Shannon channel capacity theorem poses highest bit-rate of error free transmission over additive white Gaussian noise channel.In addition,he proved that there exists channel code that can theoretically achieve the cha...Shannon channel capacity theorem poses highest bit-rate of error free transmission over additive white Gaussian noise channel.In addition,he proved that there exists channel code that can theoretically achieve the channel capacity.Indeed fortunately,the latter researchers found some practical channel codes approaching the channel capacity with insignificant losses of spectral efficiency under ignorable bit error rate(BER).The authors note,in general,that bits of the channel codes are not independent of each other in code space.Further,we note that the modulated symbols are not independent among them,as well,in Euclidean Space.By exploiting a usage of the dependencies jointly to signal design,we can transmit two independent signal streams through an additive white Gaussian channel and separate them in Euclidean space at the receiver.The capacity of this approach is found larger than that of Shannon capacity in the same channel assumptions.The numerical results confirm the theoretical procedures.展开更多
In this paper,a new likelihood-based method for classifying phase-amplitude-modulated signals in Additive White Gaussian Noise (AWGN) is proposed.The method introduces a new Markov Chain Monte Carlo (MCMC) algorithm,c...In this paper,a new likelihood-based method for classifying phase-amplitude-modulated signals in Additive White Gaussian Noise (AWGN) is proposed.The method introduces a new Markov Chain Monte Carlo (MCMC) algorithm,called the Adaptive Metropolis (AM) algorithm,to directly generate the samples of the target posterior distribution and implement the multidimensional integrals of likelihood function.Modulation classification is achieved along with joint estimation of unknown parameters by running an ergodic Markov Chain.Simulation results show that the proposed method has the advantages of high accuracy and robustness to phase and frequency offset.展开更多
基金supported by two Programs of National Natural Science Foundation of China(No.61271203 and No.61531004)
文摘Shannon channel capacity theorem poses highest bit-rate of error free transmission over additive white Gaussian noise channel.In addition,he proved that there exists channel code that can theoretically achieve the channel capacity.Indeed fortunately,the latter researchers found some practical channel codes approaching the channel capacity with insignificant losses of spectral efficiency under ignorable bit error rate(BER).The authors note,in general,that bits of the channel codes are not independent of each other in code space.Further,we note that the modulated symbols are not independent among them,as well,in Euclidean Space.By exploiting a usage of the dependencies jointly to signal design,we can transmit two independent signal streams through an additive white Gaussian channel and separate them in Euclidean space at the receiver.The capacity of this approach is found larger than that of Shannon capacity in the same channel assumptions.The numerical results confirm the theoretical procedures.
文摘In this paper,a new likelihood-based method for classifying phase-amplitude-modulated signals in Additive White Gaussian Noise (AWGN) is proposed.The method introduces a new Markov Chain Monte Carlo (MCMC) algorithm,called the Adaptive Metropolis (AM) algorithm,to directly generate the samples of the target posterior distribution and implement the multidimensional integrals of likelihood function.Modulation classification is achieved along with joint estimation of unknown parameters by running an ergodic Markov Chain.Simulation results show that the proposed method has the advantages of high accuracy and robustness to phase and frequency offset.
