Energy constrained link adaptation for multi-hop relay networks

Wireless Sensor Network (WSN) is a widely researched technology that has applications in a broad variety of fields ranging from medical, industrial, automotive and pharmaceutical to even office and home environments. It is composed of a network of self-organizing sensor nodes that operate in complex environments without human intervention for long periods of time. The energy available to these nodes, usually in the form of a battery, is very limited. Consequently, energy saving algorithms that maximize the network lifetime are sought-after. Link adaptation polices can significantly increase the data rate and effectively reduce energy consumption. In this sense, they have been studied for power optimization in WSNs in recent research proposals.;Experiments indicate that a notable reduction in energy consumption can be achieved by jointly considering the data rate and the transmit power in WSNs. The proposed ASAM algorithm considerably improves node lifetime relative to AM and AMI. Channel conditions play an important role in energy consumption for both AM and ASAM protocols. In addition, the number of modulation stages is also found to substantially affect energy consumption for ASAM. Node lifetime under different profiles of traffic intensity is also investigated. The optimal power control values and optimal power allocation factors are further derived for single-hop networks and multi-hop relay networks, respectively. Results suggest that both policies are more suitable for ASAM than for AM. Finally, the link adaptation techniques are evaluated based on the power levels of commercial IEEE 802.15.4-compliant transceivers, and ASAM consistently outperforms AM and AMI in terms of energy saving, resulting in substantially longer node lifetime.;In this thesis, we first examine the Adaptive Modulation (AM) schemes for flat-fading channels, with data rate and transmit power varied to achieve minimum energy consumption. Its variant, Adaptive Modulation with Idle mode (AMI), is also investigated. An Adaptive Sleep with Adaptive Modulation (ASAM) algorithm is then proposed to dynamically adjust the operating durations of both the transmission and sleep stages based on channel conditions in order to minimize energy consumption. Furthermore, adaptive power allocation schemes are developed to improve energy efficiency for multi-hop relay networks.