This letter discusses the performance of online SNR estimation including fading parameter estimation for parallel combinatorial SS (PC/SS) systems. The PC/SS systems are partial-code-parallel multicode SS systems, which have high-rate data transmission capability. Nakagami-m distribution is assumed as fading channel model to cover a wide range of fading conditions. The SNR and fading parameter estimation considered in this letter is based on only a statistical ratio of correlator outputs at the receiver. Numerical results show that SNR estimation performance with fading parameter estimation is close to the one in the case of perfect fading parameter information, if the number of transmitting PN codes is less than a half of assigned PN codes.

In this paper, an online SNR estimator is proposed for parallel combinatorial SS (PC/SS) systems in Nakagami fading channels. The PC/SS systems are called as partial-code-parallel multicode DS/SS systems, which have the higher-speed data transmission capability comparing with conventional multicode DS/SS systems referred to as all-code-parallel systems. We propose an SNR estimator based on a statistical ratio of correlator outputs at the receiver. The SNR at the correlator output is estimated through a simple polynomial from the statistical ratio. We investigate the SNR estimation accuracy in Nakagami fading channels through computer simulations. In addition, we apply it to the convolutional coded PC/SS systems with iterative demodulation and decoding to evaluate the estimation performance from the viewpoint of error rate. Numerical results show that the PC/SS systems with the proposed SNR estimator have superior estimation performance to conventional DS/SS systems. It is also shown that the bit error rate performance using our SNR estimation method is close to the performance with perfect knowledge of channel state information in Nakagami fading channels and correlated Rayleigh fading channels.