A joint multi user detection scheme for UWB sensor networks using waveform division multiple access

A joint multiuser detection (MUD) scheme for wireless sensor networks (WSNs) is proposed to suppress multiple access interference (MAI) caused by a large number of sensor nodes. In WSNs, waveform division multiple access ultra-wideband (WDMA-UWB) technology is well-suited for robust communications. Multiple sensor nodes are allowed to transmit modulated signals by sharing the same time periods and frequency bands using orthogonal pulse waveforms. This paper employs a mapping function based on the optimal multiuser detection (OMD) to map the received bits into the mapping space where error bits can be distinguished. In order to revise error bits caused by MAI, the proposed joint MUD scheme combines the mapping function with suboptimal algorithms. Numerical results demonstrate that the proposed MUD scheme provides good performances in terms of suppressing MAI and resisting near-far effect with low computational complexity

Improvements on the bees algorithm for continuous optimisation problems

This work focuses on the improvements of the Bees Algorithm in order to enhance the algorithm’s performance especially in terms of convergence rate. For the first enhancement, a pseudo-gradient Bees Algorithm (PG-BA) compares the fitness as well as the position of previous and current bees so that the best bees in each patch are appropriately guided towards a better search direction after each consecutive cycle. This method eliminates the need to differentiate the objective function which is unlike the typical gradient search method. The improved algorithm is subjected to several numerical benchmark test functions as well as the training of neural network. The results from the experiments are then compared to the standard variant of the Bees Algorithm and other swarm intelligence procedures. The data analysis generally confirmed that the PG-BA is effective at speeding up the convergence time to optimum. Next, an approach to avoid the formation of overlapping patches is proposed. The Patch Overlap Avoidance Bees Algorithm (POA-BA) is designed to avoid redundancy in search area especially if the site is deemed unprofitable. This method is quite similar to Tabu Search (TS) with the POA-BA forbids the exact exploitation of previously visited solutions along with their corresponding neighbourhood. Patches are not allowed to intersect not just in the next generation but also in the current cycle. This reduces the number of patches materialise in the same peak (maximisation) or valley (minimisation) which ensures a thorough search of the problem landscape as bees are distributed around the scaled down area. The same benchmark problems as PG-BA were applied against this modified strategy to a reasonable success. Finally, the Bees Algorithm is revised to have the capability of locating all of the global optimum as well as the substantial local peaks in a single run. These multi-solutions of comparable fitness offers some alternatives for the decision makers to choose from. The patches are formed only if the bees are the fittest from different peaks by using a hill-valley mechanism in this so called Extended Bees Algorithm (EBA). This permits the maintenance of diversified solutions throughout the search process in addition to minimising the chances of getting trap. This version is proven beneficial when tested with numerous multimodal optimisation problems

Schweizerische Präsenz an internationalen Forschungsfronten 1999

Winterhager M, Schwechheimer H. Schweizerische Präsenz an internationalen Forschungsfronten 1999. Center for Science and Technology Studies. Vol 2002,8. Bern: CEST; 2002.Ziel der vorliegenden Untersuchung ist die Identifikation und Analyse der wichtigsten Forschungsfronten, an denen in der Schweiz tätige Forschende 1999 beteiligt waren. Schwerpunkte schweizerischer Forschungsaktivität werden durch ein bibliometrisches Profil auf der Grundlage einer Ko-Zitationsanalyse transparent gemacht. Die mit der Ko-Zitationsanalyse identifizierten Forschungsfronten liefern eine Abbildung der aktuellen Forschungslandschaft, die allein auf der Auswertung der Ströme formaler Kommunikation (Publikationen und Zitationen) beruht. In diesem Sinne ist das Verfahren unabhängig von bestehenden Klassifikationsschemata, disziplinären Zuordnungen und subjektiven Sichtweisen einzelner Experten. Es nutzt lediglich die durch die publizierenden Forscherinnen und Forscher selbst realisierten kognitiven Bezüge, um aktuelle Forschungsfronten zu identifizieren und ihre Relationen zueinander darzustellen. Der Bericht dokumentiert zunächst das Ergebnis der Suche nach den Forschungsfronten mit schweizerischer Beteiligung. Als Datenbasis wurde eine Ko-Zitationsanalyse des Jahrgangs 1999 des Science Citation Index Expanded und des Social Sciences Citation Index herangezogen. Diese Datenbasis besteht aus insgesamt 22942 Forschungsfronten aus allen disziplinären Bereichen. Die Forschungsfronten werden ohne vorgängige disziplinäre Kategorisierungen generiert und sind daher in besonderer Weise geeignet, interdisziplinäre Entwicklungen abzubilden. Aus dem Gesamtdatenbestand aller Fronten des Jahrgangs 1999 wurden diejenigen 2.404 ausgewählt, in deren Kern mindestens eine Publikation schweizerischen Ursprungs enthalten ist