Propagation Characteristics Of Wireless Channel Research Articles

Research on 2.4 GHz Wireless Channel Propagation Characteristics in a Steel Ship Cabin

Wireless sensor network (WSN) has become a popular technology and has a good potential application in naval architecture and marine engineering field. Analysis of transmission ability of wireless signal in steel ship environment is important for network deployment including base station and node installation, which would directly impact network performance and has become a hot research field. This paper investigates 2.4 GHz frequency wireless signal propagation characteristics in the steel ship cabin. A 3D ray-tracing model of 2.4 GHz wave propagation in the ship cabin is established, a multipath propagation prediction is carried on, and receiving power is calculated. Besides, the experimental test is performed in the real ship. The simulated and experimental results are processed and compared; the influence law of large obstacles on the signal is discussed, and the guidance scheme for node and base station deployment of the wireless sensor network is proposed. The results show that this analysis could provide valid interpretation of wireless channel propagation characteristics in steel ships.

Wireless Channel Propagation Characteristics and Modeling Research in Rice Field Sensor Networks.

Wireless channel propagation characteristics and models are important to ensure the communication quality of wireless sensor networks in agriculture. Wireless channel attenuation experiments were carried out at different node antenna heights (0.8 m, 1.2 m, 1.6 m, and 2.0 m) in the tillering, jointing, and grain filling stages of rice fields. We studied the path loss variation trends at different transmission distances and analyzed the differences between estimated values and measured values of path loss in a free space model and a two-ray model. Regression analysis of measured path loss values was used to establish a one-slope log-distance model and propose a modified two-slope log-distance model. The attenuation speed in wireless channel propagation in rice fields intensified with rice developmental stage and the transmission range had monotone increases with changes in antenna height. The relative error (RE) of estimation in the free space model and the two-ray model under four heights ranged from 6.48–15.49% and 2.09–13.51%, respectively, and these two models were inadequate for estimating wireless channel path loss in rice fields. The ranges of estimated RE for the one-slope and modified two-slope log-distance models during the three rice developmental stages were 2.40–2.25% and 1.89–1.31%, respectively. The one-slope and modified two-slope log-distance model had better applicability for modeling of wireless channels in rice fields. The estimated RE values for the modified two-slope log-distance model were all less than 2%, which improved the performance of the one-slope log-distance model. This validates that the modified two-slope log-distance model had better applicability in a rice field environment than the other models. These data provide a basis for modeling of sensor network channels and construction of wireless sensor networks in rice fields. Our results will aid in the design of effective rice field WSNs and increase the transmission quality in rice field sensor networks.

The Propagation Characteristics of Radio Frequency Signals for Wireless Sensor Networks in Large-Scale Farmland

For configuring wireless sensor network and deploying nodes, the propagation characteristics of wireless channel at frequency of 433 MHz and 2.4 GHz are investigated. Through the analysis of the received signal strength indicator (RSSI) and packet loss rate (PLR), we find that the RSSI (PLR) decreases (increases) as the transceiver nodes distance increases. It is also found that the path loss decreases with the antenna height increasing, and the path loss at 2.4 GHz is more serious than that at 433 MHz. Through the regression analysis in Matlab, we find that the optimal fitting model is the parametric exponential decay (OFPED) model, and the second-best is the linear logarithmic model. For OFPED model, the values of R2 vary from 0.9347 to 0.9893, and the values of root mean square error (RMSE) range from 0.7469 to 2.243 at frequency of 433 MHz; while at frequency of 2.4 GHz, the values of R2 change from 0.9612 to 0.9857, and the values of RMSE range from 1.375 to 3.181. Moreover, we make a comparison analysis with several modified exponential decay (MED) models, and the validation results show that the MED models can be used as conservative upper and lower bounds of path loss, at least for wheat field.

Indoor position tracking using received signal strength‐based fingerprint context aware partitioning

Mobile indoor localisation has numerous uses for logistics and health applications. Current wireless localisation systems experience reliability difficulties in indoor environments due to interference and also require a large number of wireless access points to ensure position accuracy and resolution. Localisation using wireless channel propagation characteristics, such as radio-frequency (RF) receives signal strength are subject to wireless interference. The Fingerprint Context Aware Partitioning (FCAP) tracking model used received RF signal strength fingerprinting, combined with context aware information about the user's indoor environment. The authors show the use of context aware information in the FCAP model, reduces the effect of wireless interference and lowers the spatial density of access points required. The wireless localisation network consisted of reference nodes placed at locations in a building. Reference nodes are used by mobile nodes, to localise a user's position. The authors tested the FCAP model in a typical indoor environment and compared the performance and accuracy to other received signal strength indicator fingerprint localisation methods. They found the FCAP model had improved performance and was able to achieve a similar accuracy to other protocols, with fewer reference nodes.

