This paper discusses sensor network protocols in terms of the valueput, a metric that considers both the quantity and the freshness of the collected information. Considering a wireless sensor network using acknowledgment feedback, we propose two communication protocols, namely the packet retransmission protocol and the timing shift protocol, and numerically analyze their impact on the valueput. The obtained results show that the packet retransmission protocol effectively improves the throughput but not necessarily the valueput, while the timing shift protocol ensures a performance enhancement of the valueput.
This paper describes the pumping schemes for ultra-wideband (UWB) WDM transmission using only distributed Raman amplification. By using numerical analysis based on the Gaussian noise model, we evaluate the amplification performances for all-Raman UWB-WDM transmission using higher-order pumping and/or forward pumping in addition to conventional 1st-order backward pumping. Moreover, we discuss the effect of forward Raman gain in 1st-order bidirectional pumping configuration, and clarify that the forward Raman gain should be carefully optimized taking account of both noise performance and nonlinear degradation.
In this article, we apply sub-terahertz waves to imaging a target about 1 meter away from the measurement equipment and evaluate image quality for non-destructive inspection. We show the results of imaging a range of items with sub-terahertz waves and confirm that some of them are penetrated.
The use of intelligent reflecting surface (IRS) is being investigated for wireless communication in high frequency bands. By appropriately controlling the reflection coefficient of each IRS element, high quality communication can be achieved even in non-line-of-sight environment. The phase control of the IRS requires the determination of the optimal phase pattern based on the estimated channel, which is then fed back to the IRS through the control channel. To reduce channel estimation overhead, we propose a channel prediction method based on Gaussian process regression. We evaluate the proposed method performance on the points of signal-to-noise ratio (SNR) and confirm that the proposed approach can mitigate SNR degradation caused by terminal movement compared to the system without prediction.
Recently, the cyber-physical-system (CPS) has attracted great interest in the information and communications technology (ICT) research field for the virtual test of wireless communication systems. Since the performance of wireless communication significantly depends on the radio propagation channel characteristics, the development of accurate radio propagation simulation technology becomes essential for the purpose. This paper proposed the scenario-specific radio propagation simulation method from LiDAR point cloud data. By the continuous environment measurement by LiDAR, the positions of dynamic objects like pedestrians are tracked, as well as the site-specific propagation environment characteristics and their influences are taken into the simulation. For performance evaluation, the radio propagation measurement was conducted in the 28GHz band in an indoor office. The result showed a significant improvement in the RMSE of received power prediction. The proposed method will be utilized for the radio channel emulation in the CPS.