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>