Successive Interference Cancellation (SIC) allows simultaneous transmissions on a common physical channel to be detected simultaneously by receivers, given that the received power levels are sufficiently different both from each other and from the ambient noise. However, received power levels in mobile networks are notoriously variable and unpredictable, making it difficult to adjust transmitted power in such a way as to optimize throughput. An earlier approach  attempted to counteract the mobility effects by dilating the power-level sequence from the values optimised for a stationary network with constant channel attenuation; surprisingly this not only did compensate for the reduction in throughput, but actually improved it further. However, there are four major weaknesses in the work as it currently stands: (i) it is based purely in simulation, and needs a more basic analytical approach to establish its generality, (ii) users are assumed to behave in a simplistic manner, transmitting for random times at random intervals while wandering within a well-defined geometric area, (iii) the channel model is simplistic, based on free-space attenuation only, and (iv) the link-layer algorithm is generic and simplistic and does not represent fully the CSMA/CA mechanism of real wireless networks.
This project will analyse the problem bottom-up, with a view to creating an optimal algorithm independent of network size, user behaviour and channel conditions. This will involve an extensive study of the SIC mechanism, together with models of user behaviour, mobility patterns and the statistical properties of the wireless channel itself. The aim will be to create a protocol compatible with existing wireless technology which can provide mobile multi-user access, with an optimized trade-off between throughput and power consumption, and to demonstrate mathematically the generality of this algorithm.
 Tunnicliffe, Martin, “Free space attenuation and throughput in a wireless mobile network using successive interference cancellation with power randomization”, in: 15th International Conference on Computer Modelling and Simulation, 10-12 April 2013, Cambridge, U.K. ISBN 9780769549941