36, 43-46], the semi-blind MIMO-FBMC scheme leverages the pilot symbols along with blind data symbols for estimating the unitary and whitening components of the channel matrix Hm. It is thus offered significantly lower MSE than the existing IAM model-based LS CSI estimation scheme that utilises only pilot symbols. The Cramer-Rao lower bounds (CRLBs) are derived to quantify the MSE gain of the semi-blind method over the pilot-based techniques. 3.4.2 Semi-Blind MIMO-FBMC Channel Estimator Let the th antenna transmit Lo symbols on each of the subcarriers, as shown in the frame in Fig. 3.3. Each frame consists of M pilot symbols to be utilised for estimating CSI. The Nd symbols at the end of the frame carry data. Unlike OFDM, adjacent time-domain FBMC symbols interfere with each other because of the overlapping of the pulse-shaping filters. Thus, Z. zeros are placed between the adjacent pilot symbols to mitigate the ISI [24, 26]. Due to the inter-frame time gap commonly used in wireless systems, one does not need to insert zeros in the P. Singh and E. Sharma {dm,0]m=1 d'm,(M-1)(2+1)]M=0 z, zeros z,zeros Symbol time index , n Lo,Symbols N ,,data symbols Fig. 3.3 Placement of symbols in the frame for the th antenna at the FBMC transmitter. Here and X respectively, represent the pilot, zero and data symbols beginning of the frame [24]. The effect of varying Z on the MSE of the semi- blind and conventional pilot-based CSI estimation schemes is shown later using simulations, which demonstrates that employing Z = 1 is sufficient for reducing the ISI to a tolerable level. This implies that MIMO-FBMC frame with zeros employs 2M OQAM symbols on each of the subcarriers for CSI estimation, which is equivalent to M QAM symbols [24]. The channel estimation pilot overhead in MIMO-FBMC is therefore same as that of MIMO-OFDM systems [47]. As shown in Fig. 3.3, the pilot symbols are located at n = i(1 + z) for Oi M - 1. Evaluating (3.33) at these instants and stacking the resulting observations, one gets (3.35) Here the virtual pilot