Single-antenna Sensors Research Articles

Facile E-nose based on single antenna and graphene oxide for sensing volatile organic compound gases with ultrahigh selectivity and accuracy

Volatile organic compounds (VOCs) gases exist as important indicators in various processes such as human breath, food spoilage, plant disease, and industrial production, which makes VOC sensing a promising nondestructive detection method. Nanomaterial enabled electronic noses (e-noses) are gaining increasing attention for their exceptional ability to distinguish between multiple VOCs. To achieve this, multiple sensors with distinct nanomaterials are crucial for providing enough diversity for successful discrimination. Apparently if e-nose can be implemented solely on single sensor with single common nanomaterial operating at room temperature, the complexity and power consumption can be greatly decreased. In this study, a significant milestone is achieved as, for the first time, a single antenna sensor coated with commercial graphene oxide, demonstrates comparable performance to array-based e-noses, and even outperforms them in terms of the ultimate ambition of selectivity—isomeric VOC classification. An impressive classification accuracy of 96.7 % is attained for multiple VOC gases, including isomers. Additionally, the concentration of each component in VOC isomer mixtures is accurately determined. Unlike conventional antenna sensors, the sensor maintains stable communication during sensing operations. Finally, the practical feasibility of the antenna e-nose (Ant-nose) is successfully demonstrated with a series of food quality assessments.

A Novel Energy Efficient Harvesting Technique for SDWSN using RF Transmitters with MISO Beamforming

Software Defined Wireless Sensor Networks (SDWSN) is emerged to overcome the additional energy consumption in WSN. Even then the sensor nodes in the SDWSN suffer from scarce battery resources. Generally, the Radio Frequency (RF) transmitters are deployed around the base station in the SDWSN to overcome the high energy consumption problem. To enhance harvesting energy and coverage of nodes in the network, a new energy harvesting technique using RF transmitters with Multiple Input and Single Output (MISO) beamforming is proposed. In this method, multiple antenna RF transmitters and single antenna sensor nodes are deployed. The optimization problem subject to Signal to Noise Ratio (SNR) and energy harvesting constraints is formulated for hybrid beamforming design to reduce the transmit power in the network. The optimization problem based on convex Second Order Cone Programming (SOCP) is derived to get the optimal solution for hybrid beamforming design. The beamforming technique is used to steer the beam in the desired direction and null to the other direction improves the energy harvesting. The simulation results show that the proposed technique provides better average harvesting energy, average transmit power, average residual energy and throughput than the existing RF transmitter based energy harvesting methods.

Single Transmitter Direction Finding Using a Single Moving Omnidirectional Antenna

Traditional direction-finding systems are based on processing the outputs of multiple spatially separated antennas. The impinging signal Angle-of-Arrival (AOA) is estimated using the relative phase and amplitude of the multiple outputs that are sampled simultaneously. Here, we explore the potential of a single moving antenna to provide useful direction finding of a single transmitter. If the transmitted signal frequency is steady enough during the collection of data, a single antenna can be moved while tracking the phase changes to provide an Angle-of-Arrival measurement. The advantages of a single-antenna sensor include the sensor size, the lack of a need for multiple-receiver synchronization in time and frequency, the lack of mutual antenna coupling, and the cost of the system. However, a single-antenna sensor requires an accurate knowledge of its position during the data collection and it is challenged by transmitter phase instability, signal modulation, and transmitter movement during the measurement integration time. We analyze the performance of the proposed sensor, support the analysis with simulations and finally, present measurements performed by hardware configured to check the validity of the proposed single-antenna sensor.

