The MU-MIMO Beamforming Design And Its Applications In IEEE 802.11ax

Multiple input multiple out(MIMO) technology can improve systems capacity and spectral efficiency, without increasing the cost of system, just need to take into count the spatial dimension, 802.1 lax will take MIMO technology to its standard, multiuser MIMO technology can provide multi-user gain. However, it will introduce co-channel interference(CCI), if not eliminate CCI, it will seriously affect systems performance. By applying beamforming weights to the transmitted signal, it can degrade the influence of CCI, and improve the performance.In this paper combined the requirements of 802.1 lax, research the beamforming algorithm from three considerations:The computational complexity of algorithm, whether taking into account the impact of CCI and noises, as well as whether it can work under the imperfect CSI conditions. The beamfroming algorithm under perfect CSI conditions and present the modified precoding method for the system with the channel with estimation errors. Also, apply those methods to the system on 802.1 lax.Under the perfect CSI conditions, we discuss the BD algorithm and SLNR_based algorithm. The BD algorithm attempts to completely eliminate the CCI without any consideration on the noise, the performance of the BD will limited by noise. GMI is based on BD, it can balance the CCI and the noise for each user. Similar to the BD algorithm, GMI algorithm used the QR-decomposition to get the nullspace of interference matrix of channel, and used a modification matrix to eliminate the residual interference. Simulation results confirm that the GMI precoding exhibits a linear growth of the sum rate, as opposed to the BD scheme. And can provide more BER gain over the conventional BD scheme. The leakage-Based precoding criterion leads to a decoupled optimization problem and admits an analytical closed form solution, thereby causing extensive academic research. However, under the conventional leakage-based precoding, the effective channel gain for each stream can be severely unbalanced, it would lead to poor over error performance for a user. In order to conquer this drawback, we consider a new proposal scheme, slight relaxation on the SLNR maximization. Simulation results demonstrate that the new precoding achieves considerable gains in error performance over the conditional leakage-based scheme for multi-stream transmission while maintaining almost the same achievable sum-rate. At the same time, taking into the cost of leakage-base algorithm, consider a less computational complexity scheme.In actual communication system, it’s hard to get the perfect channel state information, therefore we should study on the beamfroming algorithm under the imperfect CSI conditions. Combined the GMI algorithm and Leakage-base algorithm under perfect CSI conditions, consider the system with channel estimation errors, we re-verified the GMI algorithm and the SLNR optimization problem, obtained beamfroming algorithm suitable for limited feedback scenarios.Based on the theory research, this paper apply those algorithms to 802.11 ax under perfect and imperfect CSI conditions, and take account of the different channels, the number of subcarriers and other configuration. This paper confines that GMI and SLNR algorithms are suitable for 802.11 ax.