Techniques for Improving the Cooperative Traffic Conflict Detection among Drones

Abstract

Multiple access interference naturally occurs in ad-hoc networks if the same resources in time-, frequency- or code-domain are used by two or more users concurrently. Unfortunately, it can have a severe impact on the networks' performance. Therefore, mitigation strategies are needed especially with regard to safety-critical applications of ad-hoc networks like the cooperative traffic conflict detection among drones. In our work, we evaluate two techniques which deal with the problem of multiple access interference and increase the network's capacity with respect to this particular application. The first technique is successive interference cancellation whereas the second technique is known as space division multiple access. We evaluate both techniques in a future urban drone scenario considering different conflict scenarios and network parameters, i.e. the communications range of a drone. Our results show, that both techniques are capable of improving the maximum supported drone density without degrading the application’s reliability. Especially, space division multiple access leads to an improvement of up to 157% in one of the investigated conflict scenarios