학술논문

Optimal Linear Precoder Design for MIMO-OFDM Integrated Sensing and Communications Based on Bayesian Cramér-Rao Bound
Document Type
Conference
Source
GLOBECOM 2023 - 2023 IEEE Global Communications Conference Global Communications Conference, GLOBECOM 2023 - 2023 IEEE. :1314-1319 Dec, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Engineering Profession
General Topics for Engineers
Power, Energy and Industry Applications
Signal Processing and Analysis
Parameter estimation
Simulation
Symbols
Sensors
Bayes methods
System analysis and design
Convergence
Integrated sensing and communications
MIMO-OFDM
Bayesian Cramér-Rao bound
Language
ISSN
2576-6813
Abstract
In this paper, we investigate the fundamental limits of MIMO-OFDM integrated sensing and communications (ISAC) systems based on a Bayesian Cramér-Rao bound (BCRB) analysis. We derive the BCRB for joint channel parameter estimation and data symbol detection, in which a performance trade-off between both functionalities is observed. We formulate the optimization problem for a linear precoder design and propose the stochastic Riemannian gradient descent (SRGD) approach to solve the non-convex problem. We analyze the optimality conditions and show that SRGD ensures convergence with high probability. The simulation results verify our analyses and also demonstrate a fast convergence speed. Finally, the performance trade-off is illustrated and investigated.