Decades of continuous scaling has reduced the energy of unit computing to virtually zero, while energy-efficient communication has remained the primary bottleneck in achieving fully energy-autonomous Internet-of-Things (IoT) nodes. This article presents and analyzes the tradeoffs between the energies required for communication and computation in a wireless sensor network, deployed in a mesh architecture over a 2400-acre university campus, and is targeted toward multisensor measurement of temperature, humidity and water nitrate concentration for smart agriculture. Several scenarios involving in-sensor analytics (ISA), collaborative intelligence (CI), and context-aware switching (CAS) of the cluster head during CI has been considered. A real-time co-optimization algorithm has been developed for minimizing the energy consumption in the network, hence maximizing the overall battery lifetime. Measurement results show that the proposed ISA consumes ≈ 467× lower energy as compared to traditional Bluetooth low energy (BLE) communication, and ≈ 69500× lower energy as compared with long-range (LoRa) communication. When the ISA is implemented in conjunction with LoRa, the lifetime of the node increases from a mere 4.3 h to 66.6 days with a 230-mAh coin cell battery, while preserving >99% of the total information. The CI and CAS algorithms help in extending the worst case node lifetime by an additional 50%, thereby exhibiting an overall network lifetime of ≈ 104 days, which is >90% of the theoretical limits as posed by the leakage current present in the system, while effectively transferring information sampled every second. A Web-based monitoring system was developed to continuously archive the measured data, and for reporting real-time anomalies.

The recent advancement of the Internet of Things (IoT) enables the possibility of data collection from diverse environments using IoT devices. However, despite the rapid advancement of low-power communication technologies, the deployment of IoT networks still faces many challenges. In this article, we propose a hybrid, low-power, wide-area network (LPWAN) structure that can achieve wide-area communication coverage and low-power consumption on IoT devices by utilizing both sub-GHz long-range radio and 2.4-GHz short-range radio. Specifically, we constructed a low-power mesh network with LoRa, a physical-layer standard that can provide long-range (kilometers) point-to-point communication using custom time-division multiple access (TDMA). Furthermore, we extended the capabilities of the mesh network by enabling ANT, an ultralow-power, short-range communication protocol to satisfy data collection in dense device deployments. Third, we demonstrate the performance of the hybrid network with two real-world deployments at the Purdue University campus and at the university-owned farm. The results suggest that both networks have superior advantages in terms of cost, coverage, and power consumption vis-à-vis other IoT solutions, like LoRaWAN.

This research paper presents the results of an explorative study to identify what concepts beginning students find challenging regarding semiconductors physics, diodes and transistors at an introductory electric circuits course. In order to prepare students for practically-important and application-relevant circuits and systems, there is a need to properly introduce semiconductors and solid-state electronics early in the electrical/computer engineering curriculum. Such concepts are not traditionally covered in the very first circuits course in most electrical/computer engineering programs. The purpose of this paper is to explore students' level of understanding of basic semiconductor physics, diodes, transistors and simple circuits that utilize such devices. To address the research purpose, we utilize a Design-Based Research (DBR) methodology. Design-Based Research is an iterative process where new theory is developed through applying research and theory to a specific educational problem, developing conjectures about the relationship between variables, testing and then revising educational intervention based on findings and then retesting. We analyze students' final exam scores (n=99) to determine which topics were most challenging and then qualitatively analyze students' work to explore common errors. As more Electrical and Computer Engineering (ECE) programs look to modernize their introductory courses to include topics of semiconductor physics and devices, this research can inform instructional and curricular interventions.

The transient response time and overshoot of an RF MEMS filter tuning membrane are enhanced in this work. For the first time, a dead-beat control is applied to the bias voltage of an underdamped RF MEMS membrane to achieve faster and smoother tuning. The presented method runs in real-time using a Digital Signal Processor (DSP). The parameters used by the DSP are extracted from the step response of the membrane during post-fabrication calibration. As a result, the presented methodology is systematic and immune to fabrication process variations. The presented methodology is applied on an MEMS membrane, used in tunable silicon RF filters, fabricated on an SOI wafer. Measured results show that the shaped bias voltage shortens the settling time (by 1.2–2.6x), and a significantly lowers the overshoot (by 8–60x) when compared to the voltage step response. The presented work does not require a feedback system, making it a feasible solution to embed in communication devices.

