Joint Optimization Scheme for Subcarrier Selection and Power Allocation in Multicarrier Dual-Function Radar-Communication System

Dual-function radar-communications (DFRC) system has been recognized as a promising solution to alleviate the radio frequency spectrum congestion and the shortage of spectrum resources. In this article, we address the problem of designing the joint subcarrier selection and power allocation scheme to minimize the power consumption of a DFRC system, under a general scenario in which the DFRC system is capable of performing a primary radar purpose and a secondary communications purpose in the meantime. In particular, the key mechanism is to minimize the total radiated power of the multicarrier DFRC system by jointly selecting the best possible subcarriers for radar and communications purposes in sequence and allocating the optimal power resource on the corresponding subcarriers, under the constraints of a predefined mutual information for target characterization and a desired communications data rate for information transmission. The resulting problem is formulated as a two-variable nonconvex optimization problem, one for subcarrier selection and the other for power allocation. Then, after convex relaxation reformulation and problem partition, an efficient three-step solution technique is developed for the joint optimization scheme, which combines the cyclic minimization algorithm and Karush-Kuhn-Tuckers optimality conditions. Finally, numerical results are provided to validate the theoretical findings and to verify the effectiveness of the proposed joint optimization scheme.

Automated summary

The article discusses the design of a joint subcarrier selection and power allocation scheme to minimize power consumption in a DFRC system capable of performing radar and communication purposes. A three-step solution technique is developed for the joint optimization scheme, combining cyclic minimization algorithm and Karush-Kuhn-Tuckers optimality conditions. Numerical results validate the theoretical findings and verify the effectiveness of the proposed joint optimization scheme.