# Toward Intelligent Roads: Uniting Sensing and Communication in Mobile Networks
## 1 Introduction
### Literature Overview  
While there has been extensive research dedicated to designing systems with high spectral efficiency and significantly improved performance from a communication perspective, there remain numerous unexplored aspects of JSC. For instance, while channel modeling in wireless communications has reached a mature stage, the same does not apply to sensing, which is often limited to simplified line-of-sight (LoS) models [5]. In [6; 7], the authors propose leveraging 5G new radio (NR) vehicle-to-everything (V2X) sidelink communication for localization, exploiting the near-field propagation characteristics of signals generated at high carrier frequencies and large antenna arrays to enhance accuracy, robustness, and latency. In [8], the feasibility of JSC within the IEEE 802.11 bd standard [9], an amendment to the IEEE 802.11 standard [10] designed to enhance V2X communications in challenging environments, was demonstrated. However, the impact of environmental factors, such as multipath effects, on sensing performance should also be evaluated. To make sensing an inherent network service, it is imperative to ensure its resolution meets the stringent requirements of emerging vehicular applications. Hence, a more descriptive model of the targets must be considered to represent real-world scenarios better when studying the requirements and performance of JSC systems [11; 12]. In [13; 14], a comprehensive method for jointly estimating channel and target parameters in multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) JSC systems was introduced, tackling a key challenge in the field. Although the method delivers precise estimates for channel parameters and point-like targets, its performance diminishes when handling a larger number of targets or extended target scenarios. Another crucial aspect is resource allocation, namely, assigning a portion of downlink or uplink resources to sensing tasks while ensuring that communication functions still satisfy quality-of-service (QoS) constraints. Although numerous studies have explored subcarrier and power allocation strategies that assign distinct subcarriers to sensing and communication tasks [15; 16]--achieving significant gains in detection accuracy and communication capacity--it remains paramount to develop advanced resource allocation algorithms that consider contextual factors, such as specific QoS requirements and user equipment (UE) battery consumption [17]. This necessity further highlights the critical role of tracking in predicting the object positions, facilitating proactive and efficient network-wide resource allocation [18]. With the dense deployment of base stations (BSs) or transmission-reception points (TRPs) anticipated in future networks, there is immense potential to be unlocked through their cooperation when regarded as distributed sensors [19; 20]. However, this collaborative sensing framework remains largely unexplored, and its potential to enhance the localization and tracking of vehicles, pedestrians, and other objects is still under-investigated.