Power-Aware Communication Systems

Abstract

Battery-operated systems usually operate as part of larger networks where they wirelessly communicate with other systems. Conventional techniques for lowpower design, with their focus on circuits and computation logic in a system, are at best inadequate for such networked systems. The reason is two fold. First, the energy cost associated with wireless communications dominates the energy cost associated with computation. Being dictated primarily by a totally different set of laws (Shannon and Maxwell), communication energy, unlike computation energy, does not even benefit much from Moore's Law. Second, designers are interested in network-wide energy-related metrics, such as network lifetime, which techniques focused on computation at a single system cannot address. Therefore, in order to go beyond low-power techniques developed for stand-alone computing systems, this chapter describes communication-related sources of power consumption and network-level power-reduction and energy-management techniques in the context of wirelessly networked systems such as wireless multimedia and wireless sensor networks. General principles behind power-aware protocols and resource management techniques at various layers of networked systems -physical, link, medium access, routing, transport, and application -are presented. Unlike their conventional counterparts that only manage bandwidth to achieve performance, power-aware network protocols also manage the energy resource. Their goal is not just a reduction in the total power consumption. Rather, power-aware protocols seek a trade-off between energy and performance via network-wide power management to provide the right power at the right place and the right time.

The Case for Interpreted Languages in Sensor Networks

“…The last component, associated to the irradiated power, is consumed by the radio power amplifier that depends on the signal power required by the receiver and the path loss suffered by the signal. The path loss increases proportionally with receiver-transmitter separation distance, and depends on the environment condition, being a power of two in free space but up to four in real life channels [17]. As it is dictated by the Shannon's Information Theory and Maxwell's Laws, this power cannot be reduced.…”

Energy-Model-Based Optimal Communication Systems Design for Wireless Sensor Networks

“…Since most power parameters of the analog blocks except PA are hard to be adjusted in WSN for low-power purpose, we assume that the power consumption of WSN nodes except PA is constant. As the power consumption of PA is dominant [13], we focus on it first.…”

“…This may lead to erroneous energy evaluations, since the RF and analog sections process analog signals with high-frequency content and typically consume more energy compared to the digital part. According to [13], about 75% of the total power is dissipated in the RF front end. So, it is important to develop an accurate and comprehensive energy model for WSN RF front end.…”

Energy-Constrained Duty-Cycle Optimization for Wireless Implanted Communication Devices

“…It is also assumed that no complicated signal processing techniques such as multiuser detection or iterative decoding are used. The power consumption in these parts are quite small [9] compared with the power consumption in the RF circuitry block, which is closely related to the carrier frequency. Thus, in this paper, these blocks (e.g., source coding, pulse-shaping, and digital modulation) are neglected to simplify the model.…”