Robust single-user detection is employed in a direct sequence code-division multiple-access (DS-CDMA) system in which the noise process contains impulsive components. The breakdown point is computed for a mixture noise model. The bit error probability expressions are derived under a Gaussian mixture. The performance is also evaluated in the presence of power imbalance and asynchronous reception. Noise, rather than interference, is shown to be the primary obstacle in achieving good performance for certain practical signal power and user load levels. It is concluded that DS-CDMA employing a robust correlator receiver performs better than the conventional matched filter in an impulsive noise environment.

In this paper, a new FIR adaptive filtering algorithm is introduced. This algorithm is based on the Quasi-Newton (QN) optimization algorithm. The approach uses a variable step-size in the coefficient update equation that leads to an improved performance. The simulation results show that the algorithm has very similar performance to the Robust Recursive Least Squares Algorithm (RRLS) while performing better than the Transform Domain LMS with Variable Step-Size (TDVSS) in stationary environments. The algorithm is tested in Additive White Gaussian Noise (AWGN) and Correlated Noise environments.

No abstract

No abstract

The recently proposed Recursive Inverse (RI) algorithm has shown a significant performance improvement compared to that of the Recursive Least Squares (RLS) algorithm, in various noise environments. However, both algorithms fail to converge in certain impulsive noise environments, especially if the Signal-to-Noise Ratio (SNR) is low. In this paper, a Robust RI algorithm is proposed. Analytical results show that robustness against impulsive noise is achieved by choosing the weights on the basis of the L 1 norms of the autocorrelation matrix and the crosscorrelation vector. Simulation results confirm that the proposed algorithm provides an improved performance, with a reduction in computational complexity, compared to those of the RLS and the Robust RLS in white and correlated impulsive noise.

In this letter, a new subspace based estimator that can effectively provide the order and frequencies of multiple sinusoids in noise is proposed. The estimator, referred to as SAS-Est (Subspace Aligning and Separating Estimator), simultaneously seeks to separate the steering vectors from the noise subspace and align them to the signal subspace. The angles between subspaces and the generalized Kullback-Leibler divergence are used in characterizing the alignment and separation. Minimizing the divergence leads to maximal subspace separation and best alignment, thus allowing improved performance. Simulations in additive white Gaussian noise show that the new estimator offers an improvement for both model order and frequency estimation. When compared with other methods, the improvement is more pronounced for high model orders and low signal-to-noise ratio values.

No abstract

The multiuser detection of space coded, Multi Input Multi Output (MIMO), Code Division Multiple Access (CDMA) signals in the downlink direction with channel estimation error is investigated. The main challenge in the system is dealing with the errors in estimating the channel coefficients at the receiving antennas. The performance of the decorrelating detector (DD) under different channel estimation errors, timing errors, and impulsive noise is investigated. A new Robust decorrelating detector (RDD) is proposed which compensates the channel estimation errors by modifying the channel matrix in the system. RDD also deals with the timing errors by the modification of the spreading matrix, and finally, it passes the impulsive components of the additive noise through a robust non-linearity to reduce the impulsive effects. The results show that the performance of the RDD is superior to that of the DD.