Abstract
Waveform design and spectrum sharing between Multiple Input Multiple Output (MIMO) radar and MIMO communication system is an optimization problem that has been typically addressed in literature with two-dimensional formalism involving radius and azimuth angles. In this paper, we address the problem and associated spectrum sharing constraints by the inclusion of an additional elevation angle. The design uses Finite Alphabet Constant Envelope (FACE) Binary Phase Shift Keying (BPSK) waveforms to formulate the covariance matrices. Through machine learning, a nonlinear optimization problem with constraints is converted to an optimization problem without constraints. The design criteria for the radar waveform does not interfere with the communication system. This is done by carefully selecting the base station (BS) and steering nulls towards it, which guarantees the least degradation in the radar's performance. We designed BPSK waveforms for spectral coexistence between MIMO radar and MIMO cellular communication system through different relaying protocols. Probability of detection and signal to noise ratio is formulated for different relaying protocols. The radar is capable of detecting a target in the air through azimuth as well as by elevation angle. We also showed that the desired covariance matrix is positive semi definite and radar can share the spectrum while detecting the target. We also showed a minimum square error for both angles based on the algorithm.
Highlights
The limited spectrum is allocated for commercial applications in contrast to the government or federal agencies [1]
The work presented in this paper has resolved the problem of detecting the target involving two angles which includes the azimuth and elevation angles, while keeping the constraint of Finite Alphabet Constant Envelope (FACE) beam pattern design
The radar is capable of sharing its available spectrum with the communication system
Summary
The limited spectrum is allocated for commercial applications in contrast to the government or federal agencies [1]. Different algorithms are discussed to comprehend a given covariance matrix based on different constraints to solve beam pattern matching problem for MIMO radars and MIMO communication systems. For optimizing the problem of beam pattern, the waveforms using an arbitrary cross correlation matrix have been suggested in [35] They showed their work for constant modulus constraint. They showed the spectrum sharing scenario for radar with a communication system over a single channel They showed that the waveforms are designed in such a way that they do not interfere with each other. In both cases, the radar needs to detect the target and share interference channels with the communication system. ∂ ∂ξmn v(θ, φ)k (44) The partial derivative of J( ) with respect to any element of ξ, say ξl, can be obtained as,
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