Compressive RF Fingerprint Acquisition and Broadcasting for Dense BLE Networks

This paper presents a novel bluetooth low energy (BLE) protocol enabling a BLE node to perform RF fingerprint acquisition by measuring the received signal strength (RSS) from its neighboring nodes and simultaneously broadcast the acquired fingerprint via its advertising packet. However, the fingerprint acquisition and broadcast process in a dense BLE network is very challenging owing to: 1) the likelihood of packet collision; and 2) the length-constrained packet. To this end, we exploit a compressive sensing (CS) framework allowing each node to acquire no more than M measurements from a very dense network, in which the number of nodes N is far greater than M . By aggregating the M -dimensional compressed fingerprint vector from s < N nodes, the receiver is able to reconstruct the fingerprints broadcast by all N nodes. This is the very first work that implements CS on a low power device for fingerprint acquisition. Our proposed compressive RF fingerprinting (CRF) has been demonstrated with real and dense BLE networks, consisting of 300 nodes randomly distributed around a confined area. We also conducted extensive simulations to verify the performance of three different reconstruction algorithms. The low reconstruction error at the receiving end indicates the feasibility of our proposed CRF in achieving efficient fingerprint acquisition for dense BLE networks.