Long-Term Energy Consumption and Transmission Delay Tradeoff in Wireless-Powered Body Area Networks

In this article, we investigate the long-term energy consumption and transmission delay (EC-TD) tradeoff in a wireless-powered body area network that consists of a multiantenna hybrid access point and a number of single-antenna sensor nodes (SNs). The beamforming technique and the simultaneous wireless information and power transfer (SWIPT) technique are adopted. Each SN is equipped with a battery and data buffer for storing harvested energy and sensory data. The long-term energy consumption minimization problem is addressed subject to the constraint of transmission delay. Meanwhile, the residual energy constraints of SNs are considered, which enable the setting up of the available energy of the SNs according to requirements. By employing the Lyapunov optimization theory, the original stochastic optimization problem is transformed into an equivalent instantaneous nonconvex problem in which the long-term EC-TD tradeoff can be adjusted using a system control parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> . A joint power and time allocation scheme is then proposed to solve this instantaneous problem. Moreover, based on the derived upper bounds of the long-term energy consumption and data buffer length, we reveal that the proposed resource allocation scheme achieves an EC-TD tradeoff as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$[\mathcal {O}(1/V),\mathcal {O}(V)]$ </tex-math></inline-formula> . Since the value of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> can be adjusted to achieve different energy consumption and transmission delay, the flexibility and applicability of the proposed scheme are enhanced. The simulation results validate the theoretical analysis and verify the effectiveness of the proposed scheme.

Design of a Novel Wideband Leaf-Shaped Printed Dipole Array Antenna Using a Parasitic Loop for High-Power Jamming Applications.

This paper proposes a novel wideband leaf-shaped printed dipole antenna sensor that uses a parasitic element to improve the impedance matching bandwidth characteristics for high-power jamming applications. The proposed antenna sensor consists of leaf-shaped dipole radiators, matching posts, rectangular slots, and a parasitic loop element. The leaf-shaped dipole radiators are designed with exponential curves to obtain a high directive pattern and are printed on a TLY-5 substrate for high-power durability. The matching posts, rectangular slots, and a parasitic loop element are used to enhance the impedance matching characteristics. The proposed antenna sensor has a measured fractional bandwidth of 66.7% at a center frequency of 4.5 GHz. To confirm the array antenna sensor characteristics, such as its active reflection coefficients (ARCs) and beam steering gains, the proposed single antenna sensor is extended to an 11 × 1 uniform linear array. The average values of the simulated and measured ARCs from 4.5 to 6 GHz are −13.4 dB and −14.7 dB. In addition, the measured bore-sight array gains of the co-polarization are 13.4 dBi and 13.7 dBi at 4 GHz and 5 GHz, while those of the cross-polarizations are −4.9 dBi and −3.4 dBi, respectively. When the beam is steered at a steering angle, θ0, of 15°, the maximum measured array gains of the co-polarization are 12.2 dBi and 10.3 dBi at 4 GHz and 5 GHz, respectively.

Massive MIMO-Based Distributed Signal Detection in Multi-Antenna Wireless Sensor Networks.

For massive multiple-input multiple-output (MIMO) distributed wireless sensor networks, this paper investigates the role of multi-antenna sensors in improving network perception performance. First, we construct a distributed multi-antenna sensor network based on massive MIMO. By using the anti-fading characteristics of multi-antennas, it is better to achieve accurate detection than the single-antenna sensor network. Based on this, we derive a closed-loop expression for the detection probability of the best detector. Then, we consider the case that the sensor power resources are limited, and thus we want to use finite power to achieve higher detection probability. For this reason, the power was optimized by the alternating direction method of multipliers (ADMM). Moreover, we also prove that only statistical channel state is needed in large-scale antenna scenarios, which avoid the huge overhead of channel state information. Finally, according to the simulation results, the multi-antenna sensor network has better detection performance than the single-antenna sensor network which demonstrates the improved performance of the proposed schemes and also validates the theoretical findings.

Minimizing Age of Information in Energy Harvesting Wireless Sensor Networks

We consider the uplink of an energy harvesting (EH) wireless sensor network (WSN) where N single-antenna sensors communicate with a common fusion center (FC) with the aim of cooperatively minimizing the overall average age of information (AoI). Specifically, we propose new resource allocation algorithms to minimize the average AoI in an EH-WSNs employing common multiple-access schemes, in particular time-division multiple access (TDMA) and frequency-division multiple access (FDMA). To this end, we take advantage of the convexity of the derived AoI, enabling an optimal resource block assignment, implemented as a greedy algorithm for TDMA systems and in the form of an alternating direction method of multipliers (ADMM) scheme for FDMA systems. The optimality of the greedy resource allocation scheme derived for the TDMA case is obtained by design, whereas that of the ADMM-based method derived for the FDMA case is demonstrated numerically. Simulation results indicate that the choice between TDMA or FDMA depends on the available resources, size of the data packet, and the time of packet observation in the system.

