In this paper, we focus on two-layer wireless sensor networks (WSNs) that consist of sensor-concentrator and inter-concentrator networks. In order to collect as much data as possible from a wide area, improving of network capacity is essential because data collection applications often require to gather data within a limited period, i.e., acceptable collection delay. Therefore, we propose a two-stage scheduling method for inter-concentrator networks. The proposed method first strictly schedules time slots of links with heavy interference and congestion by exploiting the combination metric of interference and traffic demand. After that, it simply schedules time slots of the remaining sinks to mitigate complexity. Simulation-based evaluations show our proposal offers much larger capacity than conventional scheduling algorithms. In particular, our proposal improves up to 70% capacity compared with the conventional methods in situations where the proportion of one- and two-hop links is small.

In wireless sensor networks, the on-off attacker nodes can present good behaviors and then opportunistically and selectively behave badly to compromise the network. Such misbehaving nodes are usually difficult to be spotted by the network system in a short term. To address this issue, in this study, we propose a reputation scheme to mitigate the on-off attack. In addition, a penalty module is properly designed so that the reputation scheme can effectively respond to the on-off misbehaviors and make such nodes quickly detected by the system, hence the minimization of their influence. We confirm the feasibility and effectiveness of the proposed scheme through simulation tests.

A number of battery-driven sensor nodes are deployed to operate a wireless sensor network, and many routing protocols have been proposed to reduce energy consumption for data communications in the networks. We have proposed a new routing policy which employs a nearest-neighbor forwarding based on hop progress. Our proposed routing method has a topology parameter named forwarding angle to determine which node to connect with as a next-hop, and is compared with other existing policies to clarify the best topology for energy efficiency. In this paper, we also formulate the energy budget for networks with the routing policy by means of stochastic-geometric analysis on hop-count distributions for random planar networks. The formulation enables us to tell how much energy is required for all nodes in the network to forward sensed data in a pre-deployment phase. Simulation results show that the optimal topology varies according to node density in the network. Direct communication to the sink is superior for a small-sized network, and the multihop routing is more effective as the network becomes sparser. Evaluation results also demonstrate that our energy formulation can well approximate the energy budget, especially for small networks with a small forwarding angle. Discussion on the error with a large forwarding angle is then made with a geographical metric. It is finally clarified that our analytical expressions can obtain the optimal forwarding angle which yields the best energy efficiency for the routing policy when the network is moderately dense.

Wireless sensor networks usually deploy sensor nodes with limited energy resources in unattended environments so that people have difficulty in replacing or recharging the depleted devices. In order to balance the energy dissipation and prolong the network lifetime, this paper proposes a routing spanning tree-based clustering algorithm (RSTCA) which uses routing spanning tree to analyze clustering. In this study, the proposed scheme consists of three phases: setup phase, cluster head (CH) selection phase and steady phase. In the setup phase, several clusters are formed by adopting the K-means algorithm to balance network load on the basis of geographic location, which solves the randomness problem in traditional distributed clustering algorithm. Meanwhile, a conditional inter-cluster data traffic routing strategy is created to simplify the networks into subsystems. For the CH selection phase, a novel CH selection method, where CH is selected by a probability based on the residual energy of each node and its estimated next-time energy consumption as a function of distance, is formulated for optimizing the energy dissipation among the nodes in the same cluster. In the steady phase, an effective modification that counters the boundary node problem by adjusting the data traffic routing is designed. Additionally, by the simulation, the construction procedure of routing spanning tree (RST) and the effect of the three phases are presented. Finally, a comparison is made between the RSTCA and the current distributed clustering protocols such as LEACH and LEACH-DT. The results show that RSTCA outperforms other protocols in terms of network lifetime, energy dissipation and coverage ratio.

Streaming services that use TCP have increased; however, throughput is unstable due to congestion control caused by packet loss when TCP is used. Thus, TCP control to secure a required transmission rate for streaming communication using Forward Error Correction (FEC) technology (TCP-AFEC) has been proposed. TCP-AFEC can control the appropriate transmission rate according to network conditions using a combination of TCP congestion control and FEC. However, TCP-AFEC was not developed for wireless Local Area Network (LAN) environments; thus, it requires a certain time to set the appropriate redundancy and cannot obtain the required throughput. In this paper, we demonstrate the drawbacks of TCP-AFEC in wireless LAN environments. Then, we propose a redundancy setting method that can secure the required throughput for FEC, i.e., TCP-TFEC. Finally, we show that TCP-TFEC can secure more stable throughput than TCP-AFEC.

