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An Orthogonal Frequency Division Multiplexing (OFDM) receiver detects and corrects sampling offsets in the time domain. The OFDM receiver oversamples a training sequence or symbol in a received OFDM signal, correlates the oversampled training sequence with a stored copy of a truncated version of the

An Orthogonal Frequency Division Multiplexing (OFDM) receiver detects and corrects sampling offsets in the time domain. The OFDM receiver oversamples a training sequence or symbol in a received OFDM signal, correlates the oversampled training sequence with a stored copy of a truncated version of the training sequence, locates a correlation peak, and derives a sampling offset by calculating a difference in magnitude of correlation samples in the vicinity of the correlation peak.

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An Orthogonal Frequency Division Multiplexing (OFDM) receiver detects and corrects sampling offsets in the time domain. The OFDM receiver oversamples a training sequence or symbol in a received OFDM signal, correlates the oversampled training sequence with a stored copy of a truncated version of the

An Orthogonal Frequency Division Multiplexing (OFDM) receiver detects and corrects sampling offsets in the time domain. The OFDM receiver oversamples a training sequence or symbol in a received OFDM signal, correlates the oversampled training sequence with a stored copy of a truncated version of the training sequence, locates a correlation peak, and derives a sampling offset by calculating a difference in magnitude of correlation samples in the vicinity of the correlation peak. the motion vector of the one of said segmented macroblocks with the largest said area-activity product. 4. The system of claim 1, wherein said means for classifying calculates a sum for each of said sub-windows of the magnitude of its motion vectors, compares the sum with a threshold, and classifies the sub-window as active or static in accordance with a comparison result. 5. The system of claim 1, wherein said means for processing obtains said outgoing motion vectors by, after a frame of a static sub-window is skipped, composing motion vectors of each skipped and non-skipped sub-window relative to its corresponding latest encoded sub-window. 6. The system of claim 1, wherein said dominant vector selection operation is a forward-dominant vector selection operation. 7. A video communication method comprising: (a) receiving multiple incoming encoded digital video signals respectively sent over plural transmission paths from a plurality of video devices; (b) processing said received video signals; (c) combining the processed video signals into an output video signal comprising a single coded video bit stream; and (d) transmitting the output video signal through said transmission paths to said plurality of video devices, respective portions of said output video signal corresponding to said video signals sent from said plurality of video devices constituting sub-windows of said output video signal; wherein processing step (b) comprises: (i) classifying said sub-windows into active sub-windows and static sub-windows; and (ii) generating said output video signal by (1) transcoding frames of said active sub-windows while skipping transcoding of frames of said static sub-windows and substituting a latest corresponding encoded sub-window for a skipped sub-window to approximate the skipped sub-window, and (2) obtaining outgoing motion vectors of said output video signal from incoming motion vectors of said active sub-windows and said static sub-windows by obtaining a motion vector of a non-aligned macroblock which is not aligned with segmented macroblock boundaries in said sub-windows by a dominant vector selection operation comprising pre-filtering out unreliable motion vectors of said segmented macroblock boundaries and selecting the one of said segmented macroblock boundaries having the largest overlapping activity as the dominant block, and selecting the motion vector of said dominant block as said motion vector of said non-aligned macroblock. 8. The method of claim 7, wherein said prefiltering step comprises determining whether a strongly overlapping dominant block exists among said segmented macroblocks. 9. The method of claim 8, wherein: (i) said step of determining whether a strongly overlapping dominant block exists among said segmented macroblocks comprises: calculating the largest overlapping area of each of the segmented macroblocks with said non-aligned macroblock, and if the largest overlapping area of one of the segmented macroblocks is greater than a predetermined threshold, then selecting the motion vector of the one of said segmented macroblocks with the largest overlapping area as the dominant vector, and if the largest overlapping area is not greater than said predetermined threshold, then setting an initial candidate list as the four motion vectors {IV1,IV2,IV3,IV4} of the four segmented macroblocks, calculating the mean and the standard deviation of said four motion vectors in accordance with the relation: for i=1 to 4, if |IVi-IVmean|>kstd·IVstd,removing IVifrom the candidate list as unreliable, and if not, keeping IViin the candidate list as reliable; (ii) said step of determining said largest overlapping activity comprises, for each motion vector on the candidate list, calculating an area-activity product Ai·ACTi, i=1,2,3,4, where Ai is the overlapping area with the neigh