745 research outputs found
A survey of localization in wireless sensor network
Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network
Wi-PoS : a low-cost, open source ultra-wideband (UWB) hardware platform with long range sub-GHz backbone
Ultra-wideband (UWB) localization is one of the most promising approaches for indoor localization due to its accurate positioning capabilities, immunity against multipath fading, and excellent resilience against narrowband interference. However, UWB researchers are currently limited by the small amount of feasible open source hardware that is publicly available. We developed a new open source hardware platform, Wi-PoS, for precise UWB localization based on Decawave’s DW1000 UWB transceiver with several unique features: support of both long-range sub-GHz and 2.4 GHz back-end communication between nodes, flexible interfacing with external UWB antennas, and an easy implementation of the MAC layer with the Time-Annotated Instruction Set Computer (TAISC) framework. Both hardware and software are open source and all parameters of the UWB ranging can be adjusted, calibrated, and analyzed. This paper explains the main specifications of the hardware platform, illustrates design decisions, and evaluates the performance of the board in terms of range, accuracy, and energy consumption. The accuracy of the ranging system was below 10 cm in an indoor lab environment at distances up to 5 m, and accuracy smaller than 5 cm was obtained at 50 and 75 m in an outdoor environment. A theoretical model was derived for predicting the path loss and the influence of the most important ground reflection. At the same time, the average energy consumption of the hardware was very low with only 81 mA for a tag node and 63 mA for the active anchor nodes, permitting the system to run for several days on a mobile battery pack and allowing easy and fast deployment on sites without an accessible power supply or backbone network. The UWB hardware platform demonstrated flexibility, easy installation, and low power consumption
Allocation of control and data channels for Large-Scale Wireless Sensor Networks
Both IEEE 802.15.4 and 802.15.4a standards allow for dynamic channel
allocation and use of multiple channels available at their physical layers but
its MAC protocols are designed only for single channel. Also, sensor's
transceivers such as CC2420 provide multiple channels and as shown in [1], [2]
and [3] channel switch latency of CC2420 transceiver is just about 200s.
In order to enhance both energy efficiency and to shorten end to end delay, we
propose, in this report, a spectrum-efficient frequency allocation schemes that
are able to statically assign control channels and dynamically reuse data
channels for Personal Area Networks (PANs) inside a Large-Scale WSN based on
UWB technology
DQLEL: Deep Q-Learning for Energy-Optimized LoS/NLoS UWB Node Selection
Recent advancements in Internet of Things (IoTs) have brought about a surge
of interest in indoor positioning for the purpose of providing reliable,
accurate, and energy-efficient indoor navigation/localization systems. Ultra
Wide Band (UWB) technology has been emerged as a potential candidate to satisfy
the aforementioned requirements. Although UWB technology can enhance the
accuracy of indoor positioning due to the use of a wide-frequency spectrum,
there are key challenges ahead for its efficient implementation. On the one
hand, achieving high precision in positioning relies on the
identification/mitigation Non Line of Sight (NLoS) links, leading to a
significant increase in the complexity of the localization framework. On the
other hand, UWB beacons have a limited battery life, which is especially
problematic in practical circumstances with certain beacons located in
strategic positions. To address these challenges, we introduce an efficient
node selection framework to enhance the location accuracy without using complex
NLoS mitigation methods, while maintaining a balance between the remaining
battery life of UWB beacons. Referred to as the Deep Q-Learning
Energy-optimized LoS/NLoS (DQLEL) UWB node selection framework, the mobile user
is autonomously trained to determine the optimal set of UWB beacons to be
localized based on the 2-D Time Difference of Arrival (TDoA) framework. The
effectiveness of the proposed DQLEL framework is evaluated in terms of the link
condition, the deviation of the remaining battery life of UWB beacons, location
error, and cumulative rewards. Based on the simulation results, the proposed
DQLEL framework significantly outperformed its counterparts across the
aforementioned aspects
Energy-delay tradeoffs in impulse-based ultra-wideband body area networks with noncoherent receivers