Noncoherent Distributed Beamforming in Decentralized Two-Way Relay Networks

Many noncoherent distributed strategies for cooperative sensor networks that do not require channel knowledge at any antenna to overcome the overhead involved in channel estimation are lately suggested; however, these strategies suffer from low system performance in terms of bit error rate (BER) and a comparably high decoding complexity. Differential beamforming strategies have recently been proposed to overcome these problems; however, they are implemented using the four-phase protocol. Thus, we propose a new strategy based on the three-phase protocol to increase the symbol rate. By doing this, a significant improvement can be achieved in the overall system performance. Hence, in this article, a new bidirectional differential beamforming strategy is suggested: 1) to be applied on the three-phase protocol instead of the four-phase protocol; 2) to be applicable for a decentralized wireless sensor network using single-antenna sensors distributed randomly between the communicating base stations; 3) to enjoy low decoding complexity; and 4) to improve the network performance in terms of BER by maximizing the received signal-to-noise ratio at the receiving base station without requiring channel knowledge at any antenna in the whole network. From our simulation results, the proposed strategy shows a substantially improved BER performance compared with the current state-of-the-art ones.

An Efficient Algorithm for Unit-Modulus Quadratic Programs With Application in Beamforming for Wireless Sensor Networks

In this letter, we consider a network of single-antenna sensors that aim at the estimation of an unknown deterministic parameter. The sensors collect the observations and forward them to a fusion center via applying a phase-only beamforming weight. The derivation of the optimal beamforming weights requires the solution of a unit-modulus quadratic program (UQP), which in the relevant literature is solved via the semidefinite relaxation (SDR) technique or via a variation of the analytic constant modulus algorithm. The former achieves better performance, though it exhibits high computational cost that increases drastically with the number of sensors. The latter requires much less complexity, though it achieves worse performance. To that end, we propose an efficient algorithm for the solution of UQPs based on the alternating direction method of multipliers. The new approach achieves almost identical performance to that of the SDR-based approach while exhibiting significantly reduced computational complexity. The convergence of the proposed algorithm to a Karush-Kuhn-Tucker point is theoretically studied, and its effectiveness is verified via numerical results.

Massive MIMO for Distributed Detection With Transceiver Impairments

This paper investigates an issue of massive MIMO-based distributed detection that considers transceiver hardware impairments at both a massive-antenna fusion center (FC) and multiple single-antenna sensors. First, we derive closed-form expressions of the probability of detection and the probability of false alarm, and show that hardware impairments create finite ceilings on the achievable detection performance. Then, we formulate a constrained optimization problem as sum of linear ratios programming to maximize the detection probability. By exploiting the inherent problem structures, we further develop an algorithm based on the alternating direction method of multipliers. Extensive simulations demonstrate that the nonideal hardware has a fundamental impact on the distributed detection performance. More specifically, in the limit of an infinite number of antennas and infinite sensor reporting power budget, the effects of FC impairment and FC receiver noise vanish, while the sensor impairment dominates the achievable distributed detection performance.

Energy-Efficient Design of MIMO Processing for Two-Tier Wireless Sensor Networks

This letter studies the energy-efficient design of linear processing strategies for a wireless sensor network consisting of two-tier wireless links. In the system, a set of single-antenna sensor nodes sense the information of interest and report the sensed data to a fusion center (FC) through a set of relay nodes. It is assumed that the FC and relay nodes are equipped with multiple antennas and the sensors-to-relays and the relays-to-FC channels are separated in frequency or time domain. Motivated by the observation that remote sensors tend to be equipped with limited battery life, this letter tackles the problem of maximizing the minimum of the energy efficiency metrics of the sensors while satisfying the per-sensor and per-relay transmit power constraints under compress-and-forward relaying strategy at the relays. Numerical results validate the advantages of the proposed energy-efficient design as compared to the conventional spectrally efficient scheme.