Real-time and reliable radio communication is essential for wireless control systems (WCS). In WCS, preambles create significant overhead and affect the real-time capability since payloads are typically small. To shorten the preamble transmission time in OFDM systems, previous works have considered adopting either time-direction extrapolation (TDE) or frequency-direction interpolation (FDI) for channel estimation which however result in poor performance in fast fading channels and frequency-selective fading channels, respectively. In this work, we propose a subcarrier-selectable short preamble (SSSP) by introducing selectability to subcarrier sampling patterns of a preamble such that it can provide full sampling coverage of all subcarriers with several preamble transmissions. In addition, we introduce adaptability to a channel estimation algorithm for the SSSP so that it conforms to both fast and frequency-selective channels. Simulation results validate the feasibility of the proposed method in terms of the reliability and real-time capability. In particular, the SSSP scheme shows its advantage in flexibility as it can provide a low error rate and short communication time in various channel conditions.

By exploiting the reciprocity and randomness properties of wireless channels, physical-layer-based key generation provides a stable secrecy channel even when the main channel suffers from a bad condition. Even though the channel variation due to the mobility of nodes in wireless channels provides an improvement of key generation rate (KGR), it decreases the key consistency probability (KCP) between the node pairs. Inspired by the received signal strength(RSS)-angle of arrival(AoA)-based geolocation research, in this work, we analyze the performance of the key extraction using the RSS and AoA. We aim to identify a way to utilize the high KGR of the AoA-based method to overcome the major drawback of having a low KGR in the most common RSS-based scheme. Specifically, we derive the KCP and KGR of the RSS-AoA-based key generation scheme. Further, we propose a new performance metric called effective key generation rate (EKGR), to evaluate the designed key generation scheme in practical scenarios. Finally, we provide numerical results to verify the accuracy of the presented theoretical analysis.

To suppress intercell interference for three-cell half-duplex relay systems, joint interference suppression and multiuser detection (MUD) schemes that estimate weight coefficients by the recursive least-squares (RLS) algorithm have been proposed but show much worse bit error rate (BER) performance than maximum likelihood detection (MLD). To improve the BER performance, this paper proposes a joint interference suppression and MUD scheme that estimates the weight coefficients by eigenvalue decomposition. The proposed scheme carries the same advantages as the conventional RLS based schemes; it does not need channel state information (CSI) feedback while incurring much less amount of computational complexity than MLD. In addition, it needs to know only two out of three preambles used in the system. Computer simulations of orthogonal frequency-division multiplexing (OFDM) transmission under three-cell and frequency selective fading conditions are conducted. It is shown that the eigendecomposition-based scheme overwhelmingly outperforms the conventional RLS-based scheme although requiring higher computational complexity.

This paper focuses on underwater wireless power transfer with electric coupling. First, the maximum available efficiency is derived by using the S-parameters of the parallel plate coupler. The frequency which represents the maximal value of the efficiency is revealed. Further, the elevation in the efficiency in association with a reduction of the electrode size is found. It is clarified that the elevation depends on the characteristic of the water dielectric loss. From these results, the optimal electrode size that obtains the maximal value of the efficiency is provided. Finally, we fabricate the couplers by utilizing the optimal frequency and the electrode size. The efficiency of 75.8% under water is achieved.

In this paper, we applied cavity resonator wireless power transfer (CR WPT) to an enclosed space with scatterers and revealed that high transfer efficiency at line-of-sight (LOS) and non-line-of-sight (NLOS) position in the power transmitter can be achieved by this method. In addition, we propose a method for limiting the wireless power transfer space utilizing metal mesh and show its effectiveness by experiment. First, we confirm that the constructed experimental model is working as a cavity resonator by theoretical formula and electromagnetic field analysis. Next, we calculate the maximum power transfer efficiency using a model including a plurality of scatterers by installing a power receiver at LOS and NLOS positions in the power transmitter, and it was confirmed that transfer efficiency of 30% or more could be expected even at the NLOS position. Then, we measured the frequency characteristics of a model in which one surface of the outer wall was replaced with a metal mesh, and it was clarified that the characteristics hardly changed in the power transfer frequency band. Finally, we confirmed that simultaneous communication can be performed with driving of the battery-less sensor by CR WPT, and clarify effectiveness of the proposed method.

