Ogawa Masakatsu

Smartphones with Bluetooth low energy (BLE, marketed as Bluetooth Smart) have been widely used. The BLE is a part of Bluetooth 4.0. It utilizes the 2.4 GHz band known as the industrial, scientific, and medical (ISM) band. The IEEE802.11 wireless local area network (WLAN) utilizes the same ISM band as BLE. Therefore, radio-frequency interference may arise with BLE and WLAN coexistence. In this paper, we focus on the interference between the WLAN beacon and the BLE advertising packet. We evaluate the bit error rate (BER) of the WLAN signal on the direct sequence spread spectrum (DSSS) modulation caused by interference with the BLE signal on the Gaussian minimum shift keying (GMSK) modulation by computer simulation. Additionally, we focus on the difference in frequency to investigate the effect of overlapping channels. Furthermore, we examine BER estimation by using the signal-to-interference ratio (SIR) assuming that the BLE signal is modeled as an additive white Gaussian noise (AWGN). Concerning the characteristic of the difference in frequency, we confirm the validity of these simulation results by experimental evaluation in the coexistence of the WLAN beacon and the BLE advertising packet. These results of simulation and experiment have shown that the difference in frequency is correlated with the interference of the BLE signal on the WLAN signal. Moreover, we have verified that the estimation of BER characteristics considering the difference in frequency by using SIR is possible.

In this paper, we propose an immediate cooperative line wait time estimation system using Bluetooth low energy (BLE, marketed as Bluetooth Smart) on a smartphone; this system is a modified version of our previous proposed method. To estimate the wait time, we utilize time stamps of when users approach and move past two preinstalled receivers. Our system comprises three main components: the receivers, a wait time estimator, and a database. The receivers record two types of data: the recorded time and the RSSI values. The wait time estimator uses the wait time estimation algorithm, which includes three main subroutines: the maximum RSSI decision, in-decision, and out-decision on the receivers for each user's smartphone. By calibrating and analyzing the recorded log data, the wait time estimator estimates the estimated wait time. This estimated wait time is stored in the database, then provided through the website to the queueing users. The experimental results showed that the difference between the estimated wait time and the expected wait time was within 10 s for all measurements.

<p>With the diversification of mobile communication systems, we need to calculate the exact bit error rate (BER) under Rician fading for the multi-level modulation methods. The method for calculating the BER under Rician fading by approximating the probability density function (pdf) in the Rician distribution by the Nakagami-m distribution has the problem that their cumulative distribution functions (cdfs) do not match. In this paper, we propose a method for deriving the BER by polynomial expansion of the Rician distribution, then we show the effectiveness of the proposed equation from simulation results.</p>

Recently, services using position information have been increasing. Radio waves and ultrasonic waves are used to acquire position information. Ultrasonic waves can be transmitted and received with existing speakers and popular smartphones. Therefore, there is no need for new devices for position estimation and their convenience is high. However, to the best of our knowledge, a modulation method and a symbol synchronization method for ultrasonic communication that are applicable to existing speakers and smartphones have not been proposed. <br>In this paper, we propose an ultrasonic communication method applicable to existing speakers and smartphones. Moreover, we propose a method of acquiring position information from the signal level of ultrasonic waves at a receiver based on the proposed ultrasonic communication method. Through an experimental evaluation, we confirmed the effectiveness of communications and position estimation.

In this paper, we propose an immediate cooperative line wait time estimation system using Bluetooth low energy (BLE, marketed as Bluetooth Smart) on a smartphone; this system is a modified version of our previous proposed method. To estimate the wait time, we utilize time stamps of when users approach and move past two preinstalled receivers. Our system comprises three main components: the receivers, a wait time estimator, and a database. The receivers record two types of data: the recorded time and the RSSI values. The wait time estimator uses the wait time estimation algorithm, which includes three main subroutines: the maximum RSSI decision, in-decision, and out-decision on the receivers for each user's smartphone. By calibrating and analyzing the recorded log data, the wait time estimator estimates the estimated wait time. This estimated wait time is stored in the database, then provided through the website to the queueing users. The experimental results showed that the difference between the estimated wait time and the expected wait time was within 10 s for all measurements.

