A Projection-Based Approach to Spectrum Sharing

Abstract

Spectrum sharing is a new way forward to solve spectrum scarcity problem. In this chapter, we first propose a spatial approach for spectrum sharing between a MIMO radar and an LTE cellular system with multiple base stations (BS). The MIMO radar and LTE share multiple interference channels. We propose projecting the radar signal onto the null space of interference channel between the MIMO radar and LTE using our proposed interference-channel-selection algorithm, in order to have zero-interference from the MIMO radar. We select interference channel with the maximum null space and project the radar signal onto the null space of this channel. Our proposed spatial spectrum sharing algorithm is radar-centric such that it causes minimum loss in radar performance by carefully selecting the interference channel and at the same time protects the \(i^{\text {th}}\) LTE BS from the radar interference. Through our analytical and simulation results we show that the loss in the radar performance is less when the proposed interference-channel-selection algorithm is used to select the channel onto which radar signals are projected. Second, we address the problem of target detection by radars that project waveform onto the null space of interference channel in order to mitigate interference to cellular systems. We consider a multiple-input multiple-output (MIMO) radar and a MIMO cellular communication system with multiple base stations (BS). We consider two spectrum sharing scenarios. In the first scenario, the degrees of freedom (DoF) available at the radar are not sufficient enough to simultaneously detect target and mitigate interference to multiple BSs. For this case we select one BS among many BSs for waveform projection on the basis of guaranteeing minimum waveform degradation. For the second case, the radar has sufficient DoF to simultaneously detect target and mitigate interference to all BSs. We study target detection capabilities of null-space projected (NSP) waveform and compare it with the orthogonal waveform. We derive the generalized likelihood ratio test (GLRT) for target detection and derive detector statistic for NSP and orthogonal waveform. The target detection performance for both waveforms is studied theoretically and via Monte Carlo simulations.