Quantized Constant-Envelope Waveform Design for Massive MIMO DFRC Systems

TL;DR

This paper introduces a novel waveform design for massive MIMO dual-functional radar-communication systems using quantized constant-envelope constraints, optimizing performance while ensuring hardware efficiency.

Contribution

It proposes an inexact augmented Lagrangian algorithm with a block successive upper-bound minimization for efficient waveform design under QCE constraints.

Findings

The proposed method outperforms existing algorithms in simulation.

It effectively balances radar and communication performance.

The approach is computationally efficient due to closed-form updates.

Abstract

Both dual-functional radar-communication (DFRC) and massive multiple-input multiple-output (MIMO) have been recognized as enabling technologies for 6G wireless networks. This paper considers the advanced waveform design for hardware-efficient massive MIMO DFRC systems. Specifically, the transmit waveform is imposed with the quantized constant-envelope (QCE) constraint, which facilitates the employment of low-resolution digital-to-analog converters (DACs) and power-efficient amplifiers. The waveform design problem is formulated as the minimization of the mean square error (MSE) between the designed and desired beampatterns subject to the constructive interference (CI)-based communication quality of service (QoS) constraints and the QCE constraint. To solve the formulated problem, we first utilize the penalty technique to transform the discrete problem into an equivalent continuous penalty model. Then, we propose an inexact augmented Lagrangian method (ALM) algorithm for solving the penalty model. In particular, the ALM subproblem at each iteration is solved by a custom-built block successive upper-bound minimization (BSUM) algorithm, which admits closed-form updates, making the proposed inexact ALM algorithm computationally efficient. Simulation results demonstrate the superiority of the proposed approach over existing state-of-the-art ones. In addition, extensive simulations are conducted to examine the impact of various system parameters on the trade-off between communication and radar performances.