Biometric Behavior Authentication Exploiting Propagation Characteristics of Wireless Channel

Massive expansion of wireless body area networks (WBANs) in the field of health monitoring applications has given rise to the generation of huge amount of biomedical data. Ensuring privacy and security of this very personal data serves as a major hurdle in the development of these systems. An effective and energy friendly authentication algorithm is, therefore, a necessary requirement for current WBANs. Conventional authentication algorithms are often implemented on higher levels of the Open System Interconnection model and require advanced software or major hardware upgradation. This paper investigates the implementation of a physical layer security algorithm as an alternative. The algorithm is based on the behavior fingerprint developed using the wireless channel characteristics. The usability of the algorithm is established through experimental results, which show that this authentication method is not only effective, but also very suitable for the energy-, resource-, and interface-limited WBAN medical applications.

Optimal nonuniform deployment of sensors for distributed detection in wireless sensor networks

We determine the optimal nonuniform spatial density of nodes in a single-hop Wireless Sensor Network (WSN) whose task is the distributed detection of a target within its sensing field. The optimization approach accounts for such factors as the Medium Access Control (MAC) protocol being used, the wireless channel's propagation characteristics, a randomized sleep/wake-up scheduling protocol, network coverage constraints, the energy consumed, the time to reach a decision, and the number of nodes in the network. The node density that minimizes the average Decision Error Probability (DEP) when a node at the center of the network serves as the Cluster Head (CH) is shown to be a function of the distance from this CH. The solution of this optimization problem and simulations demonstrate both the significant performance improvement provided by nonuniform spatial densities and the trade-offs that are possible amongst energy, network lifetime, detection performance, and time to reach a decision.

Propagation Characteristics of 2.4 GHz Wireless Channel at Different Directions and Heights in Tea Plantation

For configuring wireless sensor networks system and node deployment in tea plantation, this paper researched propagation characteristics of 2.4 GHz wireless channel at different directions and heights in perennial tea plants. Received signal strength and packet loss numbers were obtained by field testing measurements at three directions and two heights. The results showed that different heights of sensor nodes in the tea plants determine the wireless channel propagation characteristics. But the impact of propagation directions on wireless signal is weaker. Besides, validation results show that it s best to deploy the sensor nodes antennas on the top of the tea canopy or above of it in the tea plantation. This research can provide technical support for WSN application in tea plantation.

Mobility-dependent small-scale propagation model for applied simulation studies

We propose an extension to existing wireless channel modeling techniques introducing a notion of mobility behavior of the user. We represent large-scale propagation characteristics of wireless channels as a mobility-dependent stochastic process that explicitly tracks the movement of the user between areas with different received local average signal strength (RLASS). Our model consists of two different parts: mobility model and propagation model. Mobility of the user is modeled by a Markov chain with finite state space. Large-scale propagation characteristics of wireless channel are represented as a function of mobility model. Small-scale propagation characteristics are then obtained taking into account shadowing of the line-of-sight propagation path. Based on the amount of available information regarding a given landscape environment we develop two different parametrization methods (i) RLASS values are available for limited number of points in a given landscape and (ii) RLASS information is not available. The model is suitable for simulation studies of applications' performance in presence of RLASS changes caused by movement of the user.

Statistical wireless channel propagation characteristics in underground mines at 900 MHz: A comparative analysis with indoor channels

This work investigates the wideband characterization of radio propagation channel for an active, real underground mine environment. Important statistical parameters related to path loss, delay, and amplitude characteristics are extracted. Impact of different antenna heights on path loss exponent is investigated. The same measurement procedure is performed to extract the statistical characteristics of a university building due to the structural similarities between the two environments since both include long hallways, crosscuts, and turns. Based on the results, a comparative analysis is presented along with concluding remarks and future directions.

Distributed time-optimal scheduling for convergecast in wireless sensor networks

We consider applications of sensor networks wherein data packets generated by every node have to reach the base station. This results in a many-to-one communication paradigm referred to as convergecast. We are interested in determining a TDMA schedule that minimizes the total time required to complete the convergecast. Initially, we consider a simple version of the problem wherein every node generates exactly one packet. We provide a distributed scheduling algorithm for tree networks that requires at most max(3nk-1,N) timeslots for convergecast, where nk represents the maximum number of nodes in any subtree and N represents the number of nodes in the network. We propose a distributed convergecast scheduling algorithm for general networks that requires at most 3N timeslots. Through extensive simulations, we demonstrate that actual number of timeslots needed is around 1.5N. In addition to time efficiency, we prove that our convergecast scheduling algorithm requires the nodes to buffer no more than two packets at any instance. We propose a sleep schedule that conserves more than 50% of the energy. We propose simple modifications to apply our algorithm when (i) the convergecast is initiated by the base station, (ii) nodes generate multiple packets and (iii) the wireless channel propagation characteristics are not ideal. Simulation results for a real application scenario show that our convergecast scheduling algorithm performs significantly better than existing convergecast algorithms.