© 2014 IEEE. In this paper we address the problem of rate scheduling in the Impulse Radio (IR) ultra-wideband (UWB) wireless body area networks (WBANs) and the minimum energy required to stabilize the queuing system. Targeting low complexity WBAN applications, we assume noncoherent receivers based on energy detection and autocorrelation for all nodes. The coordinating node can minimize the average energy consumption of the system and achieve the queue backlog stability of the sensor nodes by controlling the number of pulses per symbol. We first illustrate the necessary and sufficient conditions of network stability for a multi-mode UWB system and then propose a feasible rate scheduling algorithm based on the Lyapunov optimization theory. The scheduling algorithm uses the instantaneous channel state information and the length of the local queue of all sensor nodes and can approach the optimal energy-delay tradeoff of the network. We apply our theoretical framework to the IR-UWB physical layer of the IEEE 802.15.6 standard and extract the optimal physical layer modes that can achieve the desired energy-delay tradeoff
A Sub-nW 2.4 GHz Transmitter for Low Data-Rate Sensing Applications
This paper presents the design of a narrowband transmitter and antenna system that achieves an average power consumption of 78 pW when operating at a duty-cycled data rate of 1 bps. Fabricated in a 0.18 ÎĽm CMOS process, the transmitter employs a direct-RF power oscillator topology where a loop antenna acts as a both a radiative and resonant element. The low-complexity single-stage architecture, in combination with aggressive power gating techniques and sizing optimizations, limited the standby power of the transmitter to only 39.7 pW at 0.8 V. Supporting both OOK and FSK modulations at 2.4 GHz, the transmitter consumed as low as 38 pJ/bit at an active-mode data rate of 5 Mbps. The loop antenna and integrated diodes were also used as part of a wireless power transfer receiver in order to kick-start the system power supply prior to energy harvesting operation.Semiconductor Research Corporation. Interconnect Focus CenterSemiconductor Research Corporation. C2S2 Focus CenterNational Institutes of Health (U.S.) (Grant K08 DC010419)National Institutes of Health (U.S.) (Grant T32 DC00038)Bertarelli Foundatio
Communication channel analysis and real time compressed sensing for high density neural recording devices
Next generation neural recording and Brain-
Machine Interface (BMI) devices call for high density or distributed
systems with more than 1000 recording sites. As the
recording site density grows, the device generates data on the
scale of several hundred megabits per second (Mbps). Transmitting
such large amounts of data induces significant power
consumption and heat dissipation for the implanted electronics.
Facing these constraints, efficient on-chip compression techniques
become essential to the reduction of implanted systems power
consumption. This paper analyzes the communication channel
constraints for high density neural recording devices. This paper
then quantifies the improvement on communication channel
using efficient on-chip compression methods. Finally, This paper
describes a Compressed Sensing (CS) based system that can
reduce the data rate by > 10x times while using power on
the order of a few hundred nW per recording channel
Energy Harvesting for Self-Powered Wireless Sensors
A wireless sensor system is proposed for a targeted deployment in civil infrastructures (namely bridges) to help mitigate the growing problem of deterioration of civil infrastructures. The sensor motes are self-powered via a novel magnetic shape memory alloy (MSMA) energy harvesting material and a low-frequency, low-power rectifier multiplier (RM). Experimental characterizations of the MSMA device and the RM are presented. A study on practical implementation of a strain gauge sensor and its application in the proposed sensor system are undertaken and a low-power successive approximation register analog-to-digital converter (SAR ADC) is presented. The SAR ADC was fabricated and laboratory characterizations show the proposed low-voltage topology is a viable candidate for deployment in the proposed sensor system. Additionally, a wireless transmitter is proposed to transmit the SAR ADC output using on-off keying (OOK) modulation with an impulse radio ultra-wideband (IR-UWB) transmitter (TX). The RM and SAR ADC were fabricated in ON 0.5 micrometer CMOS process.
An alternative transmitter architecture is also presented for use in the 3-10GHz UWB band. Unlike the IR-UWB TX described for the proposed wireless sensor system, the presented transmitter is designed to transfer large amounts of information with little concern for power consumption. This second method of data transmission divides the 3-10GHz spectrum into 528MHz sub-bands and "hops" between these sub-bands during data transmission. The data is sent over these multiple channels for short distances (?3-10m) at data rates over a few hundred million bits per second (Mbps). An UWB TX is presented for implementation in mode-I (3.1-4.6GHz) UWB which utilizes multi-band orthogonal frequency division multiplexing (MB-OFDM) to encode the information. The TX was designed and fabricated using UMC 0.13 micrometer CMOS technology. Measurement results and theoretical system level budgeting are presented for the proposed UWB TX
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