Performance Comparison between MAI and Noise Constrained LMS Algorithm for MIMO CDMA DFE and Linear Equalizers
نویسنده
چکیده
This paper presents a performance comparison between a constrained least mean squared algorithm for MIMO CDMA decision feedback equalizer and linear equalizer. Both algorithms are constrained on the length of spreading sequence, number of users, variance of multiple access interference as well as additive white Gaussian noise (new constraint). An important feature of both algorithms is that multiple access interference together with noise variance is used as a constraint in MIMO CDMA linear and decision feedback equalization systems. Convergence analysis is performed for algorithm in both cases. From the simulation results shown at the end show that algorithm developed for decision feedback equalizer has outperformed the algorithm developed for linear equalizer in MIMO CDMA case Keywords—Least mean squared algorithm (LMS); linear equalizer (LE); multiple input; multiple output (MIMO); decision feedback equalizer (DFE); multiple access interference (MAI); Variance; adaptive algorithm
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