Recently, services using position information have been increasing. Radio waves and ultrasonic waves are used to acquire position information. Ultrasonic waves can be transmitted and received with existing speakers and popular smartphones. Therefore, there is no need for new devices for position estimation and their convenience is high. However, to the best of our knowledge, a modulation method and a symbol synchronization method for ultrasonic communication that are applicable to existing speakers and smartphones have not been proposed. <br>In this paper, we propose an ultrasonic communication method applicable to existing speakers and smartphones. Moreover, we propose a method of acquiring position information from the signal level of ultrasonic waves at a receiver based on the proposed ultrasonic communication method. Through an experimental evaluation, we confirmed the effectiveness of communications and position estimation.

Smartphones with Bluetooth low energy (BLE, marketed as Bluetooth Smart) have been widely used. The BLE is a part of Bluetooth 4.0. It utilizes the 2.4 GHz band known as the industrial, scientific, and medical (ISM) band. The IEEE802.11 wireless local area network (WLAN) utilizes the same ISM band as BLE. Therefore, radio-frequency interference may arise with BLE and WLAN coexistence. In this paper, we focus on the interference between the WLAN beacon and the BLE advertising packet. We evaluate the bit error rate (BER) of the WLAN signal on the direct sequence spread spectrum (DSSS) modulation caused by interference with the BLE signal on the Gaussian minimum shift keying (GMSK) modulation by computer simulation. Additionally, we focus on the difference in frequency to investigate the effect of overlapping channels. Furthermore, we examine BER estimation by using the signal-to-interference ratio (SIR) assuming that the BLE signal is modeled as an additive white Gaussian noise (AWGN). Concerning the characteristic of the difference in frequency, we confirm the validity of these simulation results by experimental evaluation in the coexistence of the WLAN beacon and the BLE advertising packet. These results of simulation and experiment have shown that the difference in frequency is correlated with the interference of the BLE signal on the WLAN signal. Moreover, we have verified that the estimation of BER characteristics considering the difference in frequency by using SIR is possible.

<p>With the diversification of mobile communication systems, we need to calculate the exact bit error rate (BER) under Rician fading for the multi-level modulation methods. The method for calculating the BER under Rician fading by approximating the probability density function (pdf) in the Rician distribution by the Nakagami-m distribution has the problem that their cumulative distribution functions (cdfs) do not match. In this paper, we propose a method for deriving the BER by polynomial expansion of the Rician distribution, then we show the effectiveness of the proposed equation from simulation results.</p>

People often have to stand waiting in a queue, which they may find disagreeable. Facilities where people must wait, for example, food courts, banks and amusement parks, need to recognize and provide an estimated wait time to increase customer satisfaction. Hence, there is demand for wait time estimation methods. Also, the requirement for estimation accuracy changes with the length of the queue. In this paper, we propose a cooperative line wait time estimation method using Bluetooth low energy (BLE, marketed as Bluetooth Smart) on a smartphone. To estimate the wait time, we utilize the stay-times of users approaching and moving past two preinstalled receivers. The wait time is estimated by the difference between the two stay-times. Our stay-time estimation includes two methods: a direct-wave blocking method and a stay-time estimation method. We experimentally evaluated with our method in a passageway of our university campus for different values of the range value which is a parameter used in the stay-time estimation. It was found that when the range value was set to 4-8 dB, almost all of the devices estimated the wait time to be within 20 s of from the expected wait time. This result satisfied the requirement of all users according to our questionnaire about discontent with erroneously estimated wait times.

The requirements for wireless sensor networks are low power consumption and long lifetime because sensor nodes are not always supplied by mains electric power. To reduce power consumption, sensor nodes have to reduce the idle listening duration. In this paper, we propose a MAC protocol without using carrier sensing. Packets of all sensor nodes are randomly transmitted within a frame which length is as long as data collecting interval. We perform the theoretical analysis of our protocol and derive the successful transmission rate in case that packets are transmitted in different duration. We simulate our protocol to verify the theoretical analysis.