Pilot Optimization for Structured Compressive Sensing Based Channel Estimation in Large-Scale MIMO Systems with Superimposed Pilot Pattern

Compressive sensing (CS) has attracted much attention in wireless communications due to its ability to attain acceptable channel estimates with a small number of pilots. To further reduce the pilot overhead in multi-input multi-output (MIMO) systems, CS-based channel estimation may employ superimpos...

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Bibliographic Details
Published in:Wireless personal communications 2018-06, Vol.100 (3), p.977-993
Main Authors: Cai, Jun, He, Xueyun, Song, Rongfang
Format: Article
Language:English
Subjects:
Acceptable noise levels
Communications Engineering
Computer Communication Networks
Computer simulation
Criteria
Engineering
Genetic algorithms
Ill posed problems
MIMO (control systems)
Networks
Performance enhancement
Pilots
Signal,Image and Speech Processing
Wireless communications
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Summary:Compressive sensing (CS) has attracted much attention in wireless communications due to its ability to attain acceptable channel estimates with a small number of pilots. To further reduce the pilot overhead in multi-input multi-output (MIMO) systems, CS-based channel estimation may employ superimposed pilot pattern. Previous works on superimposed pilot design generally allocate pilots randomly, which may give ill-posed measurement matrices. In this paper, we focus on deterministic pilot allocation for large-scale MIMO systems with superimposed pilot pattern to improve the performance of structured CS based channel estimation. By exploiting the spatial common sparsity and the error bound of block sparse reconstruction, a new criterion is firstly proposed to optimize the pilots in the Hadamard space. The proposed criterion makes full use of the information about the principal angles across the blocks in the measurement matrix, which can enhance the average recovery ability and exclude the worst pilots simultaneously. Secondly, a genetic algorithm is proposed to minimize the merit factor of the proposed criterion efficiently. Simulation results show that the proposed optimized pilots outperform the random pilots in terms of mean-squared error by about 3 dB. Moreover, the proposed criterion is more likely to achieve better measurement matrices than the traditional criteria.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-018-5361-x