Optimizing communication and sensing performance metrics in ISAC networks involves addressing various challenges and trade-offs to achieve a balance between the two functionalities. One of the primary challenges is the inherent trade-off between communication and sensing resource allocation. Allocating more resources to one function may come at the expense of the other, leading to a performance trade-off. For example, increasing the bandwidth for communication purposes may reduce the available bandwidth for sensing applications, impacting detection accuracy.
Another challenge is the complexity of jointly optimizing diverse metrics such as coverage probability, throughput, detection probability, and false alarm probability. These metrics may have conflicting requirements, making it challenging to find a single optimal solution that maximizes all performance aspects simultaneously. Trade-offs may need to be made based on the specific requirements of the ISAC application and the network environment.
Furthermore, the integration of communication and sensing functions introduces additional complexity in system design and protocol development. Ensuring seamless coordination between communication and sensing modules, managing interference between the two functions, and designing efficient protocols that cater to both requirements are key challenges in jointly optimizing performance metrics in ISAC networks.
Balancing energy efficiency, spectrum utilization, and hardware efficiency while optimizing communication and sensing performance metrics poses another set of trade-offs. Efficient resource management and algorithm design are essential to address these challenges and achieve optimal performance in ISAC networks.