 This happens because the ISI between the pilot symbols dominates at the high SNR. As Z increases to 3, both the CSI estimation methods receiver NMSE improvement due to the reduced effect of the ISI. Furthermore, the SB CSI estimator in the presence of imperfect Wm achieves a performance close to its CRLB. This shows that fixing Z = 3 gives the ideal spectral efficiency versus NMSE trade-off, because the CRLB is nothing but the best possible estimation performance of an estimator. P. Singh and E. Sharma 3.5 Performance of FBMC Waveform in Uplink of Massive In recent years, massive MIMO technology has received widespread popularity because of its ability to support a large number of users with high throughput [55]. By using a few hundred antennas at the base station, the massive MIMO technology achieves the favourable propagation, which mitigates the co-channel interference by employing linear receivers, namely, ZF, MMSE and maximum ratio combining (MRC). This leads to a significant enhancement in spectral efficiency. OFDM is being used with massive MIMO technology for 5G deployment. However, OFDM- based systems are susceptible to practical impairments associated with carrier and timing offsets, particularly in the uplink wherein it is difficult to track the Doppler spreads experienced by different users [5, 6]. The aim of this section is to analyse the uplink performance of FBMC waveform in the context of MU massive MIMO technology. 3.5.1 Review of Existing Works Reference [56] showed that the signal-to-interference-plus-noise ratio (SINR) of FBMC waveform-based massive MIMO technology over frequency-selective channel saturates to a deterministic value that depends on the correlation between the channel impulse responses and weights of multi-antenna combining taps. Aminjavaheri et al. in [21] developed an equalizer to mitigate the SINR saturation in [56]. References [57, 58] compared OFDM and FBMC waveforms in the massive MIMO setup and highlight the benefits of the latter over the former in terms of (i) sensitiv