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Index Modulation And Its Application In Massive Machine-type Communications

Posted on:2021-02-14Degree:DoctorType:Dissertation
Country:ChinaCandidate:X X MaFull Text:PDF
GTID:1368330605969574Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
With the rapid development of mobile communications,the explosive growth of mobile data,the massive connection of mobile devices,and the extreme re-quirements of mobile services obstruct the improvement of mobile communication performance because of the limited spectrum resources,the limited energy con-sumption and the interference.Three major application scenarios:Enhance Mo-bile Broadband(eMBB),Massive Machine-type Communications(mMTC)and Ultra-Reliable Low Latency Communications(uRLLC)bring new requirements for the design of key technologies in the future mobile communication system.Index modulation technology as a promising cost and low complexity technology is beneficial for tradeoff spectral efficiency and energy efficiency.Index modulation technology,especially the spatial modulation technology and media modulation technology among them,are the research objects in this pa-per.The main research goal is to improve transmission reliability and spectrum efficiency and expand the index modulation technology to Massive Machine-type Communications(mMTC)scenario.Start by digging into the random transmis-sion characteristics of index modulation technology and the special sparse struc-ture.The main difficulties of this paper are diversity gain design with arbitrary antennas,interference management design for non-fixed interference subspaces,and joint detection of user activation and symbol of index modulation.Hence,four parts of the research work are carried out.The main research contents and innovations of this paper are as follows:1.High spectral efficiency and transmit diversity are obtained based on the design of index modulation without the limitation for the number of trans-mit antennas and the number of activated antennas.For a point-to-point multiple antenna system,index modulation cannot provide diversity gain.The current design of diversity gain for the index modulation is limited by antenna configuration and highly complicated rotation angle optimization.By combining spatial modulation and media-based modulation,a space-time coding mapping criterion is proposed to comprehensively consider the antenna domain and the channel domain.The real part and imaginary part of the transmitted symbol are separated and selected different map-ping criteria to further improve spectral efficiency.By considering the block sparsity caused by spatial modulation and the inter-block sparsity caused by media-based modulation,a hierarchical block sparse Bayesian learning algorithm is designed.2.Based on index modulation,an interference alignment scheme for non-fixed interference subspace is proposed where the receiver can obtain the maximum degree of freedom.For a two-user interference channel network,due to the random activation of index modulation,the interference gen-erated by index modulation has no fixed interference subspace,and the interference subspace changes with different time slots.By analyzing the interference characteristics generated by the index modulation,an interfer-ence alignment scheme for non-fixed interference subspace is designed;and this interference alignment scheme can be extended to complex interference channel networks.3.Massive machine-type communications in future mobile communications have two major characteristics:large-scale user equipment and sporadic user activation.Index modulation as a promising modulation transmis-sion scheme to require the low complexity,low-power in Massive machine-type communications.For the uplink index modulation system in Massive machine-type communication scenarios,the sparse user activation and s-parse index activation constitute a two-level sparse structure.And most active users remain transmission in adjacent time slots.By considering the two-level sparse structure and fixed user activation,we design a compres-sive sensing algorithm that jointly detects the user activation and index activation,with a low complexity algorithm.4.From the fixed user activation mode in Chapter.4 to the dynamic user ac-tivation mode without channel state information at receivers,a compressive sensing algorithm is proposed to joint channel estimation,user activated detection and index activated detection.In the dynamic user activation,the users can randomly access or leave the network and the activated users change with time-slots.Hence the total number of activated users is not known by the base station.The sparse user activation and sparse index activation still constitute a two-level sparse structure,but the position of the activation and the total number of non-zero position can change ran-domly.Therefore,a compressed sensing algorithm that jointly detects the user activation and the symbol of index modulation is proposed with adap-tively estimating the total number of active users per time-slot.Finally,considering unknown channel state information,a compressed sensing al-gorithm for joint channel estimation,user activation,index activation,and modulated symbol is proposed.
Keywords/Search Tags:Index Modulation, Multiple-Input Multiple-Output, Spatial Modulation, Massive Machine-type Communications, Compressive Sensing
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