Design Of Channel Estimation Schemes For Irs Assisted Millimeter Wave Massive MIMO Systems Based On Compressed Sensing

The Intelligent Reflecting Surface(IRS)has garnered significant attention as an alternative technology in B5 G and 6G wireless communication systems due to its ability to intelligently manipulate the wireless signal propagation environment,thereby enhancing system capacity and coverage.IRS can reconstruct the wireless propagation environment by intelligently adjusting the phase shifts of its reflecting elements to reflect signals from the transmitter to the desired receiver in a controlled manner.Accurate Channel State Information(CSI)acquisition is crucial for signal processing in IRS-assisted communication systems.However,the complexity of channel estimation in IRS-assisted millimeter-wave massive MIMO communication systems is high due to the large number of nearly passive and low-cost reflecting elements carried by IRS,and it typically requires a significant pilot overhead to obtain accurate CSI.Therefore,designing channel estimation algorithms with low complexity,low pilot overhead,and high accuracy poses a challenge for IRS-assisted millimeter-wave massive MIMO communication systems.Compressive sensing(CS)techniques hold promise as a powerful approach to achieving low-complexity and low-training-overhead channel estimation.This thesis primarily investigates channel estimation schemes for IRS-assisted millimeter-wave massive MIMO systems based on compressive sensing techniques.The main contributions are as follows:(1)For the channel sparsity characteristics of a single-IRS-assisted millimeter-wave massive MIMO system,a channel estimation scheme based on the K-means Based Adaptive DoubleStructured Orthogonal Matching Pursuit(KADS-OMP)algorithm is proposed.The performance advantages of this scheme under low signal-to-noise ratio and low pilot overhead are verified through computer simulations.(2)For the millimeter-wave angular expansion channel structure of a single-IRS-assisted millimeter-wave massive MIMO system,a channel estimation scheme based on the Adaptive TripleStructured Orthogonal Matching Pursuit(ATS-OMP)algorithm is proposed.The performance advantages of this scheme under different signal-to-noise ratios and pilot overheads are validated through computer simulations.(3)For the triple compressibility of the channel model in a dual-IRS-assisted millimeter-wave massive MIMO system,a channel estimation scheme based on the Adaptive Triple Compression OMP(ATC-OMP)algorithm is proposed.Building upon this algorithm’s compressibility,a channel estimation scheme based on the Adaptive Structured Double Compression OMP(ASDC-OMP)algorithm is further proposed,which exhibits excellent channel estimation performance at low signalto-noise ratio and low pilot overhead compared to the ATC-OMP algorithm.Finally,the effectiveness of the proposed algorithms is verified through computer simulations.