Technology Category
Search and Optimization: Mixed Discrete/Continuous SearchConstraint Satisfaction and Optimization: Mixed Discrete/Continuous OptimizationPlanning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
Multi-Objective Optimization for Joint Communication and Sensing in Multi-user MIMO Systems: Characterizing the Pareto Boundary
🤖 AI Summary
This work addresses the trade-off between communication and sensing performance in multi-user MIMO joint communication and sensing (JCAS) systems. It proposes a joint beamforming design that balances mutual information (for communication) and Fisher information (for sensing) via multi-objective optimization, under a scenario where a base station simultaneously serves multiple users and senses a single target. The study establishes the Pareto boundary of this system for the first time, demonstrating the superiority of joint design over separate optimizations, and includes an analytical characterization for the single-user case under equivalent isotropically radiated power (EIRP) constraints. Leveraging uplink–downlink duality, the solution is efficiently obtained through a combination of Lagrangian optimization, block coordinate ascent, line search, and projected gradient descent. Numerical results validate the optimality of the proposed scheme and systematically reveal the impacts of antenna count, number of users, and EIRP limitations on the Pareto boundary.
Technology Category
Application Category
📝 Abstract
This paper investigates the Pareto boundary performance of a joint communication and sensing (JCAS) system that addresses both sensing and communication functions at the same time. In this scenario, a multiple-antenna base station (BS) transmits information to multiple single-antenna communication users while concurrently estimating the parameters of a single sensing object using the echo signal. We present an integrated beamforming approach for JCAS in a multi-user multiple-input and multiple-output (MIMO) system. The performance measures for communication and sensing are Fisher information (FI) and mutual information (MI). Our research considers two scenarios: multiple communication users with a single sensing object and a single communication user with a single sensing object. We formulate a multi-objective optimization problem to maximize the weighted sum of MI and FI, subject to a total transmit power budget for both cases. As a particular case, we address the equivalent isotropic radiated power (EIRP) for the single communication user scenario. We use the uplink-downlink duality for the multi-user case to simplify the problem and apply Lagrangian optimization and line search methods with a block-coordinate ascending technique. We use projected gradient descent (PGD) to solve the optimization problem in the single-user case. Our numerical results demonstrate that joint beamforming is optimal for the multi-user JCAS system, as opposed to independent beamforming for each user and the sensing object. Furthermore, we reveal the Pareto boundary for the multi-user case, with variations in the number of communication users and the number of transmitting and receiving antennas. We provide the Pareto boundary depending on EIRP limitations for the single-user case.
Problem
Research questions and friction points this paper is trying to address.
Joint Communication and Sensing
Multi-Objective Optimization
Pareto Boundary
Multi-user MIMO
Beamforming
Innovation
Methods, ideas, or system contributions that make the work stand out.
Joint Communication and Sensing (JCAS)
Multi-objective Optimization
Pareto Boundary
Integrated Beamforming
Fisher Information
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