Energy efficient cooperative spectrum sensing in wireless multi-antenna sensor network

This paper will address sensor selection problem for spectrum sensing in a cognitive radio network. The sensor's limited energy is an important issue which has attracted more attention in recent years. An energy efficient cooperative spectrum sensing will hereby be proposed when multi-antenna sensors are used. Two decision-making techniques are utilized for the combination of antennas' signals in each sensor: hard and soft decision-making. OR rule is used for hard decision-making technique while selection combining, equal gain combining and maximum ratio combining (MRC) are used for the soft one. In each combination scheme, the sensor selection is a problem by means of which both the energy consumption is minimized and the detection performance gets satisfied. The problem is solved based on the standard convex optimization method. Simulation results show the achievement of a significant energy saving compared to the networks using single-antenna sensors specifically in low signal to noise ratio state. Among all methods, MRC combining enjoys the least energy consumption, as well; it satisfies the desired detection performance.

A distributed localization in wireless sensor networks utilizing AOD estimation and synthetical uniform circular array

The localization of wireless sensor nodes is one of the key technologies in wireless sensor networks (WSN). Recently, a distributed localization method has been proposed based on a novel concept of angle of departure (AOD) estimation, which can be employed by e.g., the single antenna sensors to estimate the angle information and achieve localization. Based on the AOD estimation, in this paper, we introduce a synthetic uniform circular array (SUCA) synthesized by a rotary antenna on anchor to get the distributed localization of the sensors in multi-path environments. The rotated operation of antenna could create the SUCA with a larger aperture to deal with AOD of multipath components (MPCs) and relax the condition that array aperture should be greater than the number of MPCs. This new localization method only relies on radio transceivers without requiring extra measuring equipments, and the sensor nodes conduct localization in a completely distributed manner instead of centralized processing, which is suitable for large-scale WSN. Meanwhile, the influence of carrier frequency offset (CFO) between the transceivers is also considered and it is eliminated by utilizing the signal emitted from an auxiliary antenna.

Co-UWSN: Cooperative Energy-Efficient Protocol for Underwater WSNs

Sensor networks feature low-cost sensor devices with wireless network capability, limited transmit power, resource constraints, and limited battery energy. Cooperative routing exploits the broadcast nature of wireless medium and transmits cooperatively using nearby sensor nodes as relays. It is a promising technique that utilizes cooperative communication to improve the communication quality of single-antenna sensor nodes. In this paper, we propose a cooperative transmission scheme for underwater sensor networks (UWSNs) to enhance the network performance. Cooperative diversity has been introduced to combat fading. Cooperative UWSN (Co-UWSN) is proposed, which is a reliable, energy-efficient, and high throughput routing protocol for UWSN. Destination and potential relays are selected that utilize distance and signal-to-noise ratio computation of the channel conditions as cost functions. This contributes to sufficient decrease in path losses occurring in the links and transferring of data with much reduced path loss. Simulation results show that Co-UWSN protocol performs better in terms of end-to-end delay, energy consumption, and network lifetime. Selected protocols for comparison are energy-efficient depth-based routing (EEDBR), improved adaptive mobility of courier nodes in threshold-optimized depth-based routing (iAMCTD), cooperative routing protocol for UWSN, and cooperative partner node selection criteria for cooperative routing Coop (Re and dth).

ARCUN: Analytical Approach towards Reliability with Cooperation for Underwater WSNs

Cooperative routing is a hybrid approach utilizing routing techniques and cooperative communication to improve the communication quality of single-antenna sensor nodes. It exploits the broadcast nature of wireless medium and transmits cooperatively using nearby sensor nodes as relays. In this research, a cooperative transmission scheme is proposed for UnderWater Sensor Networks (UWSNs) to improve the network performance called ARCUN. The protocol is an energy-efficient and high-throughput routing scheme for UWSN. Potential relays are selected from a group of neighbor nodes that utilize signal-to-noise ratio and distance computation of the underwater channel. Optimal role of cooperation provides load balancing in the network and gives profound improvement in network stability period and packet delivery ratio.

