Power Allocation of Superimposed Training
隐含训练序列信道估计中的功率分配

Compared with the conventional Time-Division Multiplexed (TDM) channel estimation scheme based on training sequences, the use of implicit training saves valuable bandwidth, where the training sequences are added to information sequences before antenna transmission. However, for a fixed total transmission power, the information power decrease with the increase of the training sequence power, which causes decrease in the Signal to Noise Ratio (SNR) at channel equalizer. In this paper, the relationship between the SNR of the channel equalizer and the training sequences power is analyzed for MIMO system. The optimal power allocation of the training sequence is derived based on the criterion of maximizing SNR of the equalizer. Analysis and simulation results show that the SNR of the channel equalizer is maximized at the optimal training sequence power, and the optimal power of the training sequences is increased with increase of the signal to noise ratio at the received antennas.