Localization in 6G Communication Networks Using Low Complex Time of Arrival (TOA) and Time Difference of Arrival (TDOA) Techniques

Optimal placement of sensor nodes is a challenging issue in localization applications because the Cramér-Rao lower bound (CRLB) of target nodes dependent on the sensor node geometry. Though there exists many localization algorithms and methods, localization using time of arrival (TOA) and time difference of arrival (TDOA) of wideband signals has potential features to support higher accuracy at lower complexity, these techniques become a promising choice for various applications including underwater communication, highly precise radar systems, and radio communication. However, multipath propagation (the combination of indirect path signals between target node and anchor nodes), lack of clock synchronization, computational complexity, high power consumption, interference, and noise pose major challenges that affect the localization accuracy. In this paper, a highly accurate and simplified versions of TOA, TDOA-based localization techniques are presented that suit the resource constraint applications of industrial internet of things (IIoT) and 6G communication systems. The proposed TOA, TDOA techniques are based on orthogonal frequency division multiplexing (OFDM) channel estimation that ensures reliable location estimations and is less susceptible to multipath effects. During TOA based location measurements, perfect synchronization is ensured between anchor nodes and target nodes. In case of TDOA based location measurements, though the target node is not synchronized with the anchor nodes still all the anchor nodes are synchronized. So, the synchronization error between the target node and all anchor nodes is the same. Therefore, the proposed TDOA measurements and the localization accuracy are independent of synchronization error. Simulations were conducted using fast Fourier transform (FFT) and MUSIC spectrum analysis methods at higher frequency bands under noisy environments and results are compared with the performance under ideal conditions. The results proved that both TOA and TDOA based localization values are very close to the corresponding ideal value conditions and immune to noisy environments. Overall, TDOA based localization outperforms TOA based localization technique.