Multistatic Cloud Radar Systems: Joint Sensing and Communication Design

TL;DR

This paper proposes a joint optimization framework for sensing and communication in multistatic cloud radar systems, improving detection performance by integrating waveform design with backhaul transmission strategies.

Contribution

It introduces a unified approach to optimize both radar waveforms and backhaul communication, considering different backhaul architectures and transmission strategies.

Findings

Joint optimization enhances detection accuracy over separate designs.

Proposed algorithms outperform conventional methods in simulations.

Different backhaul strategies impact system performance and design.

Abstract

In a multistatic cloud radar system, receive sensors measure signals sent by a transmit element and reflected from a target and possibly clutter, in the presence of interference and noise. The receive sensors communicate over non-ideal backhaul links with a fusion center, or cloud processor, where the presence or absence of the target is determined. The backhaul architecture can be characterized either by an orthogonal-access channel or by a non-orthogonal multiple-access channel. Two backhaul transmission strategies are considered, namely compress-and-forward (CF), which is well suited for the orthogonal-access backhaul, and amplify-and-forward (AF), which leverages the superposition property of the non-orthogonal multiple-access channel. In this paper, the joint optimization of the sensing and backhaul communication functions of the cloud radar system is studied. Specifically, the transmitted waveform is jointly optimized with backhaul quantization in the case of CF backhaul transmission and with the amplifying gains of the sensors for the AF backhaul strategy. In both cases, the information-theoretic criterion of the Bhattacharyya distance is adopted as a metric for the detection performance. Algorithmic solutions based on successive convex approximation are developed under different assumptions on the available channel state information (CSI). Numerical results demonstrate that the proposed schemes outperform conventional solutions that perform separate optimizations of the waveform and backhaul operation, as well as the standard distributed detection approach.