ap channel impulse response between the th transmit and the rth receive antenna pair. The noise n'[k] at the rth receive antenna obeys CN(0, o,2). Following the procedure described in the SISO-FBMC system, the received signal on the rth antenna at subcarrier m and symbol instant nth, after passing through the receive filter bank, is obtained as (3.31) where the complex quantity Hut symbolises the CFR between the th transmit and the rth receive antenna pair at the mth subcarrier and is computed as Hut = The demodulated noise = obeys CN(0, o2). The term bm.n = dm.n + jlm, is the virtual symbol for the th transmit antenna, where the associated intrinsic interference I'm,n is given as (3.32) (m,n)ESum,n For mathematical lease, (3.31) can be written in vector form as (3.33) where the vector Nm,n = mm.n.TI E CNrx1 comprises noise with the covariance matrix days = CNrx1 is the observation symbol vector across Nr receive antennas. The vir- tual symbol vector bm,n = has a covariance element of the MIMO CFR matrix Hm E CNrxNt at the mth subcarrier is given as Hut The observed symbols ym,n'ym,n' , ym.n are equalized, followed by the operation R(.), which pulls out the estimate of OQAM symbols from the estimated virtual data vector bm,n = bm.n.Tr. Finally, the vectors am,2n = dm.2n17 and = dm.2n+1.1T on each subcarrier are clubbed P. Singh and E. Sharma together for constructing QAM symbol vector as + m m (3.34) even. 3.4 MIMO-FBMC Semi-Blind CSI Estimation Channel state information (CSI) at receiver is typically acquired using pilot sym- bols, which do not carry information, and therefore, transmission of pilot symbols results in spectral efficiency loss. Due to the diversity gain offered by MIMO technology, the required signal-to-noise-ratio (SNR) for the desired bit-error-rate performance decreases. In such low SNR regimes, pilot-based CSI estimation methods demand large overheads for providing a reliable CSI estimate. Therefore, this section aims to develop a semi-blind channel estimation scheme for FBMC- based MIMO tech