Localization accuracy based on RSS (Received Signal Strength) is notoriously inaccurate in the application of wireless sensor networks. RSS is subject to shadowing effects, which is signal attenuation caused by stationary objects in the radio propagation. RSS are actually the result of decay over distances, and random attenuation over different directions. RSS measurement is also affected by antenna orientation. Starting from extracting the statistical orders in the function relationship between RSS and distance, this thesis first shows how non-metric MDS (Multi-Dimensional Scaling) is the suitable method for cooperative localization. Then, several issues are presented and discussed in the application of non-metric MDS, including determining full connections to avoid flip ambiguities, leveraging the proper initial estimation to avert from local minimum solutions, and imposing structural information to bend the localization result to a priori knowledge. To evaluate the solution, data were acquired from different scenarios including accurate radio propagation model, indoor empirical test, and outside empirical test. Experiment results shows that non-metric MDS can only combat the small scale randomness in the shadowing effects. To combat the large scale ones, macro-diversity approaches are further presented including rotating the receiver’s antenna or collecting RSS from more than one mote in the same position. By averaging the measurements from these diversified receivers, simulation results and empirical tests show that shadowing effects can be greatly reduced. Also included in this thesis is how effective packet structures should be designed in the mote programming based on TinyOS to collect different sequences of RSS measurements and fuse them together. / UOIT

At the present time, wireless sensor networks are becoming more and more  common and energy consumption is a key factor in the deployment and  maintenance of these networks. This thesis compares non-SFN multi-hop and  a single frequency network (SFN) or cooperative diversity algorithms with  respect to the energy consumed by the nodes. Since the nodes have limited  power capacity it is extremely important to have an efficient algorithm. In  addition, the behaviour of the network when SFN is employed must be  studied and advice offered with regards to improvements in order to achieve  preferential results. The effect on the network regarding macro diversity is  positive but, the battery energy consumption is still higher and has a drainage  effect on the network for simple multi-hop. The report will include  background information regarding mobile ad-hoc networks and the  relationship with cooperative diversity. It will also deal with how different  algorithms affect the energy consumption in multi-hop networks. Simulations  will also be presented in Matlab plots for two single frequency network  scenarios against a simple multi-hop regarding node energy during the  network discovery and decline. Results will include comparative figures which  are followed by a discussion concerning the simulation results and its effects.  The applications for wireless sensor networks include area monitoring,  environmental monitoring, data logging, industrial monitoring, agriculture  and the idea can additionally be used for wireless radio and TV distribution.  The simulations have been conducted for cooperative diversity algorithms  (SFN-A and SFN-D) against an algorithm which does not use cooperative  diversity in Matlab. The node energy consumption is compared for both  scenarios with regards to both  network reachability and decline. The node  power is analysed during the reachability of the network from the start to  attaining 100% of the discovered network. During network decline, the  behaviour of the node energy is studied for algorithms with SFN-A, SFN-D  and non SFN.  Also, the number of times node transmission occurs with  regards to  node discovery is also analysed.

<p>Wireless Sensor Network is an emerging technology that has applicationsin Wireless Actuators, remote controlling, distribution of softwareupdates and distribution of parameters to sensor nodes. This projectwork basically covers the concept of macro-diversity. This is a situationin which several transmitters are used for transferring the same signal (inmulti-hop sensor networks) to check the increase in connected nodes orin network coverage. Transmitter macro-diversity increases the receivedsignal strength and thus increases the signal-to-noise ratio which resultsin a lower outage probability. To accomplish this task three differentstrategies have been simulated using thirteen different cases. Broadcastingis used when forming SFN of size one (strategy one) and uni-castingis used for forming SFNs of size two (strategy two) and size three (strategythree).In this project reference material has been gathered frombooks, journals and web sources; and MATLAB has been used as thesimulation tool in which codes are written in the M programming language.The algorithm works firstly by discovering all the nodes that areconnected directly with the Base Station through multi-hoping, afterwhich the second algorithm is applied to check how many more nodescan be reached by forming SFNs. A gain of up to 79% was observedusing strategy one and strategy two and up to 83% in strategy three.The results shows that strategy one (Forming SFNs using BroadcastingTechnique) is the best as more nodes can be reached (for different cases)than for the other two strategies (forming SFNs using uni-casting technique).</p>

Wireless Sensor Network is an emerging technology that has applicationsin Wireless Actuators, remote controlling, distribution of softwareupdates and distribution of parameters to sensor nodes. This projectwork basically covers the concept of macro-diversity. This is a situationin which several transmitters are used for transferring the same signal (inmulti-hop sensor networks) to check the increase in connected nodes orin network coverage. Transmitter macro-diversity increases the receivedsignal strength and thus increases the signal-to-noise ratio which resultsin a lower outage probability. To accomplish this task three differentstrategies have been simulated using thirteen different cases. Broadcastingis used when forming SFN of size one (strategy one) and uni-castingis used for forming SFNs of size two (strategy two) and size three (strategythree).In this project reference material has been gathered frombooks, journals and web sources; and MATLAB has been used as thesimulation tool in which codes are written in the M programming language.The algorithm works firstly by discovering all the nodes that areconnected directly with the Base Station through multi-hoping, afterwhich the second algorithm is applied to check how many more nodescan be reached by forming SFNs. A gain of up to 79% was observedusing strategy one and strategy two and up to 83% in strategy three.The results shows that strategy one (Forming SFNs using BroadcastingTechnique) is the best as more nodes can be reached (for different cases)than for the other two strategies (forming SFNs using uni-casting technique).