In order to meet the current transmission and QoS demands of wireless video transmission, the conventional wireless systems are using Multiple Input Multiple Output (MIMO) technology aided with receiver channel state information (CSI) feedback. The CSI is used by the access point to accurately measure the users' channel quality to decide the best transmission and video encoding parameters possible for each user. However, the CSI feedback has some disadvantages such as the delayed reception at the transmitter, the CSI expiry due to the doppler shift, and finally, hardware complexity making it difficult to be implemented in low power and low cost devices. In this paper, we propose the transmission of H.264/SVC video bitstreams through MIMO system by using the received signal strength indicator (RSSI) instead of CSI. To supplement the RSSI, we implement a look-up table based mechanism to predict the video PSNR for any wireless propagation environment. Aside from being widely supported in all wireless devices, the RSSI can be obtained from the clear to send (CTS) packets in without the need of a sounding process. The results show that our proposed method improves the PSNR by more than 16 dB, and has 6 meters more range compared with the conventional method with fixed encoding ratio and packetization.
This paper presents the experimental comparison of vector quantization (VQ) methods for Thai text image. The compared methods include of Linde-Buzo-Gray (LBG), Enhanced LBG (ELBG) and Genetic algorithm (GA). The performance of VQ over gray image is measured with peak signal-to-noise ratio (PSNR) and processing time. The studied parameter are including of codebook number, cluster size, training image type, number of training image and noise. In addition, the results are shown in the verities aspects which are conducted to the appropriate approach in compression of Thai text image.
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