SMI Based Beamforming Algorithms for TDMA Signals
This paper considers the problem of co-channel interference suppression in a TDMA communication system. To improve the reception of the signal of interest (SOI) and null interfering signals, the Sample Matrix Inversion (SMI) algorithm uses a known training sequence in each TDMA burst to tune the weights of an antenna array. However, when the interfering burst overlaps the SOI data but not the SOI training sequence, SMI performance is degraded. To overcome this problem, the Constant Modulus Algorithm (CMA), updated over the entire SOI burst, is used to enhance the SMI array weights. Simulations of a co-channel interference scenario demonstrate that SMI-CMA achieves higher output SINR than the SMI-Zero Forcing and SMI-Adjacent Burst algorithms for a large range of burst overlap cases.
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