Study Of Modulation Identification Techinique For Adaptive Coded Modulation

In order to achieve high performance in wireless communication systems, it is necessary to consider a radio transceiver system able to adapt to changes in the environment. This calls for the replacement of the conventional circuit by a programmable digital circuit. This is known as Software Defined Radio (SDR). Decreases decoder and demodulator selection error using a Hidden-Markov Model (HMM) in this paper. In order to estimate the switching patterns of the encoder and modulator, our proposed system selects the maximum likelihood encoder and modulator transition patterns. The selection uses both encoder and modulator transition probability based on the HMM obtained by CSI as well as Decoder and Demodulator Selection Error probabilities .We propose two methods for reducing DSE by increasing the minimum distance between two encoders. One proposes a trellis encoder estimation scheme that compensates for this problem. The other method consists of a blind modulation identification technique for an adaptive coded modulation scheme based on LDPC codes and the Sum-Product decoding algorithm. Attention is paid to the phase error-correcting technique using the decoding result, which is critical for the modulation scheme identification.