Computing the kk-coverage of a wireless network

Coverage is one of the main quality of service of a wirelessnetwork. $k$-coverage, that is to be covered simultaneously by $k$network nodes, is synonym of reliability and numerous applicationssuch as multiple site MIMO features, or handovers. We introduce here anew algorithm for computing the $k$-coverage of a wirelessnetwork. Our method is based on the observation that $k$-coverage canbe interpreted as $k$ layers of $1$-coverage, or simply coverage. Weuse simplicial homology to compute the network's topology and areduction algorithm to indentify the layers of $1$-coverage. Weprovide figures and simulation results to illustrate our algorithm.Comment: Valuetools 2019, Mar 2019, Palma de Mallorca, Spain. 2019. arXiv admin note: text overlap with arXiv:1802.0844

Evaluating the capacity gains from Coordinated MultiPoint Transmission and Reception

International audienceThis paper evaluates and compares different Coordinated MultiPoint (CoMP) Joint Processing (JP) schemes. We consider the LTE-Advanced codebook-based schemes, where the serving beams are taken from a pre-determined codebook. We namely consider Single User Joint Processing (SUJP) and Multiple Users Joint Processing (MUJP) with two variants: Least Interfering Beams (MUJPLIB) andMost Interfering Beams (MUJPMIB). We follow a cross-layer approach where both PHY and MAC layers mechanisms are taken into account by a realistic system-level simulator, whereas the higher level performance is assessed by a Markovian analysis. This latter considers the coupling between the different cells and derives the flow level capacities of the different solutions. Our results show that, globally, MUJP achieves the best performance for low to medium traffic, while all JP schemes do not perform well for large loads