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The demand for relay-transmission technologies has recently been increasing. We study relay transmission using multiband to reduce transmission delay and meet the increasing demand. In the relay transmission, the relay node initiates relay transmission while receiving data on another frequency band. However, despite its potential, the difference of data rates between reception and forwarding causes data loss from buffer overflow. To solve this problem, we propose an algorithm that selects appropriate channels, such that the transmission rates become as high as possible without buffer overflow, and evaluate the effectiveness of the proposal.

Recently, WLANs using multiple frequency bands (e.g., 5 GHz, 2.4 GHz, and 920 MHz) have become popular as a means to increase spectral efficiency. However, during multi-hop transmissions in such multi-band WLANs, the relay node experiences a significant increase in delay and loss of data frames. This happens because of the difference of link rates between the receiving and sending sides of the relay node. In order to address this problem, we consider the channel conditions of each band on either side of the relay. Accordingly, the receiving and sending rates at the relay node are measured and calculated, respectively. Based on the measured receiving rate and calculated sending rate, we propose an algorithm for the relay node to determine the optimal coding rate and modulation method so as to dynamically control the best band and channel selection for the sending side. Simulation results demonstrate the effectiveness of our proposed algorithm in terms of improvement of delay and transmission failure probability.

Wireless communications, and in particular wireless local area network (WLAN) technology, has undergone a tremendous evolution in the past decades. After the release of the WLAN standard IEEE 802.11a/b in 1999, Wi-Fi technology soon became pervasive, thanks mainly to its deployment on the unlicensed ISM band. However, high traffic, especially in hotspots and areas with dense deployment of Wi-Fi access points (APs) (e.g., stations, airports, etc.) has caused major issues and a severe degradation of communications quality. The latest WLAN standards (e.g., 802.11ac, 802.11ax) have largely succeeded in improving the link quality and data rate by adopting state-of-the-art PHY layer technologies, e.g., OFDMA, MU-MIMO. However, improvement of the MAC layer in these standards is not noticeable due to restrictions such as hardware limitation and backward compatibility issues for legacy APs. As an effort to improve the MAC layer for the next-generation WLAN standard, in this paper we propose a simple algorithm with low computational complexity for channel selection in Wi-Fi networks. The main idea is to take advantage of the potential of the IEEE 802.11ax MAC to avoid major standard modifications. For this purpose, we employ the channel utilization ratio (CUR), which is measured periodically by each AP based on its channel sensing. Time-averaged CUR values are weighted based on a Gibbs sampling approach and a probability associated to each channel is updated. Finally, a channel is selected based on the aforementioned probabilities in predefined time slots. Simulation results show that the proposed approach can improve the system throughput by up to 5% and transmission delay by up to 20%.

Service robots in a robotic wireless network (RWN) download map information from map servers for safe movement. A RWN needs to support a number of service robots. However, this functionality is constrained by the limited radio resources of a RWN. This paper addresses the issue of improving wireless-resource efficiency for a number of robots to download map information. We propose a data sharing scheme for robots to save consumption of wireless resources in map information acquisition. In the proposed scheme, robots are clustered, and a majority of client robots locally obtain the map information from a few cluster-head robots that acquire the map information directly from the server. To reduce wireless resource consumption, local data sharing among robots employs a lower transmission power than that is used in directly downloading from the server. The proposed scheme carries out efficient cluster formation so as to reduce the number of robots that download the map from the server, and to increase the number of robots that obtain the map information from the local data sharing.

In order to increase area spectral efficiency by exploiting unused spectral resources scattering in multiple frequency bands, we have been studying a wireless LAN (WLAN) system which simultaneously transmits multiple wireless frames over multiple frequency bands such as 2.4 GHz and 5 GHz, and we developed its initial hardware prototype. This paper introduces our developed prototype, and fundamental experiment to validate the effectiveness of our proposed multi-band WLAN. Evaluation results show that simultaneous multi-band transmission technique improves a throughput performance by about 2.5 times compared with conventional single-band transmission under the crowded channel condition.

This paper describes a technique to predict the fading channel of an automated guided vehicle (AGV) that moves along a pre-determined route. A probabilistic neural network (PNN) estimates the most likely signal by performing pattern matching between a stored and current fading signal window. The prediction unit is being developed as part of an anomaly detection unit that together will provide advance information on pending communication outages in a factory communications network. Multiple distributed receivers are employed in order to further improve the accuracy of the prediction. Performance is evaluated using a ray-tracing model of the moving AGV and results show that the mean squared error (MSE) can be reduced four orders of magnitude by employing eight receivers.

This paper will study the busy/idle duration model and its prediction performance of autoregressive (AR) based predictor using the real environment data collected during rush-hour weekday evening at a railway station. The analysis shows that both busy and idle duration distribution largely appear as a generalized Pareto (GP) distribution with a different scale value. In addition, the scale value highly decides the prediction performance of the low-complexity linear AR based predictor. We also propose a new AR based predictor by separating busy/idle duration data into different streams to differentiate the scale value of the streams. The prediction performance of the proposed predictor can be improved for the streams with small scale value.

Communication demand is paramount for disaster-affected people to confirm safety, seek help, and gather evacuation information. However, the communication infrastructure is likely to be crippled due to a natural disaster, which makes disaster response excruciatingly difficult. Although traditional approaches can partially fulfill the most important requirements from the user perspective, including prompt deployment, high capacity, large coverage, useful disaster-time application, and carrier-free usability, a complete solution that provides all those features is still required. Our collaborative research and development group has developed the Movable and Deployable Resource Unit, which is referred to as the MDRU and has been proven to have all those required features. Via extensive field tests using a compact version of an MDRU (i.e., the van-type MDRU), we verify the effectiveness of the MDRU-based disaster recovery network. Moreover, we demonstrate the further improvement of the MDRU’s performance when it is complemented by other technologies such as relay-by-smartphone or satellites.

Introduction: Levodopa (LD) is important in the clinical treatment of Parkinson's disease (PD), and the changes of its pharmacokinetics may affect the clinical outcome. LD is mainly absorbed in the upper intestine; thus, the pharmacokinetics of LD may change after gastrointestinal operation. Here, we present the case of a patient who underwent resection of the intestine and compared his LD pharmacokinetics before and after resection. Case Presentation: A 72-year-old Japanese male PD patient developed jaundice and was diagnosed with cholangiocarcinoma. Pancreaticoduodenectomy was performed and part of the stomach, total duodenum, and part of the jejunum were resected. The patient had been treated with LD, and his pharmacokinetics was checked twice at the age of 68 years. Because LD is absorbed in the duodenum and jejunum, we checked his pharmacokinetics again after the operation. The results before the operation were almost similar; however, in comparison, the area under the curve and peak drug concentration was reduced, and the time-to-peak drug concentration and elimination halftime were elongated after the operation. Conclusion: Physicians must pay attention to the change of LD pharmacokinetics after gastrointestinal operation.