Hei Yongqiang

Low complexity asymptotically unitary algorithm for hybrid beamforming in mmWave communication systems

Abstract In millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, because of the high hardware cost and high power consumption, the traditional fully digital beamforming (DBF) cannot be implemented easily. Meanwhile, analog beamforming which is implemented with phase shifters has high availability but suffers poor performance. Considering the advantages of above two, a potential solution is to design an appropriate hybrid analog and digital beamforming structure, where the available iterative optimization algorithm can get performance close to fully digital processing, but solving this sparse optimization problem faces with a high computational complexity. The key challenge of seeking out hybrid beamforming (HBF) matrices lies in leveraging the trade-off between the spectral efficiency performance and the computational complexity. In this paper, we propose an asymptotically unitary hybrid precoding (AUHP) algorithm based on antenna array response (AAR) properties to solve the HBF optimization problem. Firstly, we get the optimal orthogonal analog and digital beamforming matrices relying on the channels path gain in absolute value by taking into account that the AAR matrices are asymptotically unitary. Then, an improved simultaneously orthogonal matching pursuit (SOMP) algorithm based on recursion is adopted to refine the hybrid combining. Numerical results demonstrate that our proposed AUHP algorithm enables a lower computational complexity with negligible spectral efficiency performance degradation.

Performance analysis of RC-SRake receiver in ultra-wideband communication under IEEE 802.15.4a channel

In ultra-wideband impulse radio (UWB-IR) system, Rake receiver can take advantage of the high degree of diversity that results from a large number of multipath components (MPCs). In this paper, we propose a reduced-complexity selective Rake (RC-SRake) receiver scheme under ultra-wideband multipath channels. It employs a convolution based finger estimation algorithm, which has minimal complexity that does not require precise channel information. We derive a closed-form expression for symbol error probability (SEP) of the proposed Rake receiver in term of the combined fingers and impulse noise. We evaluate these expressions numerically under various IEEE 802.15.4a channel models. It is observed that a similar ability of energy capture can be obtained with less than 10 fingers as compared to the ideal SRake. More importantly, as the number of combined fingers increases, the performance of our RC-SRake receiver improves in general despite occasional degradation due to the estimation error of impulse noise.

Multi-user MIMO Broadcast System Grouping Strategy Based on Particle Swarm Optimization

A new grouping strategy based on particle swarm optimization (PSO) is proposed for the multiuser MIMO broadcast systems in this paper. Aiming at maximizing the system capacity, the PSO algorithm is introduced to seek the best users group. Besides, two objective functions in PSO applicable for the cases of different requirements on capacity and complexity are also presented, which can be denoted as PSO_I algorithm and PSO_II algorithm respectively. Simulation results reveal that the PSO_I strategy achieves nearly the same capacity performance to the optimal exhaustive search (ES) algorithm, and the PSO_II algorithm is slightly worse than PSO_I algorithm in terms of capacity performance, but with lower complexity.

Gram-Schmidt based hybrid beamforming for mmWave MIMO systems

Abstract Due to the high cost and power consumption of the radio frequency (RF) chains, it is difficult to implement the full digital beamforming in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. Fortunately, the hybrid beamforming (HBF) is proposed to overcome these limitations by splitting the beamforming process between the analog and digital domains. In recent works, most HBF schemes improve the spectral efficiency based on greedy algorithms. However, the iterative process in greedy algorithms leads to high computational complexity. In this paper, a new method is proposed to achieve a reasonable compromise between complexity and performance. The novel algorithm utilizes the low-complexity Gram-Schmidt method to orthogonalize the candidate vectors. With the orthogonal candidate matrix, the slow greedy algorithm is avoided. Thus, the RF vectors are found simultaneously without any iteration. Additionally, the phase extraction is applied to satisfy the element-wise constant-magnitude constraint on the RF matrix. Simulation results demonstrate that the new HBF algorithm can make substantial improvements in complexity while maintaining good performance.