We have previously proposed a human target localization method using an ultra-wideband sensor with multistatic placed antennas and investigated its fundamental localization performance by computer simulation using simple indoor and human body models. In actual uses for the sensor, there are many reflectors such as desks and chairs other than walls in the room. Also, the intensity of the reflected wave from an actual human body changes complicatedly because the radar cross section varies greatly depending on the incident angle of radio waves. Therefore, in order to investigate the effectiveness of the proposed method, it is important to conduct experiments in actual radio propagation environment. In this research, we construct an experimental system that implements the proposed method and experimentally investigate the effectiveness of our proposal by changing the sensor parameters. The experimental results have confirmed that, for example, when the bandwidth is 3 GHz, the localization error was within 0.25 m with a probability of 80% or more, and the locations of a human target can be estimated with high accuracy.

Antenna diversity is a powerful means to improve the bit error rate (BER) performance in wireless communication systems. In this paper, we propose selective multi-input multi-output (MIMO) diversity with subcarrier-wise user equipment (UE) antenna identification/selection in a doubly-selective fading channel. Pilot-aided channel estimation (PACE) is used for identifying/selecting the best UE antenna prior to data transmission and decision-feedback channel estimation (DFCE) is used to update the channel state information (CSI). It is confirmed by computer simulation that the proposed selective MIMO diversity provides the improved BER performance compared to MISO/SIMO diversity in low and high mobility environments.

In order to realize high resolution location estimation by using array radar, it is necessary to increase the number of elements. However, it is often difficult because of the cost. We have shown that the number of virtual array elements can be effectively increased by using the MIMO radar with Minimum Redundancy Array (MRA) by the Khatri-Rao (KR) product virtual array processing. However, the optimum arrangements to realize a largest virtual Uniform Linear Array (ULA) is still unclear. In this paper, we have shown the optimum element arrangements that make a virtual ULA when we apply the KR product virtual array processing to MIMO radar.

A spectrum sensing technique based on the detection of the audio FM and wireless microphone signals in the TV band is proposed. Our method autocorrelates the signal that enables a formulation of the new decision making index in terms of a ratio A_r. Thereby an algorithmic interpretation with A_r as an index, one identifies the white space. This method reduces the probability of false alarm and mitigates the disadvantages of other spectrum sensing techniques.

To evaluate the electromagnetic interference (EMI) in a wireless medical telemetry system (WMTS) caused by LED lamp emission, the statistical characteristics of noise and its impact on the receiver sensitivity of the WMTS were investigated. Noise from LED lamp is generally wideband owing to high-speed switching, but the WMTS employs narrow-band reception of 8.5 kHz. The amplitude probability distribution of band-limited noise from LED lamp agrees well with that of Gaussian noise with average power equal to that of band-limited LED noise. The increase in the required signal power of the WMTS for critical reception, caused by LED noise, was almost the same as that in the case of purely Gaussian noise with equal power. The above results indicate that LED noise interfering with a WMTS channel can be well modeled by Gaussian noise, and that the interference effect can be simply represented by the reduction in the receiving carrier-to-noise ratio (CNR), enabling easier evaluation of the impact of interference in the WMTS by using the CNR.

Blau and Michaeli recently introduced a novel concept for inverse problems of signal processing, that is, the perception-distortion tradeoff. We introduce their tradeoff into the rate distortion theory of lossy source coding in information theory, and clarify the tradeoff among information rate, distortion and perception for general information sources.