Codebook Based Minimum Subspace Distortion Hybrid Precoding for Millimeter Wave Systems

Hybrid precoding is adopted for millimeter wave (mmWave) communications to offer a good trade-off between hardware complexity and system performance. In this paper, we investigate a codebook based hybrid precoder for single-user mmWave systems with large antenna arrays. We exploit the sparse nature of mmWave channels to transform the hybrid precoding design problem into a vector space distortion optimization problem which is only related to the radio frequency (RF) precoder. A near optimal solution for the RF optimization problem is derived with the assumption of the perfect channel state information (CSI) at the transmitter, which is practically very difficult to obtain. To reduce the requirement of the CSI at the transmitter, we propose the codebook based minimum subspace distortion (MSD) hybrid precoding algorithm, which obtains CSI at the combiner side and returns the index of optimal RF codewords and the baseband precoder through a limited feedback channel. Simulation results are provided and validate the effectiveness of our proposed hybrid precoding algorithm.

[1]  Xiaojing Huang,et al.  Massive hybrid antenna array for millimeter-wave cellular communications , 2015, IEEE Wireless Communications.

[2]  Robert W. Heath,et al.  Spatially Sparse Precoding in Millimeter Wave MIMO Systems , 2013, IEEE Transactions on Wireless Communications.

[3]  Robert W. Heath,et al.  Limited Feedback Hybrid Precoding for Multi-User Millimeter Wave Systems , 2014, IEEE Transactions on Wireless Communications.

[4]  Jaspreet Singh,et al.  On the Feasibility of Codebook-Based Beamforming in Millimeter Wave Systems With Multiple Antenna Arrays , 2015, IEEE Transactions on Wireless Communications.

[5]  Taeyoung Kim,et al.  Multi-beam transmission diversity with hybrid beamforming for MIMO-OFDM systems , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[6]  Mohamed-Slim Alouini,et al.  Over-Sampling Codebook-Based Hybrid Minimum Sum-Mean-Square-Error Precoding for Millimeter-Wave 3D-MIMO , 2018, IEEE Wireless Communications Letters.

[7]  Carlo Fischione,et al.  Pilot Precoding and Combining in Multiuser MIMO Networks , 2016, IEEE Journal on Selected Areas in Communications.

[8]  Robert W. Heath,et al.  Low Complexity Hybrid Precoding Strategies for Millimeter Wave Communication Systems , 2016, IEEE Transactions on Wireless Communications.

[9]  Robert W. Heath,et al.  Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems , 2014, IEEE Journal of Selected Topics in Signal Processing.

[10]  Zhen Gao,et al.  Compressive Sensing Techniques for Next-Generation Wireless Communications , 2017, IEEE Wireless Communications.

[11]  Emil Björnson,et al.  A Framework for Training-Based Estimation in Arbitrarily Correlated Rician MIMO Channels With Rician Disturbance , 2010, IEEE Transactions on Signal Processing.

[12]  Robert W. Heath,et al.  Frequency Selective Hybrid Precoding for Limited Feedback Millimeter Wave Systems , 2015, IEEE Transactions on Communications.

[13]  Robert W. Heath,et al.  An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems , 2015, IEEE Journal of Selected Topics in Signal Processing.

[14]  Xiaodai Dong,et al.  Low-Complexity Hybrid Precoding in Massive Multiuser MIMO Systems , 2014, IEEE Wireless Communications Letters.

[15]  Jiaheng Wang,et al.  Codebook-Based Hybrid Precoding for Millimeter Wave Multiuser Systems , 2017, IEEE Transactions on Signal Processing.

[16]  Chen Hu,et al.  Channel Estimation for Millimeter-Wave Massive MIMO With Hybrid Precoding Over Frequency-Selective Fading Channels , 2016, IEEE Communications Letters.

[17]  Olav Tirkkonen,et al.  Joint Grassmann-Stiefel Quantization for MIMO Product Codebooks , 2014, IEEE Transactions on Wireless Communications.