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Abstract A Wireless Sensor Network (WSN) consists of a number of sensor nodes that are randomly deployed, and it transforms a physical data into a form that would make it easier for the user to understand. The main challenge in the design of WSNs is the limited battery power of the sensor nodes and the difficulty of replacing or recharging these batteries due to the nature of the monitored field. The direct approach to collect data from sensor nodes is that each sensor node transmits the data directly to the Base Station (BS). However, this approach consumes a lot of energy to transmit data from each sensor node to the BS. Thus, nodes die very quickly, and as a result, they reduce the network lifetime. Therefore, as few transmissions as possible are desired for efficient energy utilization. Firstly, a modification of the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is presented based on compressive sensing to reduce the amount of power by decreasing the size of transmitted data. Furthermore, a proposed protocol, namely Adaptive Soft Thresholding based Energy Efficient sensor Network (ASTEEN) is presented to reduce the amount of energy in WSNs based on an adaptive soft thresholding strategy that takes the importance of sensed data into consideration. The Peak-to-Average Ratio Reduction (PAPR) problem is considered in this thesis to reduce transmission power. Several non-linear companding techniques are presented and compared for this purpose. Moreover, the routing strategy in sensor networks is considered in an efficient treatment. A Wireless Sensor Network (WSN) consists of a number of sensor nodes that are randomly deployed, and it transforms a physical data into a form that would make it easier for the user to understand. The main challenge in the design of WSNs is the limited battery power of the sensor nodes and the difficulty of replacing or recharging these batteries due to the nature of the monitored field. The direct approach to collect data from sensor nodes is that each sensor node transmits the data directly to the Base Station (BS). However, this approach consumes a lot of energy to transmit data from each sensor node to the BS. Thus, nodes die very quickly, and as a result, they reduce the network lifetime. Therefore, as few transmissions as possible are desired for efficient energy utilization. Firstly, a modification of the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is presented based on compressive sensing to reduce the amount of power by decreasing the size of transmitted data. Furthermore, a proposed protocol, namely Adaptive Soft Thresholding based Energy Efficient sensor Network (ASTEEN) is presented to reduce the amount of energy in WSNs based on an adaptive soft thresholding strategy that takes the importance of sensed data into consideration. The Peak-to-Average Ratio Reduction (PAPR) problem is considered in this thesis to reduce transmission power. Several non-linear companding techniques are presented and compared for this purpose. Moreover, the routing strategy in sensor networks is considered in an efficient treatment. A Wireless Sensor Network (WSN) consists of a number of sensor nodes that are randomly deployed, and it transforms a physical data into a form that would make it easier for the user to understand. The main challenge in the design of WSNs is the limited battery power of the sensor nodes and the difficulty of replacing or recharging these batteries due to the nature of the monitored field. The direct approach to collect data from sensor nodes is that each sensor node transmits the data directly to the Base Station (BS). However, this approach consumes a lot of energy to transmit data from each sensor node to the BS. Thus, nodes die very quickly, and as a result, they reduce the network lifetime. Therefore, as few transmissions as possible are desired for efficient energy utilization. Firstly, a modification of the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is presented based on compressive sensing to reduce the amount of power by decreasing the size of transmitted data. Furthermore, a proposed protocol, namely Adaptive Soft Thresholding based Energy Efficient sensor Network (ASTEEN) is presented to reduce the amount of energy in WSNs based on an adaptive soft thresholding strategy that takes the importance of sensed data into consideration. The Peak-to-Average Ratio Reduction (PAPR) problem is considered in this thesis to reduce transmission power. Several non-linear companding techniques are presented and compared for this purpose. Moreover, the routing strategy in sensor networks is considered in an efficient treatment. A Wireless Sensor Network (WSN) consists of a number of sensor nodes that are randomly deployed, and it transforms a physical data into a form that would make it easier for the user to understand. The main challenge in the design of WSNs is the limited battery power of the sensor nodes and the difficulty of replacing or recharging these batteries due to the nature of the monitored field. The direct approach to collect data from sensor nodes is that each sensor node transmits the data directly to the Base Station (BS). However, this approach consumes a lot of energy to transmit data from each sensor node to the BS. Thus, nodes die very quickly, and as a result, they reduce the network lifetime. Therefore, as few transmissions as possible are desired for efficient energy utilization. Firstly, a modification of the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is presented based on compressive sensing to reduce the amount of power by decreasing the size of transmitted data. Furthermore, a proposed protocol, namely Adaptive Soft Thresholding based Energy Efficient sensor Network (ASTEEN) is presented to reduce the amount of energy in WSNs based on an adaptive soft thresholding strategy that takes the importance of sensed data into consideration. The Peak-to-Average Ratio Reduction (PAPR) problem is considered in this thesis to reduce transmission power. Several non-linear companding techniques are presented and compared for this purpose. Moreover, the routing strategy in sensor networks is considered in an efficient treatment. |