Abstract:In many physical channels where multiuser detection techniques are to be applied, the ambient channel noise is known through experimental measurements to be decidedly non-Gaussian, due largely to impulsive phenomena. This is due to the impulsive nature of man-made electromagnetic interference and a great deal of natural noise. This paper presents a robust multiuser detector for combating multiple access interference and impulsive noise in code division multiple access (CDMA) communication systems. A new M-esti… Show more
“…In this section, the influence functions of M-estimators proposed in the literature [12,14] are listed (see Fig. 1).…”
Section: A Influence Functionsmentioning
confidence: 99%
“…The Huber's M-estimator is determined by the Huber penalty function kν depends on the robustness measures derived from the influence function of [14], where k is a constant. …”
Section: A Influence Functionsmentioning
confidence: 99%
“…By assuming = l l α W , the probability of error, (14), for user #1 can be expressed, using the relation between ( ) ⋅ Q and complementary error function ( ) ⋅ erfc , as [9] 1 1 1 1 1 11 11…”
Section: Asymptotic Performance Of M-decorrelatormentioning
a vempatisr@ieee.org, b pamulavk@ieee.org, e tvakumar2000@yahoo.co.in Keywords: Influence function, maximal ratio combiner, M-estimator, Nakagami-m distribution, probability of error.Abstract. This paper presents the robust multiuser detection in synchronous direct sequence-code division multiple access (DS-CDMA) systems with Maximal Ratio Combiner (MRC) receive diversity over frequency-nonselective, slowly fading Nakagami-m channels in a non-Gaussian environment. Average probability of error is derived for decorrelating detector over single path Nakagami-m fading channel. A new M-estimator proposed to robustify the detector is studied and analyzed. Simulation results show that the new M-estimator outperforms linear decorrelating detector, the Huber, and the Hampel estimator based detectors.
“…In this section, the influence functions of M-estimators proposed in the literature [12,14] are listed (see Fig. 1).…”
Section: A Influence Functionsmentioning
confidence: 99%
“…The Huber's M-estimator is determined by the Huber penalty function kν depends on the robustness measures derived from the influence function of [14], where k is a constant. …”
Section: A Influence Functionsmentioning
confidence: 99%
“…By assuming = l l α W , the probability of error, (14), for user #1 can be expressed, using the relation between ( ) ⋅ Q and complementary error function ( ) ⋅ erfc , as [9] 1 1 1 1 1 11 11…”
Section: Asymptotic Performance Of M-decorrelatormentioning
a vempatisr@ieee.org, b pamulavk@ieee.org, e tvakumar2000@yahoo.co.in Keywords: Influence function, maximal ratio combiner, M-estimator, Nakagami-m distribution, probability of error.Abstract. This paper presents the robust multiuser detection in synchronous direct sequence-code division multiple access (DS-CDMA) systems with Maximal Ratio Combiner (MRC) receive diversity over frequency-nonselective, slowly fading Nakagami-m channels in a non-Gaussian environment. Average probability of error is derived for decorrelating detector over single path Nakagami-m fading channel. A new M-estimator proposed to robustify the detector is studied and analyzed. Simulation results show that the new M-estimator outperforms linear decorrelating detector, the Huber, and the Hampel estimator based detectors.
“…However, the batch algorithm [2] requires singular value decomposition (SVD), which is inconvenient for adaptive implementation. Further, it requires accurate rank estimation of the correlation matrix, which is not easy in an inherently noisy environment [4]- [9].…”
“…Recently, the problem of robust multiuser detection in nonGaussian channels has been addressed in the literature [1] & [2], which were developed based on the Huber and Hampel estimators. The Huber's estimator [3] can limit the effect of gross errors; however, the effect may still have to be large enough to reach an unacceptable level.…”
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