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Two variants of systematic resampling(S-RS)are proposed to increase the diversity of particles and thereby improve the performance of particle filtering when it is utilized for detection in Bell Laboratories Layered Space-Time(BLAST)systems.In the first variant,Markov chain Monte Carlo transition is integrated in the S-RS procedure to increase the diversity of particles with large importance weights.In the second one,all particles are first partitioned into two sets according to their importance weights,and then a double S-RS is introduced to increase the diversity of particles with small importance weights.Simulation results show that both variants can improve the bit error performance efficiently compared with the standard S-RS with little increased complexity.
Two variants of systematic resampling (S-RS) are proposed to increase the diversity of particles and thereby improve the performance of particle filtering when it is utilized for detection in Bell Laboratories Layered Space-Time (BLAST) systems. The first variant, Markov chain Monte Carlo transition is integrated in the S-RS procedure to increase the diversity of particles with large importance weights. In the second one, all particles are first partitioned into two sets according to their importance weights, and then a double S-RS is introduced to increase the diversity of particles with small importance weights. Simulation results show that both variants can improve the bit error performance compared with the standard S-RS with little increased complexity.