Joint Frame Structure and Beamwidth Optimization for Integrated Localization and Communication

In next-generation wireless networks, the integration of localization and communications techniques are regarded as a paradigmatic shift for enhancing spectrum and hardware utilizations. The channel sensing, encompassing localization and channel estimation, plays a pivotal role in various aspects such as beamforming, precoding and high-quality data transmission. In this paper, we present a method for optimizing the frame structure in the localization and communication integration system, to reveal the intricate relationship among channel estimation, user's localization and communication throughput in terms of the spectral efficiency (SE). Specifically, we initially derive the error bounds for channel estimation and location prediction in dynamic point-to-point communication scenario. Leveraging these bounds, we optimize the sensing and communication duration together with beamwidth design, to maximize the SE while ensuring communication requirements. An efficient iterative algorithm is employed to tackle this non-convex problem. Numerical results demonstrate that our proposed method can achieve a nearoptimal SE performance with significantly lower complexity compared to exhaustive search method. Furthermore, our results underscore the critical role of localization in optimizing sensing and communication durations for SE, particularly in high dynamic scenarios.