OTFS-AIDED CELL-FREE MASSIVE MIMO ISAC SYSTEMS

Abstract

Considering the rapidly increasing number of cellular users, ensuring a high data rate and quality services in 5G networks is challenging. Cell-free massive multipleinput multiple-output (mMIMO) emerges as a prominent solution, where multiple wireless access points coordinate to serve multiple users efficiently.Orthogonal Time Frequency Space (OTFS) waveform is ideal for doubly-selective channels in high mobility environments, making it suitable for integrated sensing and communication (ISAC) designs. By co-locating antennas for radar and communication at base stations, both systems can use the same physical channel. Additionally, cell-free massive MIMO technology enables multi-static sensing of multiple targets within the environment, enhancing ISAC efficiency. This thesis proposes a OTFS aided cell-free ISAC mMIMO system in which there are U number of downlink UEs and a sensing target in it. In this study, we derive the closed-form expression for the Signal-to-Interference-plus-Noise Ratio (SINR) and compare the resulting Spectral Efficiency (SE) with the Ergodic Capacity for communication systems. To enhance communication performance, we employ two sets of precoders: Regularized Zero Forcing (RZF) for communication and Nullspace (NS) beamforming for sensing, comparing their performance against Maximal Ratio Transmitting (MRT) precoders. For the sensing aspect, we derive the closed-form Sensing Signal-to-Noise Ratio (SNR) to detect the presence of the target and the Cram´er-Rao Bound (CRB) for Direction of Arrival (DOA) estimation. Numerical simulations are conducted to verify these analytical results, confirming the effectiveness of the proposed methods. The comparison shows that RZF and NS beamforming significantly improve SE and sensing accuracy compared to MRT.