In this paper, the performance of multi-stage parallel interference cancellation receiver using forward-backward filtering channel estimation is evaluated for the W-CDMA uplink. The channel estimation employs a non-causal forward-backward-multiplication-method filter, which was originally proposed for the reception of W-CDMA random access. Results of link level simulations for data and voice traffic scenarios over Pedestrian A and Vehicular A channels are discussed in comparison with the conventional channel estimation methods of 1-slot pilot averaging, 1-slot averaging, and weighted multiple slot averaging. It is shown that the forward-backward filtering channel estimation improves performances of the interference cancellation receiver as well as that of the ordinary Rake receiver in both Pedestrian A and Vehicular A channels. With its features of short processing delay and low complexity, the forward-backward filtering channel estimation is suitable for practical implementations of multi-stage interference cancellation receivers.

Personal Handy Phone (PHP), the Japanese digital cordless telephone system is being developed. The 32kbits/s ADPCM (Adaptive Differential Pulse Code Modulation) codec has been standardized for PHP. This paper describes firstly, the advanced algorithms of a Voice Activity Detection (VAD) function that reduces power dissipation of a digital cordless telephone terminal, secondly, a comfort noise generator operates in conjunction with the VAD and finally, a transmission error control based on the use of the prediction coefficients generated in the ADPCM codec. These proposed algorithms function in the low signal-to-noise ratio (SNR) environment of personal radio communications. The quality of the reconstructed speech after the process is influenced by the VAD decision errors (false detection when no voice is present, or no detection when voice is present) , the similarity of the generated comfort noise to the actual background noise, and the transmission quality. The simulation results of the performance achieved by these algorithms are shown and required loading of the computation are also given.