Wireless Ad hoc networks have been rapidly developed in recent years since they promise a wide range of applications. However, their structures, which are based on the IEEE 802.11 standard, cause a severe unfairness problem in bandwidth sharing among different users. This is an extreme drawback because in wireless ad hoc networks, all users need to be treated fairly regardless of their geographical positions. In this paper, we propose a method to improve the fairness among flows by sensing channel access of other nodes based on the information obtained at the link layer and then, controlling the packet sending rate from the link layer to the MAC layer and the dequeue rate from the queue. Simulation results show that the proposed method achieves a better fairness with a good total throughput compared to conventional methods.

We developed a 5.8 GHz power-variable phase-controlled magnetron (PVPCM) which controls the phase of magnetron output by a phase shifter and controls the power by the anode current of the magnetron. This method is different from the previous 2.45 GHz phase-controlled magnetron which utilizes an injection method and a phase locked loop by the anode current, since the frequency of 5.8 GHz magnetron hardly changes with the anode current. Our experiments show that the developed 5.8 GHz PVPCM had a variable output power with 1% power stability from 160 W to 329 W, the phase accuracy was nearly ±1°, and the response time was less than 100 µs. Stable output power, high phase-controlled accuracy, and fast response speed microwave sources based on the PVPCMs are suitable for phased array system for wireless power transfer.

The IEEE 802.11 wireless local area network (WLAN) is the most widely deployed communication standard in the world. Currently, the IEEE 802.11ax draft standard is one of the most advanced and promising among future wireless network standards. However, the suggested uplink-OFDMA (UL-OFDMA) random access method, based on trigger frame-random access (TF-R) from task group ax (TGax), does not yet show satisfying system performance. To enhance the UL-OFDMA capability of the IEEE 802.11ax draft standard, we propose a centralized contention-based MAC (CC-MAC) and describe its detailed operation. In this paper, we analyze the performance of CC-MAC by solving the Markov chain model and evaluating BSS throughput compared to other methods, such as DCF and TF-R, by computer simulation. Our results show that CC-MAC is a scalable and efficient scheme for improving the system performance in a UL-OFDMA random access situation in IEEE 802.11ax.

Since the sensor nodes are subject to faults due to the highly-constrained resources and hostile deployment environments, fault management in wireless sensor networks (WSNs) is essential to guarantee the proper operation of networks, especially routing. In contrast to existing fault management methods which mainly aim to be tolerant to faults without considering the fault type, we propose a novel efficient fault-aware routing method where faults are classified and dealt with accordingly. More specifically, we first identify each fault and then try to set up the new routing path according to the fault type. Our proposed method can be easily integrated with any kind of existing routing method. We show that our proposed method outperforms AODV, REAR, and GPSR, which are the representative works of single-path routing, multipath routing and location based routing, in terms of energy efficiency and data delivery ratio.

Efficient use of heterogeneous wireless access networks is necessary to maximize the capacity of the 5G mobile communications system. The wireless local area networks (WLANs) are considered to be one of the key wireless access networks because of the proliferation of WLAN-capable mobile devices. However, throughput starvation can occur due to the well-known exposed/hidden terminal problem in carrier sense multiple access with collision avoidance (CSMA/CA) based channel access mechanism, and this problem is a critical issue with wireless LAN systems. This paper proposes two novel schemes to identify starved access points (APs) and user equipments (UEs) which throughputs are relatively low. One scheme identifies starved APs by observing the transmission delay of beacon signals periodically transmitted by APs. The other identifies starved UEs by using the miscaptured beacon signals ratio at UEs. Numerous computer simulations verify that that the schemes can identify starved APs and UEs having quite low throughput and are superior to the conventional graph-based identification scheme. In addition, AP and UE management with the proposed schemes has the potential to improve system throughput and reduce the number of low throughput UEs.

