In this paper, we present our spectrum sharing algorithm between a multi-input multi-output (MIMO) radar and Long Term Evolution (LTE) cellular system with multiple base stations (BS)s. We analyze the performance of MIMO radars in detecting the angle of arrival, propagation delay and Doppler angular frequency by projecting orthogonal waveforms onto the null-space of interference channel matrix. We compare and analyze the radar's detectable target parameters in the case of the original radar waveform and the case of null-projected radar waveform. Our proposed spectrum-sharing algorithm causes minimum loss in radar performance by selecting the best interference channel that does not cause interference to the i'th LTE base station due to the radar signal. We show through our analytical and simulation results that the loss in the radar performance in detecting the target parameters is minimal when our proposed spectrum sharing algorithm is used to select the best channel onto which radar signals are projected.
The theoretical feasibility is explored of spectrum-sharing between radar and wireless communications systems via an interference mitigation processing approach. The new approach allows radar and wireless systems to operate at the same carrier frequency if the radar possesses a multiple-input multiple-output (MIMO) structure. A novel signal processing approach is developed for coherent MIMO radar that effectively minimizes the arbitrary interferences generated by wireless systems from any direction, while operating at the same frequency using cognitive radio technology. Various theoretical aspects of the new approach are investigated, and its effectiveness is further validated through simulation. In this paper, we present a beampattern analysis of the MIMO radar coexistence algorithm proposed in [1]. We extend the previous work and analyze the performance of MIMO radars by projecting finite alphabet constant-envelope waveforms onto the null-space of interference channel matrix. First, we compare and analyze the Cramer-Rao bound (CRB) on angle direction estimation. Second, we compare and analyze beampatterns of the original radar waveform and the null-projected radar waveform. Analytical and simulation results show minimal degradation of a radar's angle estimation of a target and transmit-receive beampattern. We also propose methods to substantially improve angle estimation and beampatterns of a null projected radar waveform which will not only guarantee optimal performance of the radar but at the same time guarantee coexistence of the radar and communication systems. We propose projecting radar waveform onto the null space of an interference channel matrix between the radar and a communication system as a solution for coexistence of radar and communication systems in the same band. This approach assumes that the cognitive radar has full knowledge of the interference channel and tries to modify its signal vectors in such a way that they fall in the null space of the channel matrix. We investigate the effects of null space projections on radar performance and target parameter identification both analytically and quantitatively by using maximum likelihood and Cramer-Rao bound performance bounds to estimate target direction in the two cases of no null space projection and null space projection. Through simulation we demonstrate that by optimal choice of the number of antennas, the performance and target identification capabilities of radar in our method are competitive with that of traditional radar waveforms, while simultaneously guaranteeing coexistence between radar and communication systems.