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The networking environment allowing for coexistence of voice and data communication has become complex, and voice aspects of telecommunication, particularly in voice-over-IP networks, demand echo cancellers to cover all voice channels, as opposed to only long-haul channels, as it used to be in traditional public switched telephone networks. Echo path coverage requirements for the echo cancellers have become more demanding, which contributed to an increase of computational cost of their implementations. One of the methods of decreasing that cost is via taking advantage of sparseness of the echo path impulse response (sparse systems). In addition to requirements related to reducing an overall computational cost, it is desirable to accelerate the adaptation, so the voice quality is improved. In the case of sparse systems, the requirement of accelerating the adaptation translates into faster allocation of the main adaptive filter window. This study explores an approach that takes advantage of the relation between the FIR filter length and the convergence speed, with focusing of the subrate adaptive filter that is being used for identifying the pure delay. The proposed approach is suitable for single reflectors. The proposed idea can be expanded to cover multi-reflectors. The presented results of numerical experiments relate to the NLMS. Yet the approach is general and can be applied to other adaptive filter algorithms. The computational overhead associated with the parallel structure (and related decision algorithm) is tangible yet quite minor. This additional cost is split over two distinct parts: (a) filter window overlap to ensure the echo path delays that fit to the parallel structure partitioning are treated without disadvantage and (b) the additional decision logic that is used to identify the position (within one of the M parallel branches covering approximately 1/Mth of the entire echo path coverage each) of the echo path impulse response peak. The principal ben- - efit of the parallel structure is the adaptation speed increase (and this increase is a function of M) at an expense of only very minor computational cost.
Date of Conference: 19-21 March 2008