Research On Interference Suppression Algorithms With Low Complexity For Massive MIMO Systems

In order to further meet the increasing capacity demand of wireless communication,the massive MIMO technology and full-duplex(FD)technology have been gradually developed.While improving the system capacity,these technologies increase the computational complexity,hardware complexity and feedback overhead.To this end,it is particularly important to study interference suppression with low computational complexity,interference suppression based on low-cost hardware and interference suppression based on low feedback overhead.The main contributions of this dissertation are as follows:(1)To address the high computational complexity issue of the interference suppression in massive MIMO systems,this dissertation studies the EE-SE-complexity tradeoff,and then a capacity-based EE-SE optimization problem that is formulated.To obtain the optimized results,a normal-boundary-intersection particle-swarm-optimization(NBI-PSO)algorithm is proposed.Compared with the existing weighted-sum algorithms,the proposed NBI-PSO algorithm can evenly produce the complete Pareto front.From the perspective of the practical systems considering the modulation order,a throughput-based EE-SE(TEE-TSE)optimization problem is formulated.Due to the discrete property of the modulation order,the NBI-PSO algorithm cannot converge at the transition point of the modulation order.To this end,a modified NBI-PSO algorithm is also developed and the TEE-TSE tradeoff is obtained.To investigate the performance-complexity tradeoff,an EE-SE-complexity tradeoff problem is formulated.The analysis shows that the NBI-PSO algorithm cannot obtain the complete Pareto surface,and therefore,an extended NBI-PSO algorithm is proposed and the EE-SEcomplexity tradeoff is obtained.(2)To address the high computational complexity issue of the interference suppression in massive MIMO systems,this dissertation studies the low-complexity interference suppression based on the low-rank property of the channel.By exploiting the spatial correlation of the full-dimensional massive MIMO channels,a dominant path zero-forcing precoding(DPZF)scheme is proposed.The proposed DPZF scheme includes two stages.In the first stage,by solving the rank-r channel matrix approximation,the elevation and the azimuth components of r dominant paths for each user’s channel are obtained.In the subsequent stage,the Gram matrix is reformulated with the obtained components so as to zero force the most dominant path of each user’s channel with low complexity.For the proposed DPZF,the upper bound of the performance gap to the conventional ZF is derived and the complexity is analyzed.The analysis and simulation results indicate that the proposed DPZF can yield a more elegant performance-complexity tradeoff than the existing precoding schemes.(3)To address the high hardware complexity issue of the interference suppression in massive MIMO systems,this dissertation studies the interference suppression under one-bit quantization.However,the one-bit quantization brings severe amplitude distortion.The spatial Σ-Δstructure is one important manner that can recover the amplitude information from one-bit quantized signals.Firstly,the spatial degree of quantization noise reduction(DQNR)is defined to analyze the efficiency of suppressing the amplitude distortion via the large-scale antenna array.The analysis shows that the upper bound of the spatial DQNR is 3 for the considered spatial Σ-Δ structure.However,the upper bound is hard to be achieved via conventional schemes,and the achieved spatial DQNR is even not greater than 1 in the worst case.Thus the distortion suppression is inefficient.To address this issue,a random beam shaping(RBS)scheme is proposed,and is proved that it can achieve the spatial DQNR of3.The random beam shaping results in the power leakage of the beams and it may limit the distortion suppression when considering the additive noise.To reduce the power leakage,an accurate beam shaping(ABS)scheme is proposed.In the ABS scheme,the vector for the beam shaping is optimized through the alternative minimization algorithm and the beams are concentrated around the region with low power of quantization noise.The simulation results illustrate that the proposed beam shaping schemes can more efficiently exploit the large-scale antenna array to recover the amplitude distortion due to the one-bit quantization.(4)To address the high feedback overhead issue of the interference suppression in massive MIMO systems,this dissertation studies the interference neutralization(IN)with partial CSIT for full-Duplex cellular networks.The FD communications have the potential to double the throughput of the cellular networks.However,the inter-user interference(IUI)from the uplink(UL)users to the downlink(DL)users severely hinders the improvement of the throughput.To this issue,a new IN scheme is proposed.Before the UL signals are transmitted,their phases are rotated through a set of scalars known by the base station(BS),which endows the conventional receive antennas of the BS with the reconfigurability.The BS assists the IUI management by precoding and forwarding the UL signals to the DL users.Consequently,the UL signals forwarded by the BS locate in the opposite direction of the IUI so as to neutralize it.After the IUI is neutralized,all the symbols of the last time slots can be recovered.The degrees of freedom(Do F)region and the corresponding feasible conditions are analyzed.The analysis and numerical results demonstrate that the maximum achieved sum Do F is 1.5N where N is the antenna number.The IN can achieve the optimal Do F under some system configurations.Especially under the massive MIMO scenario,the IN can achieve 2-fold Do F over the HD counterpart.