Automated classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. We have investigated this possibility experimentally and numerically using a diffraction imaging approach. A fast image analysis software based on the gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images. The results of GLCM analysis and subsequent classification demonstrate the potential for rapid classification among six types of cultured cells. Combined with numerical results we show that the method of diffraction imaging flow cytometry has the capacity as a platform for high-throughput and label-free classification of biological cells.
In this reported work, the blockage probability for the 60GHz radio links is analysed in typical indoor environments with random human activities. With up to Q random distributed human bodies, the average blockage possibility is calculated in the sense of statistics for the radio links between the user devices and the ceiling-mounted access point (AP) in a typical wireless LAN architecture. Also, the blockage impact to the effective channel capacity is quantified as a reduction related to the blockage probability. Numerical simulations show that the blockage probability increases almost linearly as the user devices are moving towards the edge of the service area, and the increasing rate is largely affected by the height of the AP and the human density.Introduction: Recently, high-speed communication in indoor environments using the 60GHz millimetre-wave band has attracted much attention from both industry and academic societies owing to attractive features such as ultra-high transmission rate, high-level security and unlicensed operation [1]. However, the radio transmission essentially relies on the line of sight (LOS) path between the transceivers, which is very sensitive to blockage impact by human activity. Since the human body shadowing effect is almost inevitable in indoor applications, such as 60GHz wireless LAN (WLAN), extensive research efforts have been made to characterise the shadowing impacts via simulation and measurement campaigns. Collonge et al.[2] presented several propagation measurements in a realistic indoor environment with natural human activity for a 60GHz channel, and identified the unavailability rate (UR) of the channel as the portion of time when the LOS path is blocked. In a typical office environment, the authors in [3] revealed that the loss of propagation-path visibility of the 60GHz radio links is affected by the human density and service area. Also, Wang et al. in [4] characterised the human body shadowing attenuation by excluding the blocked signal power at the receiver, and quantified the link stability by the distribution of the duration when the attenuation level exceeds a certain threshold. However, in a dynamic obstruction environment, it is seldom mentioned to analytically evaluate the probability that a 60GHz radio link might be blocked in a statistical way, which largely affects the performance of the emerging applications in 60GHz band, e.g. the wireless streaming of uncompressed high-definition (HD) TV.In this Letter, an analysis framework of the blockage probability is proposed for 60GHz radio links in a typical indoor environment with random human activity. Different from [2] and [3], a wireless LAN with a star topology is considered in a general indoor scenario. The access point (AP) is ceiling-mounted at the centre of a service area, in which the user devices (DEVs) are randomly distributed and communicate with the AP via LOS paths. From the probabilistic distribution of the human bodies and the incurred shadow area, the possibility of a singlehop radio link being ...
We consider a large-scale MIMO system operating in the 60 GHz band employing beamforming for high-speed data transmission. We assume that the number of RF chains is smaller than the number of antennas, which motivates the use of antenna selection to exploit the beamforming gain afforded by the large-scale antenna array. However, the system constraint that at the receiver, only a linear combination of the receive antenna outputs is available, which together with the large dimension of the MIMO system makes it challenging to devise an efficient antenna selection algorithm. By exploiting the strong line-of-sight property of the 60 GHz channels, we propose an iterative antenna selection algorithm based on discrete stochastic approximation that can quickly lock onto a nearoptimal antenna subset. Moreover, given a selected antenna subset, we propose an adaptive transmit and receive beamforming algorithm based on the stochastic gradient method that makes use of a low-rate feedback channel to inform the transmitter about the selected beams. Simulation results show that both the proposed antenna selection and the adaptive beamforming techniques exhibit fast convergence and near-optimal performance.
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