Radar and Communication Co-existence: an Overview (1902.08676v1)

Abstract: Increased amounts of bandwidth are required to guarantee both high-quality/high-rate wireless services (4G and 5G) and reliable sensing capabilities such as automotive radar, air traffic control, earth geophysical monitoring and security applications. Therefore, co-existence between radar and communication systems using overlapping bandwidths has been a primary investigation field in recent years. Various signal processing techniques such as interference mitigation, pre-coding or spatial separation, and waveform design allow both radar and communications to share the spectrum. This article reviews recent work on co-existence between radar and communication systems, including signal models, waveform design and signal processing techniques. Our goal is to survey contributions in this area in order to provide a primary starting point for new researchers interested in these problems.

• The paper demonstrates that advanced interference mitigation strategies, including radar- and communication-centric approaches, significantly improve spectral sharing performance.
• It categorizes co-existence methods and employs techniques like convex optimization, atomic norm minimization, and sub-Nyquist sensing to manage interference.
• The study highlights practical implications for autonomous driving and smart networks by integrating adaptive signal processing in dynamic electromagnetic environments.

Co-existence of Radar and Communication Systems: Technical Insights and Analysis

The paper "Radar and Communication Co-existence: an Overview" synthesizes contemporary research on the concurrent operation of radar and communication systems within the same frequency spectrum. Ensuring the harmonious functioning of these systems is critical as they compete for bandwidth owing to the rising demand for high-quality wireless services and advanced sensing applications like automotive radar and air traffic control.

Overview of Co-existence Approaches

This paper categorizes co-existence strategies into three primary architectures:

1. Co-existence in Spectral Overlap: This involves both radar and communication systems using the same frequency spectrum. Here, the main challenge lies in mitigating interference to maintain the satisfactory performance of both systems. A radar-centric approach within this category focuses on optimizing radar signals to minimize interference to communication receivers, leveraging knowledge of potential interference bands. Conversely, communication-centric approaches adapt the communication system to handle interference from radars, utilizing techniques like atomic norm minimization to suppress radar interference without prior knowledge of its parameters.
2. Co-existence via Cognition: Cognition-based methods aim to dynamically allocate spectral resources through environmental sensing and learning techniques. Cognitive systems exploit frameworks like sub-Nyquist sampling to detect occupied frequency bands, thus ensuring that radar systems operate in vacant parts of the spectrum. The SpeCX system exemplifies this approach by integrating sub-Nyquist communication sensing and radar operation to achieve optimal spectral sharing.
3. Functional Co-existence: This strategy integrates radar and communication functionalities within the same system, either embedding communication signals into radar waveforms or utilizing communication waveforms for radar purposes. Approaches such as Dual Function Radar Communication (DFRC) systems and passive radar exploit these functionalities to ensure effective operation without explicit spectrum negotiation.

Theoretical Implications

The synthesis of these strategies elucidates several critical theoretical considerations for optimizing co-existence:

• The complexity of radar signal and communication waveform design mandates advanced techniques, such as convex optimization and alternating maximization, to satisfy performance constraints under interference.
• A thorough understanding of channel state information (CSI) and interference modeling plays a crucial role in improving the SINR of radar systems and ensuring communication quality.
• Cognitive radar necessitates the development of sophisticated environment sensing technologies capable of operating at low sampling rates without compromising on resolution or reliability.

Practical Implications and Future Prospects

Practically, the convergence of radar and communication systems promises improved computational efficiency and network performance. Current research initiatives prioritize adaptive and robust designs to cope with dynamic electromagnetic environments. These designs will be instrumental in addressing the requirements of emerging applications such as autonomous driving and smart sensing networks.

Future developments may include further integration of artificial intelligence to refine cognitive sensing mechanisms and enable real-time adaptability. Furthermore, the expansion of mmWave technologies signifies broader spectrum opportunities, albeit necessitating comprehensive exploration of millimeter-wave propagation characteristics to enhance radar-communication synergies.

In summary, the co-existence of radar and communication systems presents a complex yet promising avenue of research. Balancing the intricate trade-offs inherent in these systems requires continued innovation in signal processing techniques and algorithmic strategies to fulfill the evolving demands of modern wireless technology.