Abstract
To improve both sensing and communication performances, this paper proposes a coordinated multi-point (CoMP) transmission design for a dual-functional radar-communication (DFRC) system. In the proposed CoMP-DFRC system, the central processor (CP) coordinates multiple base stations (BSs) to transmit both the communication signal and the dedicated probing signal. The communication performance and the sensing performance are both evaluated by the signal-to-interference-plus-noise ratio (SINR). Given the limited backhaul capacity, we study the waveform and clustering design from both the radar-centric perspective and the communication-centric perspective. Dinkelbach's transform is adopted to handle the single-ratio fractional objective for the radar-centric problem. For the communication-centric problem, we adopt quadratic transform to convexitify the multi-ratio fractional objective. Then, the rank-one constraint of communication beamforming vector is relaxed by semidefinite relaxation (SDR), and the tightness of SDR is further proved to guarantee the optimal waveform design with fixed clustering. For dynamic clustering, equivalent continuous functions are used to represent the non-continuous clustering variables. Successive convex approximation (SCA) is further utilized to convexitify the equivalent functions. Simulation results are provided to verify the effectiveness of all proposed designs.
Original language | English (US) |
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Pages (from-to) | 1323-1335 |
Number of pages | 13 |
Journal | IEEE Transactions on Communications |
Volume | 71 |
Issue number | 3 |
DOIs | |
State | Published - Jan 11 2023 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2023-04-05Acknowledged KAUST grant number(s): ORA-2021-CRG10-4696
Acknowledgements: This research was supported by National Key RandD Program of China (Grant No. 2021YFB2900302), Joint Funds of the National Natural Science Foundation of China (Grant No. U21A20452), and King Abdullah University of Science and Technology Research Funding (KRF) under Award No. ORA-2021-CRG10-4696
This publication acknowledges KAUST support, but has no KAUST affiliated authors.