MMW Sensor for Hidden Targets Detection and Warning Based on Reflection/Scattering Approach

An antenna sensor for millimeter wave (MMW) hidden target detection and warning applications is introduced. The sensor consists of three adjacent high gain microstrip/horn hybrid antenna elements. The central antenna acts as bi-static radar, while the two side antennas are used to receive the scattered back signals from a hidden object. The proposed antenna sensor has been employed in a detection/imaging system prototype based on time domain reflectometry (TDR). A very short pulse generated by a vector network analyzer is used to illuminate a three layers body model made from cotton, natural leather and reinforced papers. The model construction is chosen to emulate the presence of human body. Experimental scanning of a hidden metallic target has been conducted for three different orientations of the target. Compared to a single antenna sensor, the triple sensor shows a great enhancement in the detection ability and the constructed image resolution of a hidden target.

A Cooperative MIMO Framework for Wireless Sensor Networks

We explore the use of cooperative multi-input multi-output (MIMO) communications to prolong the lifetime of a wireless sensor network (WSN). Single-antenna sensor nodes are clustered into virtual antenna arrays that can act as virtual MIMO (VMIMO) nodes. We design a distributed cooperative clustering protocol (CCP), which exploits VMIMO's diversity gain by optimally selecting the cooperating nodes (CNs) within each cluster and balancing their energy consumption. The problem of optimal CN selection at the transmit and receive clusters is formulated as a nonlinear binary program. Aiming at minimizing the imbalance in the residual energy at various nodes, we decompose this problem into two subproblems: finding the optimal number of CNs (ONC) in a cluster and the CN assignment problem. For the ONC problem, we first analyze the energy efficiency of two widely used VMIMO methods: distributed Space Time Block Code (DSTBC) and distributed Vertical-Bell Laboratories-Layered-Space-Time (DVBLAST). Our analysis provides an upper bound on the optimal number of CN nodes, which greatly reduces the computational complexity of the ONC problem. The second subproblem is addressed by assigning CNs based on the residual battery energy. To make CCP scalable to large WSNs, we propose a multihop energy-balanced routing mechanism for clustered WSNs (C-EBR) with a novel cost metric. Finally, we derive sufficient conditions on the intra- and intercluster ranges, under which CCP guarantees connectivity of the intercluster topology. Extensive simulations show that the proposed approach dramatically improves the network lifetime.

Estimation in Phase-Shift and Forward Wireless Sensor Networks

We consider a network of single-antenna sensors that observe an unknown deterministic parameter. Each sensor applies a phase shift to the observation and the sensors simultaneously transmit the result to a multi-antenna fusion center (FC). Based on its knowledge of the wireless channel to the sensors, the FC calculates values for the phase factors that minimize the variance of the parameter estimate, and feeds this information back to the sensors. The use of a phase-shift-only transmission scheme provides a simplified analog implementation at the sensor, and also leads to a simpler algorithm design and performance analysis. We propose two algorithms for this problem, a numerical solution based on a relaxed semidefinite programming problem, and a closed-form solution based on the analytic constant modulus algorithm. Both approaches are shown to provide performance close to the theoretical bound. We derive asymptotic performance analyses for cases involving large numbers of sensors or large numbers of FC antennas, and we also study the impact of phase errors at the sensor transmitters. Finally, we consider the sensor selection problem, in which only a subset of the sensors is chosen to send their observations to the FC.

AOD estimation in WSN localization system with synthetic aperture technique

Angel of departure (AOD) based distributed localization scheme in wireless sensor networks allows the single antenna sensor node to estimate its own AOD information by an equivalent antenna array for further position calculation. However, the condition that the number of antennas at the multi-antenna agent/anchor node should be larger than the number of multipath signal components (MPCs) constrains its actual application. In this paper, we provide a more practical approach to achieve AOD information estimation under multipath environment. Given that the sensor node can not identify the line of sight (LOS) signal component due to the insufficient degree of freedom, which is determined by the above limiting condition, we introduce a synthetic aperture technique with the aid of a fast moving multi-antenna agent/anchor node. This operation greatly enlarges the degree of freedom of the equivalent antenna array constructed at sensor node end but without requiring other extra physical antennas equipped at agent/anchor node or sensor node end, which means that it relaxes the limiting condition. Therefore, the AOD information of LOS signal component can be estimated and extracted successfully in complex multipath environment. Theoretical analysis proves the effectiveness of our proposed synthetic aperture technique and numerical simulations show great performance improvement.