Partial updating is an effective method for reducing computational complexity in adaptive filter implementations. In this work, a novel random partial update sum-squared auto-correlation minimization (RPUSAM) algorith...
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Partial updating is an effective method for reducing computational complexity in adaptive filter implementations. In this work, a novel random partial update sum-squared auto-correlation minimization (RPUSAM) algorithm is proposed. This algorithm has low computational complexity whilst achieving improved convergence performance, in terms of achievable bit rate, over a partial update sum-squared auto-correlation minimization (PUSAM) algorithm with a deterministic coefficient update strategy. The performance advantage of the RPUSAM algorithm is shown on eight different carrier serving area test loops (CSA) channels and comparisons are made with the original SAM and the PUSAM algorithms.
Recently, a block based adaptive decision feedback equalizer (ADFE) is presented which first uses an iterative scheme to evaluate a block of unknown decisions. FFT based block processing is then used on the received i...
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Recently, a block based adaptive decision feedback equalizer (ADFE) is presented which first uses an iterative scheme to evaluate a block of unknown decisions. FFT based block processing is then used on the received input block and the decision block to carry out the block ADFE operation. A direct floating point (FP) based realization of this scheme, however, pushes up the cost and complexity of processing hugely, as each FP operation involves several additional steps not present in its fixed point (FxP) counterpart. To overcome this problem, a block floating point (BFP) based treatment is presented in this paper for realization of the block ADFE. The proposed scheme, while maintaining FP like high dynamic range, deploys mostly FxP operations and thus reduces the processing cost and complexity substantially.
A novel structure with direct inversion of a multiple input multiple output (MIMO) system is proposed in this paper. Based on this structure, 2 adaptive algorithms, LMS like and Affine Projection algorithm (APA), are ...
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A novel structure with direct inversion of a multiple input multiple output (MIMO) system is proposed in this paper. Based on this structure, 2 adaptive algorithms, LMS like and Affine Projection algorithm (APA), are proposed to directly obtain an accurate estimate of the inverse of the plant system. The proposed algorithms have faster convergence speed than the FxLMS algorithm. Furthermore, this structure does not necessitate any a prior information of plant system and it can trace the fluctuation of the plant. It is shown through simulations that the proposed method overperforms the FxLMS algorithm in convergence speed so it is much applicable to real world environments than the FxLMS algorithm.
A space-time adaptive reduced-rank processor for interference suppression in DS-CDMA systems is proposed based on interpolated FIR filters. The interpolated minimum mean squared error (MMSE) solution is described for ...
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A space-time adaptive reduced-rank processor for interference suppression in DS-CDMA systems is proposed based on interpolated FIR filters. The interpolated minimum mean squared error (MMSE) solution is described for a novel scheme where the interpolator is rendered adaptive and adaptive algorithms are developed for estimating the parameters of both reduced-rank receiver and interpolator. Linear and successive interference cancellation (SIC) space-time receivers with the proposed structure are investigated for mitigating multi-access interference (MAI) and intersymbol interference (ISI) in an uplink scenario. An analysis of the convergence properties of the proposed structure is carried out and simulations for typical scenarios are performed, showing the superiority of the method against previously reported ones.
In this paper, an adaptive window length estimation for channel estimation in direct-sequence (DS) code-division multiple-access (CDMA) receivers is presented. The estimated optimum window length is derived based on a...
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In this paper, an adaptive window length estimation for channel estimation in direct-sequence (DS) code-division multiple-access (CDMA) receivers is presented. The estimated optimum window length is derived based on autocovariance analysis of the estimated channel coefficients. As the propagation channel changes over time, an adaptive algorithm for updating the window length is proposed through Doppler and signal-to-noise ratio (SNR) estimations. The proposed system improves the performance by adaptively selecting and continuously updating the window lengths over a wide-range of velocities (5 to 400 kmph).
In this paper, a FIR based synchronous DS/CDMA receiver is proposed, employing sliding-window LMS algorithm. This receiver has the capacity to suppress the ISI (inter symbol interference) and combat multipath fading e...
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In this paper, a FIR based synchronous DS/CDMA receiver is proposed, employing sliding-window LMS algorithm. This receiver has the capacity to suppress the ISI (inter symbol interference) and combat multipath fading experiencing in both static and dynamic multipath environment. This paper emphasizes the importance of Spread Spectrum technique (CDMA) and the adaptive algorithms and its performance comparisons. The main objective of this paper is to implement, analyze and compare different FIR based adaptive algorithms like NLMS, DRLMS with respect to SWLMS for ISI equalization. The bit-error rate and the output SNR will be considered as the main performance criteria. Attention will be also given to the computational complexity of the implemented algorithms.
This paper proposes a preset adaptive equalizer which effectively equalizes the distortion caused by channel nonlinearities. This equalizer closely approximates an optimal equalizer by using the Gaussian radial basis ...
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