Radar And Communication Spectrum Sharing


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Radar and Communication Spectrum Sharing


Radar and Communication Spectrum Sharing

Author: Shannon D. Blunt

language: en

Publisher: SciTech Publishing

Release Date: 2018-11-01


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Radar and Communication Spectrum Sharing addresses the growing conflict over use of the radio-frequency spectrum by different systems, such as civil and security applications of radar and consumer use for wireless communications. The increasing demand for this finite resource is driving innovation into new ways in which these diverse systems can cohabit the spectrum. The book provides a broad survey of recent and ongoing work on the topic of spectrum sharing, with an emphasis on identifying the technology gaps for practical realization and the regulatory and measurement compliance aspects of this problem space. The introductory section sets the scene, making the case for spectrum access and reviewing spectrum use, congestion, lessons learned, ways forward and research areas. The book then covers system engineering perspectives, the issues involved with addressing interference, and radar/communication co-design strategies. With contributions from an international panel of experts, this book is essential reading for researchers, engineers and advanced students in radar, communications, navigation, and electronic warfare whose work is impacted by spectrum engineering requirements.

Spectrum Sharing Between Radars and Communication Systems


Spectrum Sharing Between Radars and Communication Systems

Author: Awais Khawar

language: en

Publisher: Springer

Release Date: 2017-06-12


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This book presents spectrum sharing efforts between cellular systems and radars. The book addresses coexistence algorithms for radar and communication systems. Topics include radar and cellular system models; spectrum sharing with small radar systems; spectrum sharing with large radar systems; radar spectrum sharing with coordinated multipoint systems (CoMP); and spectrum sharing with overlapped MIMO radars. The primary audience is the radar and wireless communication community, specifically people in industry, academia, and research whose focus is on spectrum sharing. The topics are of interest for both communication and signal processing technical groups. In addition, students can use MATLAB code to enhance their learning experience.

Strategies for Radar-Communication Spectrum Sharing


Strategies for Radar-Communication Spectrum Sharing

Author: Ammar Ahmed

language: en

Publisher:

Release Date: 2021


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Spectrum sharing has become increasingly important since the past decade due to the ongoing congestion of spectral resources. Higher data rates in wireless communications require expansion of existing frequency allocations. Significant research efforts have been made in the direction of cognitive radio to effectively manage the existing frequency usage. Recently, coexistence of multiple platforms within the same frequency bands is considered effective to mitigate spectral congestion. This requires both systems to work collaboratively to mitigate their mutual interference. This challenging problem can be significantly simplified if both systems are controlled by the same entity. Joint radar-communication (JRC) system is such an example where radar and communication system objectives are achieved by the same physical platform. In this dissertation, we consider three different types of JRC systems. These JRC systems respectively exploit a single transmit antenna, an antenna array for beamforming, and a distributed JRC network, and develop novel signal processing techniques to optimize the performance of these systems. Special attention is given to the resource optimization objectives and numerous resource allocation schemes are developed and investigated. First, we consider a single transmit antenna-based JRC system which exploits dual-purpose transmit orthogonal frequency division multiplexing (OFDM) waveforms to perform radar and communication objectives simultaneously. We optimize the power allocation of the OFDM subcarriers based on the frequency-sensitive target response and communication channel characteristics. For this purpose, we employ mutual information as the optimization metric. In the simulation examples considered for this system, we observed that the JRC system enjoys approximately 20\% improvement in the performance of communication subsystem with a mere 5\% reduction in radar subsystem performance. Second, we propose a quadratic amplitude modulation (QAM) based sidelobe modulation scheme for beamforming-based JRC systems which enhances the communication data rate by enabling a novel multiple access strategy. The main principle of this proposed strategy lies in enabling the beamformer to transmit signals with distinct amplitudes and phases in different directions. We also investigate optimal power allocation for such a spectrum sharing approach by employing a spatial power control-based beamforming approach. Furthermore, the robustness of these beamforming-based JRC systems is improved using chance constrained programming. In this context, we observe that the chance constrained optimization can be relaxed to form a deterministic and convex problem by employing the statistical profile of the communication channels. When dealing with JRC systems that are equipped with more antennas than the number of radio frequency chains, we perform the resource optimization in terms of minimized power usage and optimal selection of antennas resulting in an efficient utilization of hardware up-conversion chains. In the simulation examples considered for these schemes, we observe that, even with a reduction of nearly 30\% of the transmit antennas, the beamforming-based JRC system is able to perform the required radar and communication tasks without any disadvantage. Our last contribution is on a distributed JRC system, which is the first effort in this research direction, enabling spectrum sharing for networked radar systems coexisting with the communication systems. We devise a power allocation strategy for such a system by employing convex optimization techniques. In this strategy, the target localization error and the Shannon capacity are respectively considered as the optimization criteria for radar and communication systems. For the simulation example considered in this case, we observe that the proposed resource allocation strategy achieves a communication performance that was approximately 5 times greater than that achieved by the radar-only counterpart. Moreover, the target localization performance achieved by the JRC system using the proposed approach was approximately 4 times better than the performance achieved by the communication-only approach.