Differential Data-Aided Channel Estimation for Up-Link Massive SIMO-OFDM

Abstract

Pilot symbol assisted modulation (PSAM) is widely used to obtain the channel state information (CSI) needed for coherent demodulation. It allows the density of pilot symbols to be dynamically chosen depending on the channel conditions. However, the insertion of pilots reduces the spectral efficiency, more severely when the channel is highly time-variant and/or frequency-selective. In these cases a significant amount of pilots is required to properly track the channel variations in both time and frequency dimensions. Alternatively, non-coherent demodulation does not require any CSI for the demodulation independently of the channel conditions. For the particular case of up-link (UL) based on massive single input-multiple output (SIMO) combined with orthogonal frequency division multiplexing (OFDM), we propose to replace the traditional reference signals of PSAM by a new differentially-encoded data stream that can be non-coherently detected. The latter can be demodulated without the knowledge of the CSI and subsequently used for the channel estimation. We denote our proposal as hybrid demodulation scheme (HDS) because it exploits both the benefits of a coherent demodulation scheme (CDS) and a non-coherent demodulation scheme (NCDS) to increase the spectral efficiency. The mean squared error (MSE) of the channel estimation, bit error rate (BER), achieved throughput and complexity are analyzed to highlight the benefits of this differential data-aided channel estimation as compared to other approaches. We show that the channel estimation is almost as good as PSAM, while the BER performance and throughput are improved for different channel conditions with a very small complexity increase.

Non-coherent massive MIMO-OFDM for communications in high mobility scenarios

“…The advantages of NCDS with respect to CDS vanish when the channel is quasi-static and with high SNR. Then, it is advisable to ind hybrid schemes, such as [20] where the best of both paradigms is used according to the communication scenario and needs. Finally, it is foreseen that in the future communications will be tightly integrated with sensing, which is one of the main objectives of the the Sixth Generation (6G) of mobile communications [38].…”

“…these are mainly characterized by a signi icant Doppler spread due to the high mobility. In these situations, the traditional CDS requires an enormous amount of reference signals in order to continuously and accurately track the variations of the channel, reducing considerably the overall ef iciency of the system, as pointed out in [10], [11], [20]. Otherwise, if the CSI is not properly estimated, the performance of the CDS is also seriously compromised.…”

“…This overhead can be excessively high for very fast time-varying channels. In such cases, a signi icant number of reference signals is required for the continuous tracking of the channel estimation [20].…”

“…The works in the literature have provided the theoretical foundations to understand NCDS and point to some cases when they can outperform the traditional CDS, in particular in scenarios with high mobility [20]. Also, recent works show some combinations of NCDS with MIMO-OFDM for the uplink (UL) and downlink (DL).…”

Effect of Spatial Correlation on the Performance of Non-coherent Massive MIMO based on DMPSK

“…Several reference signals (pilots) must be used to estimate the channel state information (CSI). In high mobility, high frequency selectivity and/or low SNR scenarios, the use of CSI is problematic, since many pilots may be needed [2], [3], thus making the coherent processing potentially unfeasible.…”