Integrated Sensing and Communication based on Non-Orthogonal Resource Allocation
Aqib, Muhammad (2025)
2025
Sähkötekniikan DI-ohjelma - Master's Programme in Electrical Engineering
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
Hyväksymispäivämäärä
2025-12-19
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-2025121811954
https://urn.fi/URN:NBN:fi:tuni-2025121811954
Tiivistelmä
This thesis presents an Integrated Sensing and Communication (ISAC) system that combines Non-Orthogonal Multiple Access (NOMA)-based Orthogonal Frequency Division Multiplexing (OFDM) communication with stepped frequency modulated waveform using triangular sweeps. The proposed framework enables simultaneous high data transmission of two users and precise range and velocity estimation of two targets using a shared spectrum-efficient waveform.
User signals are multiplexed using power-domain NOMA through superposition coding, then modulated onto OFDM subcarriers and transmitted over stepped radio frequency (RF) which sweeps triangularly. The proposed composite waveform supports dual functionality of communication and sensing. The communication receiver employs Successive Interference Cancellation (SIC) to separate and decode the individual user streams, while radar processing extracts delay and Doppler frequencies from received echoes using matched filtering to estimate target range and velocity. The symmetric nature of the triangular sweeps ensures consistent sensing performance during both up and down sweeps.
The integration of communication and radar sensing functions over shared hardware and spectral resources is successfully demonstrated in MATLAB. The proposed ISAC framework achieves sub-meter level sensing accuracy, operating near the Cramér-Rao Bound limits for range and velocity estimation, while concurrently supporting communication with a significantly improved Bit Error Rate (BER) at 30dB via MMSE and ZF channel equalization methods. These findings underscore the system's effectiveness and its potential for efficient coexistence in applications such as vehicular networks and autonomous systems.
User signals are multiplexed using power-domain NOMA through superposition coding, then modulated onto OFDM subcarriers and transmitted over stepped radio frequency (RF) which sweeps triangularly. The proposed composite waveform supports dual functionality of communication and sensing. The communication receiver employs Successive Interference Cancellation (SIC) to separate and decode the individual user streams, while radar processing extracts delay and Doppler frequencies from received echoes using matched filtering to estimate target range and velocity. The symmetric nature of the triangular sweeps ensures consistent sensing performance during both up and down sweeps.
The integration of communication and radar sensing functions over shared hardware and spectral resources is successfully demonstrated in MATLAB. The proposed ISAC framework achieves sub-meter level sensing accuracy, operating near the Cramér-Rao Bound limits for range and velocity estimation, while concurrently supporting communication with a significantly improved Bit Error Rate (BER) at 30dB via MMSE and ZF channel equalization methods. These findings underscore the system's effectiveness and its potential for efficient coexistence in applications such as vehicular networks and autonomous systems.