Research On Key Techniques Of Media-based Modulation

Recently,media-based modulation(MBM)has been proposed as a new spatial multiplexing technology.The core idea of MBM is embedding information in the variation of end-to-end channel states,which can be realized by changing radio frequency(RF)properties of the propagation environment close to the transmitter with cheap and low power switches.MBM system can be combined with traditional source based modulation(SBM)system,which means that it can transmit both channel state information and RF modulated information.Therefore,MBM is more competitive in spectral efficiency and energy efficiency compared to other multi-antenna technologies.Firstly,the principle of MBM is studied.MBM can transmit either channel state information or both channel state information and RF modulated information.Then the idea of single-input multiple-output MBM(SIMO-MBM)and MIMO-MBM is introduced,and an equivalent system model called generalized MBM is proposed.Based on this system model,the capacities between MBM with different transmission modes and other multi-antenna technologies are compared.Numerical results show that MBM achieves better capacity performance than traditional MIMO systems and is suitable for transmitting higher data rate.Then the detection methods at receiver side are investigated including maximum likelihood(ML)algorithm and sphere decoder(SD)algorithm.Based on traditional SD algorithm,a reduced complexity SD algorithm for MBM system is proposed.Theoretical analysis and simulation results verify that the proposed SD algorithm achieves the same Bit Error Rate(BER)performance as ML algorithm but has much lower complexity than ML and conventional SD algorithms.Secondly,due to the fact that MBM can generate many different channel states,channel state selection,which is similar to traditional antenna selection,algorithms are studied to further improve the BER performance of the system.MBM system can choose an optimal subset of channel states to modulate information and improve MBM's performance and reliability.Then two channel state selection algorithms called CS-MBM and CS-MSBM are proposed.The main ideas of these two algorithms are based on maximizing the minimum Euclidean distance of constellation.Meanwhile,these two algorithms can reduce the complexity of channel state selection process significantly.The simulation results show that these two algorithms perform well.If the constellation size is large,these two algorithms can achieve better BER performance.However,if the constellation size is small,there is a slight loss in BER performance.Finally,since the MBM system employs the channel state to convey modulated information,the availability of accurate channel state information is indispensable at the receiver side for detection.In practice,however,the channel state is usually time-variant due to the mobility on the terminal side,especially for the high-speed railway scenario,which reduces the reliability of requiring the channel state information.Therefore,the BER performance of MBM over time-selective channels due to Doppler shifts is evaluated.Then,in order to improve the performance and reliability of MBM over time-selective channels,two channel tracking algorithms based on least mean square adaptive filter and recursive least squares adaptive filter called LMS-MBM and RLS-MBM are proposed.The complexities of these two algorithms are equal to each other on a macro level,but RLS-MBM is more complicated than LMS-MBM on some details.Numerical simulations verify that although both two channel tracking algorithms improve systems' BER performance significantly,RLS-MBM outperforms the LMS-MBM.Meanwhile,the length of pilots affects the performance of LMS-MBM and RLS-MBM.Longer pilot training length results in a better performance of LMS-MBM and RLS-MBM.