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Online ISSN 1751-9683 Print ISSN 1751-9675

IET Signal Processing

Volume 3, Issue 2, March 2009

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Volume 3, Issue 2

March 2009

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    • Identification of nonlinear systems by the genetic programming-based Volterra filter
      • Author(s): L. Yao  and  C.-C. Lin
      • Source: IET Signal Processing, Volume 3, Issue 2, p. 93 –105
      • DOI:  10.1049/iet-spr:20070203
      • Type: Article
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      • p. 93 –105 (13)
        The genetic programming (GP) algorithm is utilised to search for the optimal Volterra filter structure. A Volterra filter with high order and large memories contains a large number of cross-product terms. Instead of applying the GP algorithm to search for all cross-products of input signals, it is utilised to search for a smaller set of primary signals that evolve into the whole set of cross-products. With GP's optimisation, the important primary signals and the associated cross-products of input signals contributing most to the outputs are chosen whereas the primary signals and the associated cross-products of input signals that are trivial to the outputs are excluded from the possible candidate primary signals. To improve GP's learning capability, an effective directed initialisation scheme, a tree pruning and reorganisation approach, and a new operator called tree extinction and regeneration are proposed. Several experiments are made to justify the effectiveness and efficiency of the proposed modified by the GP algorithm.
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      TOA-based distributed localisation with unknown internal delays and clock frequency offsets in wireless sensor networks
      • Author(s): K. Yu ; Y.J. Guo ; M. Hedley
      • Source: IET Signal Processing, Volume 3, Issue 2, p. 106 –118
      • DOI:  10.1049/iet-spr:20080029
      • Type: Article
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      • p. 106 –118 (13)
        Locating sensor nodes in an ad hoc wireless sensor network (WSN) is a challenging task. In general, the network nodes are not synchronised and the internal delays within the nodes are unknown. Here, time-of-arrival (TOA)-based localisation is investigated when practical parameters such as clock time offset, clock frequency offset and system internal delay are all involved. The TOA measurements are made between each pair of nodes that are within radio range. First, an efficient frequency offset (FO) estimation algorithm is derived. Then, a two-stage localisation scheme is proposed. In the first stage, localisation starts from the nodes with the largest numbers of neighbouring anchors and priority is always given to nodes with more neighbouring anchors and/or localised nodes. In the second stage, the locations of all neighbouring nodes are exploited to improve location accuracy. Two iterative algorithms are developed: the Taylor series-based least squares (TS-LS) method and the sequential quadratic programming (SQP) optimisation method. During the localisation process, a number of measures are taken to ensure the reliability of each location estimate to avoid abnormal errors and reduce error propagation. The Cramer–Rao lower bound is also derived to benchmark the location accuracy.
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      Application of Jacobi algorithm for ISI channels
      • Author(s): P. Xiao  and  M. Sellathurai
      • Source: IET Signal Processing, Volume 3, Issue 2, p. 119 –132
      • DOI:  10.1049/iet-spr:20080062
      • Type: Article
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      • p. 119 –132 (14)
        Here, the Jacobi iterative algorithm is applied to combat intersymbol interference (ISI) caused by frequency-selective channels. The performance bound of the equaliser is analysed in order to gain an insight into its asymptotic behaviour. Because of the error propagation problem, the potential of this algorithm is not reached in an uncoded system. However, its extension to a coded system with the application of the turbo-processing principle results in a new turbo equalisation algorithm, which demonstrates comparable performance with reduced complexity compared with some existing filter-based turbo equalisation schemes; and superior performance compared with some frequency domain solutions, such as orthogonal frequency division multiplexing and single-carrier frequency domain equalisation.
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      Computationally efficient PCRLB for tracking in cluttered environments: measurement existence conditioning approach
      • Author(s): H. Meng ; M.L. Hernandez ; Y. Liu ; X. Wang
      • Source: IET Signal Processing, Volume 3, Issue 2, p. 133 –149
      • DOI:  10.1049/iet-spr:20080040
      • Type: Article
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      • p. 133 –149 (17)
        In this paper, we consider the problem of calculating the posterior Cramér–Rao lower bound (PCRLB) for tracking in cluttered domains in which there can be both missed detections and false alarms. We introduce a novel approach, whereby we condition on the ‘existence sequence’, which is a sequence of zeros and ones depending on whether at least one measurement exists at each sampling time. An existing Riccati-like recursion then provides a PCRLB conditional on each existence sequence, and an unconditional PCRLB is calculated as a weighted average of these conditional bounds. This new approach is referred to as ‘measurement existence sequence conditioning’ (MESC). The MESC approach is compared with both the information reduction factor (IRF) approach and measurement sequence conditioning (MSC) approach. It is proved that the MESC approach provides a less optimistic bound than the IRF approach. This is a desirable property, as it shows that the MESC bound is more realistic than the IRF bound. It is also shown that the MESC bound provides a more optimistic bound than the MSC approach. Although this is undesirable, in the simulations differences between the MESC and MSC bounds are very small (typically less than 5%). This suggests that the key reason for the over-optimism of the IRF bound is the fact that it does not take into account the effect of missed detections. Although the MESC approach treats cases with one or more detection differently to the MSC approach, the similarity between these two bounds suggests that discriminating between such cases is of less importance. However, the greatest value of the new MESC approach is that the bound can be enumerated precisely, without the need for inefficient and computationally expensive sampling. In case studies, we show that the MESC bound can be calculated 10–100 times more quickly than the MSC bound. It is concluded that the novel MESC formulation introduced herein represents an exciting development in the determination of the PCRLB in cluttered environments.
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      Adaptive space-time reduced-rank estimation based on diversity-combined decimation and interpolation applied to interference suppression in CDMA systems
      • Author(s): R.C. de Lamare  and  R. Sampaio-Neto
      • Source: IET Signal Processing, Volume 3, Issue 2, p. 150 –163
      • DOI:  10.1049/iet-spr:20080123
      • Type: Article
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      • p. 150 –163 (14)
        An adaptive low-complexity space-time reduced-rank processor is proposed for interference suppression in asynchronous DS code division multiple access (CDMA) systems based on a diversity-combined decimation and interpolation method. The novel design approach for the processor employs an iterative procedure to jointly optimise the interpolation, decimation and estimation tasks for reduced-rank parameter estimation. Joint iterative least squares design parameter estimators are described and low-complexity adaptive recursive least squares (RLS) algorithms for the proposed structure are developed. To design the decimation unit, the optimal decimation scheme based on the counting principle is presented and low-complexity decimation structures are proposed. Linear space-time receivers with antenna arrays based on the proposed reduced-rank processor are then presented and investigated to mitigate multi-access interference and intersymbol interference in an asynchronous DS-CDMA system uplink scenario. An analysis of the convergence properties of the proposed space-time processor is carried out and analytical expressions are derived to predict the mean squared error performance of the proposed processor with RLS algorithms. Simulations show that the proposed processor outperforms the best known reduced-rank schemes at substantially lower complexity.
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