Diagonal Pattern and Algorithm for Range-Velocity Estimation in ISAC Networks

A significant characteristic of railway scenarios is that, when trains pass by base stations (BSs), a considerable volume of traffic is generated by a large number of onboard passengers within a short period. This situation imposes significant challenges on the time-frequency resource allocation and computational capabilities of BSs. Additionally, with the advent of 6G Integrated Sensing and Communications, BSs are required to transmit sensing signals to effectively monitor trains and their surrounding environment, further exacerbating the resource scarcity. This paper presents a novel diagonal pattern along with its corresponding 1D-DFT algorithm for range-velocity estimation. Simulation results demonstrate that the diagonal pattern and algorithm outperform existing gridtype patterns and conventional 2D-DFT algorithms in several key metrics, including sensing signal overhead, computational complexity, and resolution. This makes them particularly suitable for environments with stringent performance requirements, such as railway scenarios.