Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.
Zenaidi, Mohamed Ridha; Rezki, Zouheir; Alouini, Mohamed-Slim(IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2017-03-01)[Article]
In energy harvesting communications, the transceivers have to adjust the data transmission to the energy scavenged during the course of communication. The performance of the transmission depends on the channel conditions which vary randomly due to mobility and environmental changes. In this paper, we consider the problem of power allocation taking into account the energy arrivals over time and the quality of channel state information (CSI) measured at the transmitter, in order to maximize the throughput. Differently from previous work, we focus on energy harvesting communications where the CSI at the transmitter is not perfect and may include estimation errors. In the present paper, we introduce a Markov process that models the energy arrival process. Indeed, we solve the throughput maximization problem with respect to energy harvesting constraints. We show that the optimal online power policy can be found using dynamic programming. Furthermore, we study the asymptotic behavior of the communication system at low and high average recharge rate (ARR) regime. Selected numerical results are provided to support our analysis.
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