In this paper, two efficient VLSI architectures for biorthogonal wavelet transform are proposed. One is constructed by the filter bank implementation and another is constructed by the lifting scheme. In the filter bank implementation, due to the symmetric property of biorthogonal wavelet transform, the proposed architecture uses fewer multipliers than the orthogonal wavelet transform. Besides, the polyphase decomposition is adopted to speed up the processing by a factor of 2. In the lifting scheme implementation, the pipeline-scheduling technique is employed to optimize the architecture. Both two architectures are with advantages of lower implementation complexity and higher throughput rate. Moreover, they can also be applied to realize the inverse DWT efficiently. Based on the above properties, the two architectures can be applied to time-critical image compressions, such as JPEG2000. Finally, the architecture constructed by the lifting scheme is implemented into a single chip on 0.35 µm 1P4M CMOS technology, and its area and working performance are 5.005 5.005 mm2 and 50 MHz, respectively.

A powerful HARQ-based linear precoding scheme is proposed to utilize the flexibility of post-combining HARQ strategy in MIMO communications systems. The scheme selects the appropriate symbols and transmit powers for each eigen-mode to acquire more performance gains. Simulation results show that the proposed scheme achieves about 5.5 dB signal-to-noise ratio gains over original spatial multiplexing scheme at an average bit error rate of 10-4. Furthermore, the gap between the two schemes increases with the number of transmissions.