Constant Modulus Waveform Design with Space-Time Sidelobe Reduction for DFRC Systems

TL;DR

This paper proposes novel algorithms for designing constant modulus MIMO waveforms in DFRC systems, jointly optimizing beam patterns and ambiguity functions to improve target localization and resolution, while employing CI-based precoding for enhanced communication.

Contribution

It introduces two advanced solution algorithms based on MM and LADMM for efficient waveform design, with novel surrogates and low-complexity implementations for large MIMO systems.

Findings

Enhanced target detection and imaging performance.

Significant reduction in space-time sidelobes.

Faster convergence and computational efficiency of the proposed algorithms.

Abstract

Dual-function radar-communication (DFRC) is a key enabler of location-based services for next-generation communication systems. In this paper, we investigate the problem of designing constant modulus multiple-input multiple-output (MIMO) waveforms for DFRC systems. We jointly shape the spatial beam pattern and ambiguity function of the transmit space-time matrix to improve target localization accuracy and enhance target resolution in cluttered environments. For communications, we employ constructive interference (CI)-based precoding, which exploits multi-user and radar-induced interference to enhance MIMO symbol detection. We develop two novel solution algorithms based on majorization-minimization (MM) and the linearized alternating direction method of multipliers (LADMM) principles. For the MM approach, we introduce a novel diagonal majorizer for complex quadratic functions, yielding a tighter surrogate and faster convergence than standard largest eigenvalue-based surrogates. After majorization, we decompose the approximated problem into independent subproblems that can be efficiently solved via parallelizable coordinate descent. To accommodate large MIMO dimensions, we further develop a low-complexity LADMM solution. We combine a biconvex reformulation and first-order proximal approximations to handle the nonconvex quartic objective without requiring costly matrix inversions. We evaluate the performance of the proposed algorithms in comparison to the existing DFRC algorithm. Simulation results demonstrate that the proposed algorithms can substantially enhance target detection and imaging performance due to the reduction of space-time sidelobes.