Compressed sensing for optimising connectivity in FANET architecture

FANET is co-operative, reconfigurable, autonomous network of UAVs. The emerging technology of FANET has many applications in civilian and military field like search and rescue mission, surveillance, reconnaissance, monitoring etc. which create temporary mobile ad-hoc platform for communication and data collection. For such applications, main requirements are maintaining and sustaining connectivity with nodes and effective utilisation of limited resources like bandwidth. Further, as the UAVs are moving with very high velocity, their topology changes rapidly and hence connectivity among them may lose. To address this problem, usage of novel technique called compressed sensing is proposed. In compressed sensing method, instead of sampling the signal by Nyquist rate, signal is sampled by Sub-Nyquist rate i.e. sampling rate less than Nyquist rate. Thus, few samples are transmitted and signal can be recovered by using convex optimisation technique. In FANET, number of UAVs are few. Hence, number of frequencies occupied will be sparse as compared to available wide spectrum band. In this paper, sparsity in form of number of UAVs is exploited and compressed sensing is implemented on coordination information which is shared between nodes.