Road Traffic Density Estimation For Adaptive Beam Allocation in an ISAC Setup

In this paper, we propose and study a particular use case capable of performing radio-based traffic density estimation for adaptive beam allocation. The proposed scheme explores the synergy between communication and sensing from an Integrated sensing and communication (ISAC) perspective. The traffic den-sity estimation is aided by communication functionality, which involves reusing communication waveforms and utilizing multi-beam forming and sweeping techniques. Meanwhile, the sensing outcomes assist in proactively allocating radio beams. There have been accurate traffic monitoring methods relying on a large number of detectors. However, these traditional techniques have some shortcomings, and it is necessary to explore alternative traffic density estimation approaches. In this regard, we exploit orthogonal frequency division multiplexing (OFDM) communication signals of opportunity reflected from targets (vehicles) to estimate the traffic density of a road section by using Jensen-Shannon (JS) divergence and weighted-centroid interpolation based on a few samples of density scenarios. Then, we present a millimeter-wave (mmWave) adaptive beam allocation protocol based on the traffic density estimation to enhance communication coverage for the vehicular users in the area of interest. The simulation results demonstrate that our traffic density estimation can handle a wide range of targets with a relatively low estimation error. In addition, the analysis of the adaptive beam allocation shows that it effectively improves the quality of service (QoS, in terms of outage probability) of the communication system.