# Toward Intelligent Roads: Uniting Sensing and Communication in Mobile Networks
## 3 Cooperative Data Fusion in JSC Network for Vehicular Scenarios
### Resource Allocation Strategies  
The sensing and communication capabilities of the BSs are ensured through shared resources between the two functionalities, including frequency division, time division, power division via a multibeam radiation pattern, and higher-level BSs selection. Since these two functionalities have contrasting requirements and performance metrics, ensuring proper resource allocation between them is critical. Assessing the sensing capability in a multitarget scenario, such as the one depicted in Figure 4, involves several metrics: missed detections, false alarms, and the localization error of detected targets. A good way to summarize performance into a single criterion is to use the optimal sub-pattern assignment (OSPA) metric, which incorporates the localization accuracy, detection rate, and false alarm rate into one measure. When no false alarms or missed detections are present (i.e., the number of detected targets equals the true number), the OSPA can be interpreted as the average root mean squared error (RMSE) of the position estimation [36]. Conversely, false alarms and missed detections introduce a penalty term, increasing the OSPA distance and reflecting degraded performance as errors accumulate. For the communication capability, the aggregate capacity--defined in [18] as the downlink sum rate of each BS--can be considered. Another important aspect is the network overhead caused by inter-BS cooperation, which requires data exchange via backhaul to the FC; this is an issue that the research community has only recently begun investigating. Figure 5 shows the sensing/communication trade-off for a MIMO-OFDM system based on 5G NR numerology, where multiple monostatic BSs cooperate to detect and locate the vehicles and pedestrians in the urban scenario. Table 1 summarizes the main parameters of the waveform adopted and the vehicular scenario. Based on the different types of analysis of the JSC system, the following can be observed:  
* _Impact of power division:_ The fraction of power allocated for sensing when the system operates in a multibeam configuration is denoted as \(\rho_{\rm P}\). At low values of \(\rho_{\rm P}\), localization performance deteriorates due to the difficulty in detecting weak targets, such as pedestrians. Conversely, reducing \(\rho_{\rm P}\) enhances communication performance by increasing the available power. In this challenging scenario, the MBM filter outperforms the PHD filter. * _Impact of frequency division:_ Frequency division is achieved by allocating a fraction, \(\rho_{\rm f}\), of subcarriers for sensing. The choice of subcarrier allocation is crucial for sensing, as the range estimation resolution is highly dependent on signal bandwidth; generally, the larger the bandwidth, the higher the resolution. A small \(\rho_{\rm f}\) may result in target blurring and diminished localization capabilities. Conversely, reducing \(\rho_{\rm f}\) allocates more resources to communication, thereby increasing capacity. * _Impact of time division:_ Continuous scanning of the environment by the BSs may result in significant resource allocation for sensing, which is not always necessary. To conserve communication resources, the refresh rate of range-angle maps can be reduced by a factor D, leading to a fraction of time allocated for sensing, which is denoted as \(\rho_{\rm t}=1/\rm D\). When \(\rho_{\rm t}\) is small, the sensing performance declines due to the tracking system's limited ability to predict target motion accurately. Conversely, reducing \(\rho_{\rm t}\) increases communication capacity, as more time resources become available for this functionality. In this context, a key interesting feature of target classification is to adapt \(\rho_{\rm t}\) based on the target type; for instance, a pedestrian who moves at low speed can be tracked effectively with a \(\rho_{\rm t}=0.1\), while a car needs \(\rho_{\rm t}=0.5\), hence implicating more time resources. * _Cooperation gain:_ The number of cooperating BSs significantly affects sensing performance.