The increasing demand for cellular network capacity can be mitigated through the installation of nomadic eNodeB, which serve a temporal increase of traffic volume in specific area. When nomadic cells are deployed, the transmission power of neighbour base stations needs to be optimised to limit the inter-cell interferences. The authors analyse the problem of neighbourhood selection for the optimisation, to define what part of the networks needs to be reconfigured when new base station is added. They evaluate the iterative approach, with increasing range of neighbouring cells being reconfigured and propose a novel, sampling-based local TX power reconfiguration method, which is evaluated by a numerical model in both regular (honeycomb) topology and in realistic topology reflecting locations of cells in a city. The analysis confirms that the proposed algorithm allows to select small subset of neighbouring cells to be reconfigured (in majority of the cases <10 cells), and achieve similar efficacy as global optimisation, with total network throughput different by <1% comparing to the global optimisation.
a1751-8628 00378nas a2200145 4500000000100000000000100001008004100002100001900043700002200062700001900084700001900103700002000122245008300142490000700225 2020 d 1 aMaciej Nikodem 1 aMariusz Słabicki 1 aTomasz Surmacz 1 aPaweł Mrówka 1 aCezary Dołęga 00 aMulti-Camera Vehicle Tracking Using Edge Computing and Low-Power Communication 0 v20 00318nas a2200121 4500000000100000000000100001008004100002100001900043700002200062700001700084245008800101490000700189 2020 d 1 aMaciej Nikodem 1 aMariusz Słabicki 1 aMarek Bawiec 00 aEfficient Communication Scheme for Bluetooth Low Energy in Large Scale Applications 0 v20 00423nas a2200157 4500000000100000000000100001008004100002260002100043100002200064700001900086700002200105700002300127245005900150856004900209490000700258 2020 d c13 February 2020 1 aGopika Premsankar 1 aBissan Ghaddar 1 aMariusz Słabicki 1 aMario Di Francesco 00 aOptimal configuration of LoRa networks in smart cities uhttps://ieeexplore.ieee.org/document/8998148 0 v16 00407nas a2200157 4500000000100000000000100001008004100002260001300043100001900056700001900075700002200094700001900116700002100135700002000156245007300176 2020 d bSpringer 1 aMaciej Nikodem 1 aTomasz Surmacz 1 aMariusz Słabicki 1 aDominik Hofman 1 aPiotr Klimkowski 1 aCezary Dołęga 00 aRobust Radio Communication Protocol for Traffic Analysis Application 00424nas a2200145 4500000000100000000000100001008004100002260000900043100002700052700002200079700002200101700002300123245008300146856004900229 2021 d bIEEE 1 aVeronica Toro-Betancur 1 aGopika Premsankar 1 aMariusz Słabicki 1 aMario Di Francesco 00 aModeling Communication Reliability in LoRa Networks with Device-level Accuracy uhttps://ieeexplore.ieee.org/document/9488783 01877nas a2200169 4500000000100000000000100001008004100002260003800043100002000081700002200101700002200123700002100145245009300166856005000259300001400309520138400323 2023 d c07/2023 bIEEE aMarrakesh, Morocco 1 aSławomir Nowak 1 aKrzysztof Grochla 1 aMariusz Słabicki 1 aMichał Gorawski 00 aEfficient Universal Indoor Multicharacteristic Propagation model for indoor environments uhttps://ieeexplore.ieee.org/document/10183073 a1052-1058 3 aAccurate indoor radio propagation modelling is a well-known problem that researchers tend to solve in many ways. Related methods differ in terms of accuracy and complexity. The article’s contribution is a new stochastic propagation model, Universal Indoor Multicharacteristic Propagation (UIMP), which results are statistically consistent with those measured in a real environment. The model could be used to verify real- world applications due to the low computational complexity and high accuracy level compared to state-of-the-art methods. This method can be especially beneficial for the efficient modelling of complex environments shared by many users using discrete events simulations (DES) based on a series of measurements in a real environment. In the article, we describe the method and present how to establish the model. The motivation was to develop an efficient method for use in an actual application: using the Bluetooth Low Energy (BLE) signal to estimate the position of users in indoor environments – the use of the proposed UIMP model allowed for a reliable assessment of the developed functionalities. Therefore we also present how the model was used to evaluate an example, real functionality, showing that the use of simplified models may falsify the assessment of the analyzed method and may lead e.g. to incorrect implementation assumptions.