- The paper derives performance bounds for coexisting radar and communications systems, demonstrating that cooperative signaling can enhance both target estimation and data throughput.
- It develops a joint estimation and information theoretic framework, employing techniques like water-filling to optimally allocate power across shared spectral bands.
- Numerical examples illustrate practical scenarios where radar-as-relay strategies enable mutual gains in estimation precision and communication capacity.
Cooperative Radar and Communications Signaling: An Analysis of Joint Performance Bounds
Introduction
The integration of radar and communications systems has been a critical area of exploration due to the limited spectral resources that are increasingly becoming constrained by the coexistence and interference between different systems. Typically, radar and communication systems view each other as sources of interference. However, this paper presents an approach where these systems work cooperatively, leveraging their coexistence to potentially enhance performance under certain theoretical conditions. The focus is on the radar-as-relay scenario using an innovative concept known as multiuser detection radar (MUDR).
Contributions
The primary contribution of the paper involves the derivation of performance bounds for systems where radar and communication functions are coexistent. The approach explores limits on combined communication rates and estimation rates when a radar system also acts as a communication relay. The conventional paradigm assumes that radar's presence in the same spectral space as communication systems degrades performance; however, this paper presents cases where the integration can lead to improvements for both systems.
The joint radar-communications system operates similarly to a heterogenous multistatic radar or statistical MIMO radar network while simultaneously facilitating a heterogeneous communication network. This dual capability is contingent upon certain constraints explored within the paper that dictate the viability and efficacy of such integrative approaches.
Joint Estimation and Information Theoretic Framework
Central to the investigation is the development of a joint estimation and information theoretic framework that quantifies performance limits in terms of the communication and estimation rates. Drawing analogies from multiple-access channel theory, the paper delineates how power allocation, bandwidth separation, and receiver architecture impact the achievable performance bounds, under the premise that the radar can decode communications signals while estimating radar channels.
The formalism utilizes a comprehensive set of parameters that model the radar and communications channel. Performance bounds are derived by considering both the information rate achievable through estimation of radar parametric data (such as target delay) and the communication rate achievable in a shared spectrum environment.
Inner and Outer Bounds
The paper progresses by providing a theoretical exposition on achievable inner bounds and outer bounds of system performance. The outer bounds mirror the constraints experienced in communications multiple-access systems. The inner bounds provide a more realisable performance metric by considering achievable rates through different system setups, such as successive interference cancellation and water-filling approaches.
The inclusion of the water-filling technique demonstrates the optimal allocation of power across different frequency channels to maximize the combined radar and communications rate. This approach offers insight into how communication channels can be optimized even when joint estimation and communications usage complicates spectral management.
Analytical and Numerical Insights
Numerical examples presented in the paper underscore the theoretical developments with practical parameters. This includes assumptions of antenna gains, power levels, propagation characteristics, spectral bandwidths, and more. These examples visualise the benefits of integrating radar functions with communication relays, particularly when water-filling techniques are applied to the mixed-use spectral bands.
The analytical demonstrations support the theory that cooperative signaling can achieve a concurrent improvement in the estimation of radar parameters and the data rate of communications. The bounds derived, while optimistic and theory-driven in certain assumptions, illustrate a plausible power allocation strategy that benefits both radar sensing and communication throughput.
Implications and Future Directions
The implications of this research extend to advances in cognitive radar and radio environments where dynamic spectral sharing is a necessity rather than a choice. By manifesting a model where systems not only coexist but mutually benefit, the work suggests a pathway towards more efficient spectrum utilization, critical for contemporary and future wireless ecosystems. The approach lays foundational groundwork for further exploration into joint system designs that maximize the trade-offs between estimation accuracy and communication quality.
Future investigations might consider expanding the framework to incorporate practical system constraints, such as hardware limitations, real-world noise, and cost-benefit analyses of deploying such integrated systems. Further research could refine the bounds and perhaps develop adaptive algorithms that evolve based on real-time spectral conditions and performance feedback.
In conclusion, this paper makes a significant theoretical contribution to the field of joint radar and communications systems, presenting a balanced account of benefits, techniques, and hypothetical system improvements through cooperative approaches.