This paper proposes weight updating techniques for spectrum sensing based on a cyclic autocorrelation function (CAF) shared diversity combining. We had reported that CAF shared diversity combining can improve the performance by the weight calculated from the time-averaged CAF value. However, the performance is degraded when the weight includes CAFs calculated from purely additive white Gaussian noise. To avoid this, this paper proposes the weight updating technique in which only the CAFs are employed to obtain the time-averaged CAF when it is judged that a primary user is present. This paper provides theoretical analysis results of the proposed technique. The proposed results show that the performance of signal detection can be improved as compared to the conventional technique.

In this paper, we propose a traffic feature-based botnet detection scheme emphasizing the importance of long patterns. Since the communication sequences of bots are not easily changed, the long communication patterns of botnets are useful for detection. The proposed scheme emphasizes the long pattern’s importance by improving the feature extraction algorithms and giving weights to the long patterns with large occurrences. By the computer simulation with real dataset, we show the effectiveness of our scheme.

In order to achieve high-speed and large-capacity communication, efficient use of frequency resources even over different wireless communication systems is an important issue. We previously proposed the spectrum superposing scheme using subcarrier transmission power assignment (STPA) and blind adaptive array (BAA). Even when multiple systems use the same frequency band, the secondary system enables the both receivers to mitigate inter-system interference by STPA-BAA. However, STPA-BAA has a problem that the operational region of the secondary system is limited due to low-level subcarriers. This paper attempts to resolve this issue by introducing subcarrier modulation adaptation. It can effectively expand the operational region of our proposed approach even in the low signal-to-noise-power-ratio (SNR) situation.

This letter presents a screening technique for elderly adults with mild cognitive impairment towards the early detection of dementia based on daily gait measurement using a Doppler radar. The gait parameters corresponding to walking speed, gait cycle, and leg velocities were remotely extracted using a simple Doppler radar system for elderly participants aged 65 years and above. The screening capabilities of the participants with mild cognitive impairment were investigated by using the extracted gait parameters. The results verified that our Doppler radar technique achieved mild cognitive impairment screening with approximately 94% sensitivity and 69% specificity.