Rapid Connectivity in Low-Altitude Wireless Networks: Sensing-Assisted Closed-Form Solution

The application of integrated sensing and communication (ISAC) technology to address the ever-growing application demands of low-altitude wireless networks (LAWNs) has become a key milestone for the deployment of next-generation wireless systems. Affected by three-dimensional (3D) high-mobility of low-altitude platforms, conventional ISAC methods are confronted with the severe issues on real-time beam adjustment. Existing beam adjustment approaches for LAWNs mainly rely on black-box iterative or artificial intelligence-based algorithms, where the resultant beam misalignment caused by processing latency would substantially degrade the communication performance and pose obstacles to the rapid connectivity of LAWNs. To this end, we propose a closed-form solution for sensing-assisted LAWNs (SA-LAWNs) to guide the real-time system configuration for frequency/temporal/spatial division schemes, and efficiently adjust the 3D beam to achieve the near-optimal communication rate. Firstly, we introduce a closed-form 3D position and velocity joint estimation methodology for single base station, where angular velocity is directly measured according to Doppler Difference among array elements. Next, all estimated parameters are utilized to adjust antenna steering matrix to achieve beam focusing/alignment for near/far-field cases, and we hence derive the statistical models together with the closed-form expressions of beam gain and communication capacity. Then, we approximately calculate the closed-form optimized point suggesting sensing resources in frequency/temporal/spatial-division schemes. Finally, Monte Carlo simulations indicate that our proposed closed form optimization methodology achieves above 97% of the communication rate compared to global optimal solution.