a subset of pilots in the local area around the desired resource unit. Decision-aided interpolation [16] reportedly provides the best performance at high SINR (signal-to-interference- plus-noise ratio). But cellular radio systems generally operate in low SINR. For low SINRs, linear techniques have been shown to perform better. Haustein et al. [12] show that the loss in interpolation gain is only a factor of 2 to reduce the computa- tional burden by a factor of 20. A prerequisite for this is an SINR estimation [12], which makes the filter robust. A localized interpolation method has been implemented in Haustein et al. [12] on a Texas Instruments (TI) 6713 DSP operating at 300-MHz clock by applying local interpolation separately in each resource unit. This is done for each pair of transmit and receive antennas. Implementation is simplified by exploiting the fact that inter- polation matrices are independent of frequency when the local pilot grids are iden- tical. This has been taken into account when defining the pilot patterns described later. The precalculated filter matrices are stored according to the estimated signal- to-noise ratio (SNR). Runtime for interpolation over the entire 20-MHz LTE band is 95 us for a 2 x 2 MIMO configuration (i.e., well within the coherence time). © 2009 by Taylor & Francis Group, LLC 300 SC/DSP Weight calc. & SINR est. Short CE Rx1 FFT Rx1 blocks removal Data, Data Tx1, IDFT data FFT Rx1 blocks long blocks stream 1 demod 1 2x2 SDMA/MIMO Multi Spatial separation decoding demapping Data, Data Tx2, IDFT data long blocks stream 2 blocks demod 2 FFT Rx2 removal Short CE Rx2 blocks FFT Rx2 Matrix X vector BLOCK- BLOCK- QAM Demod multiplication Rx processing per OFDM tone demapping demapping eemod CE and MIMO filter calculation Figure 11.2 Functional blocks of the uplink chain. Top: two transmitters of two UEs; bottom: multiuser receiver at one BS. © 2009 by Taylor & Francis Group, LLC Early Real-Time Experiments and Field Trial Measurements Downlink Uplink Antenna 1 Antenna 2 Terminal 1 