Tunable RF filters are essential components for the coming generation of communication systems. Amongst these, RF filters, tuned electrostatically or by piezoelectric actuators, have shown excellent performance in terms of tuning range and insertion loss. Those filters, however, require a wide dynamic range control voltage. Generating such voltages is a challenge due to power and size limitations. In this work, we present a variableoutput high-voltage charge-pump that can generate a suitable voltage for those filters. The presented improved Dickson chargepump has been simulated with the control part implemented in 130 nm RF-CMOS. The voltage tuning is controlled by a digital input, easing the integration of the charge-pump with other system components. The charge-pump can generate voltages from 0 V to 45 V. At the highest output voltage, the circuit consumes only 26 mW.

A technique to design analog signal-interference narrow-band bandpass filters by merging transmission lines and surface-acoustic-wave (SAW) resonators is reported in this work. By inserting one-/two-port SAW resonators into the transversal filtering sections (TFSs) of the signal-interference filter, narrowband filtering actions with remarkable electrical properties can be synthesized. The latter particularly refers to the untypically-high effective unloaded quality factor (Qu) associated with the generated bandpass filtering response given its fully-planar realization. This leads to perceptible benefits in terms of in-band transmission loss and occupied physical area when compared to a classic pure signal-interference filter design. Moreover, for a given type of SAW resonator, adjustable bandwidth and transmission zeros (TZs) can be produced to attain a large variety of high-selectivity filtering functions. For practical validation, a three-stage microstrip narrow-band bandpass filter with measured S-parameters of a 433.9-MHz one-port SAW resonator is shown. The spurious-mode effect of the measured SAW resonator, as a limiting factor in the overall filter performance, is also discussed.

Energy conservation is essential in Wireless Sensor Networks (WSNs) because of limited energy in nodes' batteries. Collaborative beamforming uses multiple transmitters to form antenna arrays; the electromagnetic waves from these antenna arrays can create constructive interferences at the receiver and increase the transmission distance. Each transmitter can use lower power and save energy, since the energy consumption is spread over multiple transmitters. Each beamforming transmission requires multiple collaborative transmitters. Repetitively using the same transmitters will deplete their energy and create coverage holes in the sensing area. To prevent holes, energy should be balanced by using different transmitters. This article investigates the factors that can affect the energy consumption and network lifetime when using beamforming. We present an algorithm for selecting the transmitters in order to prolong the network lifetime. Compared with an existing beamforming transmitters scheduling algorithm, our algorithm doubles the network lifetime. When compared with direct transmission or multihop transmissions towards a receiver far away from the sensing area, our approach can increase the network's lifetime substantially.

Collaborative beamforming is a transmission technique by using multiple transmitters to form antenna arrays and creating highly directional beams to a distant receiver. Collaborative beamforming can enhance energy efficiency in wireless sensor networks. However, the same information needs to be shared among the transmitters in advance. As a result, communication among the transmitters is required; this consumes energy and shortens the lifetime of the sensor network. In this paper, we propose a procedure for data sharing when multiple sensing nodes and multiple transmitters are used and examine the energy consumption for beamforming. We show that beamforming is energy-efficient when the sensor nodes are deployed far away from the base station and the energy consumed for data sharing has negligible effects on the network's lifetime.

A fast and power efficient phase difference and frequency offset estimation technique for collaborative beamforming in a wireless sensor network is presented. Common radio blocks are used to implement the phase difference estimation technique and we present an analytical expression for the phase difference estimation accuracy in an AWGN channel. The analysis including the effect of noise and multipath on the estimation accuracy shows the effectiveness of the proposed estimation technique for collaborative beamforming applications.

