| In 5G and future B5G/6G wireless networks,millimeter-wave(mm Wave)bands will be used to meet the capacity demand of future network due to its advantage of huge bandwidth.However,mm Wave signals experience higher propagation loss compared to sub-6GHz bands,which limit the network coverage.Thanks to the small wavelength of mm Wave signals,mm Wave systems can leverage massive multiple input multiple output(MIMO)antennas packed into a small form factor,which can provide significant beamforming gains to combat the severe propagation loss.Moreover,combined with the cooperative transmission technology,the network coverage can be further extended and the severe line-of-sight(Lo S)blockage can be avoided for mm Wave systems.However,limited by the current semiconductor industry development,the mm Wave massive MIMO system faces the challenges of high complexity,cost and power consumption.To address above challenges,the analog-digital hybrid array architecture and the low-resolution analog-to-digital converters(ADCs)/digital-to-analog converters(DACs)transceiver emerged.For different application scenarios,choosing suitable hardware architecture is a direct and effective solution to reduce system complexity.However,the low complexity hardware architecture and the wideband effect of large-scale antenna array lead to the degradation of system performance.Thus,robust communication signal processing algorithms are needed to combat the system performance loss caused by hardware impairments.Moreover,there are multiple nodes in relay systems,which make the optimal design of the system more complicated.To this end,this dissertation mainly studies the low-complexity hardware architecture for mm Wave massive MIMO systems,and proposes effective high-precision relay channel estimation algorithms and robust beamforming algorithms to improve the system performance.The main contents and contributions of this dissertation are summarized as follows.Firstly,this dissertation discusses an overlapped subarray between traditional fullyconnected and sub-connected structures and determine how many antennas should be connected for each radio frequency(RF)chain in hybrid antenna array.Moreover,for the mm Wave downlink multi-user MIMO communication,this dissertation designs a twostage hybrid beamforming algorithm based on the overlapped subarray structure.Simulation results indicate that there exists the most cost-effective overlapped subarray spacing associated with the required number of phase shifters for the sparse mm Wave channel.Our analysis provides a guideline for the design of hybrid antenna array architecture.Secondly,this dissertation proposes a series of high-precision two-timescale channel estimation algorithms by exploring the two-timescale characteristics of dual-hop channel in practical MIMO relay systems.Specifically,in mobile cellular networks,the location of the macro-cell base station(BS)and the relay station(RS)are generally fixed,whereas the user equipments(UE)are in moving state.Thus,the dual-hop MIMO channel follows the two-timescale characteristics,i.e.,the UEs-RS channel varies in a short-timescale manner,whereas the RS-BS channel varies in a long-timescale manner.To this end,this dissertation formulates the two-timescale channel estimation problem as an approximate maximum likelihood(AML)problem with the one-stage training(OST)scheme.Then,a batch(AML-Batch)algorithm is designed to solve the resultant optimization problem.Moreover,to overcome the drawbacks of batch algorithm,a low-complexity online(AML-Online)algorithm is proposed based on the two-stage stochastic optimization framework.Simulation results show that the performance of the proposed two-timescale estimation algorithms is better than that of the traditional single-timescale estimation algorithms.Furthermore,considering mm Wave cooperative systems with the intelligent reflection surface(IRS),this dissertation proposes a two-timescale compressed channel estimation algorithm by exploring the structure sparsity characteristics of the cascaded channel,which can reduce the pilot overhead and improve the estimation accuracy.Thirdly,this dissertation studies the robust beamforming problem for massive MIMO multi-pair two-way relay systems with low-resolution ADCs/DACs to reduce the performance loss caused by low-resolution ADCs/DACs and obtain satisfactory performance in massive user access scenarios,Based on the separated minimum mean square error(MMSE)scheme,this dissertation proposes a robust MMSE(R-MMSE)beamforming algorithm.Simulation results show that the proposed R-MMSE algorithm can reduce the performance loss caused by low-resolution ADCs/DACs,and the performance of proposed R-MMSE algorithm is better than that of the traditional nonrobust algorithms.Finally,this dissertation studies the array wideband effect on wideband mm Wave ultra-massive antenna array systems.When the number of antennas and the signal bandwidth are very large,the narrowband array signal processing model is not suitable.Thus,the signal must be treated as a wideband signal.this dissertation analyzes the influence of non-zero bandwidth on narrowband multiple signal classification(MUSIC)algorithm in ultra-massive antenna array systems,and conclude that there exists a critical bandwidth point.Then,we study the wideband effect on wideband mm Wave ultramassive phased array.In the phased array,the wideband effect is also called as beam squint effect.With the standard analog beamforming method,we view the analog beamforming and the physical channel as a spatial equivalent channel.It can be observed that the beam squint causes obvious beamforming gain loss and the spatial equivalent channel becomes a frequency-selective channel with multiple deep fading points.To eliminate the deep fading points,an advanced analog beamforming method is proposed based on constant envelope zero auto-correlation(CAZAC)sequence.Finally,the biterror-rate(BER)performance of mm Wave single-carrier frequency-domain equalization(SC-FDE)system is simulated to verify the effectiveness of the proposed method. |
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