Multi-input multi-output (MIMO) systems where channel state information (CSI) is known at a transmitter can provide a high spectral efficiency. However, time lag between a channel estimation time and an actual transmission time causes performance degradation under time-varying fading conditions. In this paper, we propose direction based transform matrices and a linear prediction method with ray cancelling for a beamspace MIMO channel prediction method. Computer simulation results show that our method can achieve more accurate prediction for a longer time period and therefore better BER performance that is almost the same as when there is no time lag.

In a TDD based AAA/SDMA system, the array weights determined from up-link signals are applied to the downlink transmission because of the channel reciprocity. However, under fast fading conditions, for example due to fast moving MS, the array weights are no longer optimum for the downlink signal transmission and hence the spectral efficiency of the system degrades. In this paper, we present the downlink performance of MS with two antenna elements moving at speeds of ~5, 20 and 40 kmph in the field trial system of i-Burst, which is a wireless broadband system employing AAA and SDMA techniques. The field experiment results show that adaptive antenna processing at MS is effective in improving the mobility performance of TDD-AAA/SDMA system

Space division multiple access (SDMA) technology attained increasing interest due to its ability to increase system capacity, and thereby to improve frequency usage efficiency. Especially in the Time Division Duplex (TDD) system, the SDMA system is simple due to the reciprocity of TDD channel. However in a fast fading environment, performance of the downlink transmission degrades significantly, since the adaptive control can not track fast changing channels due to the time difference between receive and transmit time slot. iBurst is a TDD broad band wireless communication system, which uses SDMA technology with its 12-element antenna array on the base station side to increase frequency usage efficiency. In this paper, a 2- element Adaptive Antenna Array was introduced into an iBurst mobile station and the field experiments were carried out. The field experiment results show that the performance degradation in fast fading channels is recovered and the mobility is enhanced.

A local virtual signal tuned (VST) null-steering adaptive antenna array applied to mobile stations is proposed in this paper. The VST adaptive array detects the spatial signature of the incident signals and generates local uncorrelated virtual signals based on the spatial signature to control the array weights in order to form the required array radiation pattern. The VST array can control its directivity pattern very flexibly and shows good performance for a practical CDMA mobile communication system with a continuous pilot signal. In this paper, the interference suppression performance of the VST array is evaluated for a burst pilot signal mobile communication system. The results show that the VST has better interference suppression performance under severe operation and poor reception conditions compared to an MMSE sense adaptive algorithm.

For 3D reconstruction, polynocular stereo based on multiple image fusion is a promising method. We developed a convolver-based nine-eye stereo machine called SAZAN. It performs real-time acquisition of dense depth map at 20 MDPS (Million Depth-pixels Per Second). The reduction of matching ambiguities, which is the most crucial part in stereo matching, is effectively performed by filtering operations of 2D convolver LSI. Several new ideas and capabilities including a nonlinear data reduction of LoG outputs, an efficient geometric calibration and a subpixel disparity are also implemented in hardware. Considering the hardware size and the various factors that have an influence on the final processing quality, the computational performance is compared with existing stereo systems including the CMU stereo machine.

A video-rate stereo machine has been developed at CMU with the capability of generating a dense range map, aligned with an intensity image, at the video rate. The target performance of the CMU video-rate stereo machine is: 1) multi-image input of 6 cameras; 2) high throughput of 30 million point/spl times/disparity measurement per second; 3) high frame rate of 30 frame/sec; 4) a dense depth map of 256/spl times/240 pixels; 5) disparity search range of up to 60 pixels; 6) high precision of up to 7 bits (with interpolation); and 7) uncertainty estimation available for each pixel.