision, Writing - review & editing. Yechao Bai: Conceptualization.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

[1]

Y. Han, E. Ekici, H. Kremo, O. Altintas, Spectrum sharing methods for the coexis-tence of multiple rf systems: a survey, Ad Hoc Netw. 53 (2016) 53-78.

[2]

L. Han, K. Wu, Multifunctional transceiver for future intelligent transportation sys-tems, IEEE Trans. Microw. Theory Tech. 59 (7) (2011) 1879-1892.

[3]

P.M. McCormick, S.D. Blunt, J.G. Metcalf, Simultaneous radar and communications emissions from a common aperture, part I: theory, in: 2017 IEEE Radar Conference (RadarConf), 2017, pp. 1685-1690.

[4]

D. Ciuonzo, A.D. Maio, G. Foglia, M. Piezzo, Intrapulse radar-embedded communi-cations via multiobjective optimization, IEEE Trans. Aerosp. Electron. Syst. 51 (4) (2015) 2960-2974.

[5]

A. Hassanien, M.G. Amin, Y.D. Zhang, F. Ahmad, Dual-function radar-communications: information embedding using sidelobe control and waveform di-versity, IEEE Trans. Signal Process. 64 (8) (2016) 2168-2181.

[6]

X. Zhou, L. Tang, Y. Bai, Y.C. Liang, Performance analysis and waveform opti-mization of integrated fd-mimo radar-communication systems, IEEE Trans. Wirel. Commun. 20 (11) (2021) 7490-7502.

[7]

T. Zhang, X.G. Xia, Ofdm synthetic aperture radar imaging with sufficient cyclic prefix, IEEE Trans. Geosci. Remote Sens. 53 (1) (2015) 394-404.

[8]

Y. Liu, G. Liao, J. Xu, Z. Yang, Y. Zhang, Adaptive ofdm integrated radar and com-munications waveform design based on information theory, IEEE Commun. Lett. 21 (10) (2017) 2174-2177.

[9]

C. Shi, F. Wang, S. Salous, J. Zhou, Low probability of intercept-based optimal ofdm waveform design strategy for an integrated radar and communications system, IEEE Access 6 (2018) 57689-57699.

[10]

Y. Li, G.L. Stuber, Orthogonal Frequency Division Multiplexing for Wireless Com-munications, Springer-Verlag New York, Inc., 2006.

[11]

N. Levanon,Multifrequency radar signals, in: Radar Conference, 2000. The Record of the IEEE 2000 International, 2000, pp. 683-688.

[12]

G. Franken, H. Nikookar, P.V. Genderen,Doppler tolerance of ofdm-coded radar signals, in:2006 European Radar Conference, 2006, pp. 108-111.

[13]

C. Sturm, T. Zwick, W. Wiesbeck, An ofdm system concept for joint radar and com-munications operations, in: IEEE Vehicular Technology Conference, 2009, pp. 1-5.

[14]

C.R. Berger, B. Demissie, J. Heckenbach, P. Willett, S. Zhou, Signal processing for passive radar using ofdm waveforms, IEEE J. Sel. Top. Signal Process. 4 (1) (2010) 226-238.

[15]

Y. Liu, G. Liao, Y. Chen, J. Xu, Y. Yin, Super-resolution range and velocity estima-tions with ofdm integrated radar and communications waveform, IEEE Trans. Veh. Technol. 69 (10) (2020) 11659-11672.

[16]

C. Sturm, W. Wiesbeck, Waveform design and signal processing aspects for fusion of wireless communications and radar sensing, Proc. IEEE 99 (2011) 1236-1259.

[17]

J. Sanson, A. Gameiro, D. Castanheira,Comparison of doa algorithms for mimo ofdm radar, in:2018 15th European Radar Conference (EuRAD), 2018, pp. 226-229.

[18]

Y. Liu, G. Liao, Z. Yang,Range and angle estimation for mimo-ofdm integrated radar and communication systems, in:2016 CIE International Conference on Radar (RADAR), 2016, pp. 1-4.

[19]

P. Kumari, D.H.N. Nguyen, R.W. Heath, Performance trade-off in an adaptive ieee 802.11ad waveform design for a joint automotive radar and communication system, in: IEEE International Conference on Acoustics, 2017, pp. 4281-4285.

[20]

C. Shi, F. Wang, M. Sellathurai, J. Zhou, S. Salous, Power minimization based robust ofdm radar waveform design for radar and communication systems in coexistence, IEEE Trans. Signal Process. 66 (5) (2017) 1316-1330.

[21]

M. Temiz, E. Alsusa, M.W. Baidas, A dual-functional massive mimo ofdm communi-cation and radar transmitter architecture, IEEE Trans. Veh. Technol. 69 (12) (2020) 14974-14988.

[22]

F. Liu, C. Masouros, A. Li, H. Sun, L. Hanzo, Mu-mimo communications with mimo radar: from co-existence to joint transmission, IEEE Trans. Wirel. Commun. 17 (4) (2018) 2755-2770.

[23]

J. Li, P. Stoica, MIMO Radar Signal Processing, Wiley-IEEE Press, 2009.

[24]

T.A. Schonhoff, Detection and Estimation Theory and Its Applications, Prentice Hall, 2006.

[25]

H.Q. Ngo, Massive MIMO: Fundamentals and System Designs, Linkoping Uiv. Elec-tronic Press, Linkoping, Sweden, 2015.

[26]

M. Grant, S.P. Boyd, cvx: Matlab software for disciplined convex programming, 2016.

[27]

K.-Y. Wang, A.M.-C. So, T.-H. Chang, W.-K. Ma, C.-Y. Chi, Outage constrained robust transmit optimization for multiuser miso downlinks: tractable approximations by conic optimization, IEEE Trans. Signal Process. 62 (21) (2014) 5690-5705.

[28]

A. Ben-Tal, A. Nemirovski, Lectures on modern convex optimization (analysis, al-gorithms, and engineering applications)—back matter, 2001, pp. 485-488, https://dx.doi.org/10.1137/1.9780898718829.

[29]

N.D. Sidiropoulos, L. De Lathauwer, X. Fu, K. Huang, E.E. Papalexakis, C. Falout-sos, Tensor decomposition for signal processing and machine learning, IEEE Trans. Signal Process. 65 (13) (2017) 3551-3582.

[30]

J.B. Kruskal, Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics, Linear Algebra Appl. 18 (2) (1977) 95-138.

[31]

A. Stegeman, N.D. Sidiropoulos, On Kruskal’s uniqueness condition for the cande-comp/parafac decomposition, J. Causal Inference 420 (2015) 540-542.

[32]

N.D. Sidiropoulos, G.B. Giannakis, Blind parafac receivers for ds-cdma systems, IEEE Trans. Signal Process. 48 (3) (2000) 810-823.

[33]

S. Boyd, Convex Optimization, Cambridge University Press, 2004.

AI Summary AI Mindmap
PDF

469

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/