The need for high-speed data transfer on the one hand and the limited resources available, especially the lack of frequency spectrum on the other hand, are the most important challenges facing G4-standard telecommunications networks, such as WiMAX, LTE and TD-SCDMA. Methods have been devised to improve spectral efficiency (SE). One of these methods is adaptive modulation and coding (AMC) in which the sender selects its modulation and coding scheme (MCS) based on channel conditions and with respect to the error probability limit of a certain set. In this paper, the performance of two AMC methods with the same modulation and coding design, one with the Moore state machine method and the other with the first-order finite state Markov chain method, is simulated and the optimal state is extracted. In each of these two methods, each state is represented by a pair of regular modulation and coding rates. The designs are QPSK, 16QAM and 64QAM modulations and block codes with rates of 1.2, 2.3 and 3.4. In Moore -adaptive method, the modulation and coding scheme is adapted based on the average attenuation coefficient of the channel, and in Markov-adaptive method, it is done based on the signal-to-noise ratio (SNR) of the average channel. The simulation results show that the spectral efficiency of the Moore method is better in the signal-to-noise ratio from 9 to 13.35 dB to 31.6% and in the signal-to-noise ratio of 13.35 to 18.6 dB is 7.9% better than the spectral efficiency of the Markov-adaptive method. Also, the spectral efficiency of Markov method in signal-to-noise ratio from 18.6 to 22 decibels is 52.1% better than the spectral efficiency of Moore-adaptive method.
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