Energy conservation is essential in wireless sensor networks (WSNs) because of limited energy in batteries. Collaborative beamforming uses multiple transmitters to form antenna arrays; the electromagnetic waves from these antenna arrays can create constructive interferences at the receiver and increase the transmission distance. Each transmitter can use lower power and save energy, since the energy consumption is spread over multiple transmitters. However, if the same nodes are always used for collaborative beamforming, these nodes would deplete their energy much sooner and this sensing area will no longer be monitored. To avoid this situation, energy consumption for collaborative beamforming needs to be balanced over the whole network by assigning the transmitters in turns. The transmitters in each round are selected by a scheduler and the energy carried in each node is balanced to increase the number of transmissions. We define the lifetime of a network as the number of transmissions until a certain percentage of the nodes depletes their energy. This paper proposes an algorithm to calculate energy-efficient schedules based on the remaining energy and the phase differences of their signals arriving at the receiver. Compared with an existing algorithm, our algorithm can extend the network lifetime by more than 60%.

Reducing energy consumption is critical for wireless sensor networks. The dominant factor is the energy for data transmission. Collaborative beamforming can save transmission energy by improving the directivity of electromagnetic waves so that the signal at the receiver is stronger. Compared with a single transmitter, collaborative beamforming spreads the long distance transmission energy over multiple transmitters. This balances the battery lifetime on individual nodes because each transmitter can use lower power. However, beamforming depends on proper coordination of phases among the participating sensor nodes. This requires communication among the sensor nodes and consumes energy. This paper investigates whether the transmission energy can be saved by using beamforming based on the number of nodes and the total size of data needed to transmit. We determine the minimum size of data to balance the communication overhead when given the total number of nodes.

Energy-efficient broadcast communication is an important problem in wireless ad hoc networks. Previously, minimum-energy broadcast that exploits the broadcast nature of radio transmission has been studied and shown to be NP-complete for omnidirectional antennas. In this paper, we investigate the minimum-energy broadcast problem under a wide spectrum of directional antenna models, including sectored antennas with fixed sectors and beamwidth and antenna array-based smart antennas with varying degrees of beam orientation and beamwidth. We first propose the RF design and implementation of each model, which suggests the practical parameters of antennas under that model. We then show that the minimum-energy broadcast problem under each of the antenna models is NP-complete. Lastly, we present a heuristic algorithm based on BIP for the above problem under each directional antenna model and experimentally compare the energy efficiency of using different directional antennas using these heuristics. Our results show that using antennas with adjustable orientation and variable beamwidth gives the best results. For such antennas, the scanning angle is the dominant factor in improving the quality of the broadcast trees. The number of antennas per node is not that critical to obtaining a better broadcast tree as long as it is large enough to cover the entire 360◦ around a node so as to prevent network partitioning.

Wireless mesh networks (WMNs) have been proposed as an effective solution for ubiquitous last-mile broadband access. Three key factors that affect the usability of WMNs are high throughput, cost-effectiveness, and ease of deployability. In this paper, we propose DMesh, a WMN architecture that combines spatial separation from directional antennas with frequency separation from orthogonal channels to improve the throughput of WMNs. DMesh achieves this improvement without inhibiting cost-effectiveness and ease of deployability by utilizing practical directional antennas that are widely and cheaply available (e.g., patch and yagi) in contrast to costly and bulky smart beamforming directional antennas. Thus, the key challenge in DMesh is to exploit spatial separation from such practical directional antennas despite their lack of electronic steerability and interference nulling, as well as the presence of significant sidelobes and backlobes. In this paper, we study how such practical directional antennas can improve the throughput of a WMN. Central to our architecture is a distributed, directional channel assignment algorithm for mesh routers that effectively exploits the spatial and frequency separation opportunities in a DMesh network. Simulation results show that DMesh improves the throughput of WMNs by up to 231% and reduces packet delay drastically compared to a multiradio multichannel omni antenna network. A DMesh implementation in our 16-node 802.11b WMN testbed using commercially available practical directional antennas provides transmission control protocol throughput gains ranging from 31% to 57%