Target Localization Using Quantized Observations in Delay-Sensitive Networks

Precise target localization is pivotal in beyond 5G and 6G networks, particularly in location-aware vertical applications. In this letter, we investigate the performance limits for target localization using quantized observations via Fisher information analysis. To account for data transmission delays between agents and the fusion center, we derive the posterior Cramér-Rao bound for target localization in delay-sensitive scenarios and unveil the bidirectional effects of bit-depth on localization accuracy. Then, a bit allocation algorithm is proposed to balance the limited communication resources over the network. Finally, the simulation results validate our theoretical analysis and the effectiveness of the proposed bit allocation algorithm.