PHY-Layer Authentication Exploiting Channel Sparsity in MmWave MIMO UAV-Ground Systems

This paper exploits the efficient channel modeling and channel sparsity to propose a novel Physical (PHY)-layer authentication framework for a Millimeter Wave (mmWave) Multiple-Input Multiple-Output (MIMO) Unmanned Aerial Vehicle (UAV)-ground system. Inspired by the Image Processing theory, we first explore a new Laplace prior approach for the efficient modeling of angular-domain mmWave MIMO channels. With the help of the new channel model, we then reveal the channel sparsity in the concerned system exhibiting a nice spatial correlation property. By a joint use of channel sparsity correlation, efficient sparsity feature extraction with Expectation Maximization (EM)/Generalized Approximate Message Passing (GAMP) algorithms and hypothesis testing, we thus devise a new authentication framework for the concerned system. Theoretical performance analysis is also carried out by deriving the closed-form expressions for false alarm and detection probabilities. Finally, extensive numerical results are provided to validate the feasibility of the proposed channel model and the theoretical analysis, as well as to demonstrate the efficiency of the new authentication framework under various scenarios.