# Optimal Resource Allocation for Joint Sensing and Communication: Multiple Targets and Clutters

## TL;DR

This paper investigates optimal power allocation in a joint sensing and communication system using RF signals, focusing on multiple targets and clutter, and proposes an iterative algorithm to minimize total power consumption.

## Contribution

It introduces a novel approach for joint resource allocation in RF-based target probing with multiple sensors and targets, addressing non-convex optimization challenges.

## Key findings

- MRT is optimal at low SINR levels.
- ZF outperforms MRC at high SINR.
- Proposed iterative algorithm effectively minimizes power.

## Abstract

We study a contactless target probing based on stimulation by a radio frequency (RF) signal. The transmit signal is dispatched from a transmitter equipped with a two-dimensional antenna array. Then, the reflected signal from the targets are received at multiple distributed sensors. The observation at the sensors are amplified and forwarded to the fusion center. Afterwards, the fusion center performs space-time post processing to extract the maximum common information between the received signal and the targets impulse responses. Optimal power allocation at the transmitter and amplification at the sensors is investigated. The sum-power minimization problem turns out to be a non-convex problem. We propose an efficient algorithm to solve this problem iteratively. By exploiting maximum-ratio transmission (MRT), maximum-ratio combining (MRC) of space-time received signal vector is the optimal receiver at sufficiently low signal-to-interference-plus-noise-ratio (SINR). However, zero-forcing (ZF) at the fusion center outperforms MRC at higher SINR demands.