Many basic tasks in Wireless Sensor Networks (WSNs) rely heavily on the availability and accuracy of target locations. Since the number of targets is usually limited, localization benefits from Compressed Sensing (CS) in the sense that measurements can be greatly reduced. Though some CS-based localization schemes have been proposed, all of these solutions make an assumption that all targets are located on a pre-sampled and fixed grid, and perform poorly when some targets are located off the grid. To address this problem, we develop an adaptive dictionary algorithm where the grid is adaptively adjusted. To achieve this, we formulate localization as a joint parameter estimation and sparse signal recovery problem. Additionally, we transform the problem into a tractable convex optimization problem by using Taylor approximation. Finally, the block coordinate descent method is leveraged to iteratively optimize over the parameters and sparse signal. After iterations, the measurements can be linearly represented by a sparse signal which indicates the number and locations of targets. Extensive simulation results show that the proposed adaptive dictionary algorithm provides better performance than state-of-the-art fixed dictionary algorithms.

This letter considers a backscatter assisted wireless powered communication network (BAWPCN) with non-orthogonal multiple access (NOMA). This model consists of a hybrid access point (HAP) and multiple users which can work in either backscatter or harvest-then-transmit (HTT) protocol. To fully exploit time for information transmission, the users working in the backscatter protocol are scheduled to reflect modulated signals during the first phase of the HTT protocol which is dedicated for energy transfer. During the second phase, all users working in the HTT protocol transmit information to the HAP simultaneously since NOMA is adopted. Considering both short-term and long-term optimization problems to maximize the system throughput, the optimal resource allocation policies are obtained. Simulation results show that the proposed model can significantly improve the system performance.

This paper presents a capacitor-loaded 4x4 planar loop array for three-dimensional near-field beamforming of magnetic resonance wireless power transfer (WPT). This planar loop array provides three important functions: beamforming, selective power transfer, and the ability to work alignment free with the receiver. These functions are realized by adjusting the capacitance of each loop. The optimal capacitance of each loop that corresponds to the three functions can be found using a genetic algorithm (GA); the three functions were verified by comparing simulations and measurements at a frequency of 6.78MHz. Finally, the beamforming mechanism of a near-field loop array was investigated using the relationship between the current magnitude and the resonance frequency of each loop, resulting in the findings that the magnitude and the resonance frequency are correlated. This focused current of the specified loop creates a strong magnetic field in front of that loop, resulting in near-field beamforming.

The compressive sensing (CS) theory has been recognized as a promising technique to achieve the target localization in wireless sensor networks. However, most of the existing works require the prior knowledge of transmitting powers of targets, which is not conformed to the case that the information of targets is completely unknown. To address such a problem, in this paper, we propose a novel CS-based approach for multiple target localization and power estimation. It is achieved by formulating the locations and transmitting powers of targets as a sparse vector in the discrete spatial domain and the received signal strengths (RSSs) of targets are taken to recover the sparse vector. The key point of CS-based localization is the sensing matrix, which is constructed by collecting RSSs from RF emitters in our approach, avoiding the disadvantage of using the radio propagation model. Moreover, since the collection of RSSs to construct the sensing matrix is tedious and time-consuming, we propose a CS-based method for reconstructing the sensing matrix from only a small number of RSS measurements. It is achieved by exploiting the CS theory and designing an difference matrix to reveal the sparsity of the sensing matrix. Finally, simulation results demonstrate the effectiveness and robustness of our localization and power estimation approach.

Wireless sensor network (WSN) has attracted many researchers to investigate it in recent years. It can be widely used in the areas of surveillances, health care and agriculture. The location information is very important for WSN applications such as geographic routing, data fusion and tracking. So the localization technology is one of the key technologies for WSN. Since the computational complexity of the traditional source localization is high, the localization method can not be used in the sensor node. In this paper, we firstly introduce the Neyman-Pearson criterion based detection model. This model considers the effect of false alarm and missing alarm rate, so it is more realistic than the binary and probability model. An affinity propagation algorithm based localization method is proposed. Simulation results show that the proposed method provides high localization accuracy.