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Averaged stochastic gradient algorithms for adaptive blind multiuser detection in DS/CDMA systems

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1 Author(s)
Krishnamurthy, V. ; Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia

In this paper, we present a blind adaptive gradient (BAG) algorithm for code-aided suppression of multiple-access interference (MAI) and narrow-band interference (NBI) in direct-sequence/code-division multiple-access (DS/CDMA) systems. This BAG algorithm is based on the concept of accelerating the convergence of a stochastic gradient algorithm by averaging. This ingenious concept of averaging was invented by Polyak and Juditsky (1992)-this paper examines its application to blind multiuser detection and NBI suppression in DS/CDMA systems. We prove that BAG has identical convergence and tracking properties to recursive least squares (LMS) but has a computational cost similar to the least mean squares (LMS) algorithm-i.e., an order of magnitude lower computational cost than RLS. Simulations are used to compare our averaged gradient algorithm with the blind LMS and LMS schemes

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Communications, IEEE Transactions on  (Volume:48 ,  Issue: 1 )