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Research On Key Technologies Of Massive MIMO Wireless Communication System For B4G/5G

Posted on:2017-09-02Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y WangFull Text:PDF
GTID:1318330515458336Subject:Information and Communication Engineering
Abstract/Summary:PDF Full Text Request
To meet the challenge of significant and continuing growth of wireless communication traffic and intel-ligent terminals,the industry has embarked researching and standardizing of the 5th generation(5G)mobile communication system that is to be commercialized in the year beyond 2020.Especially,the industry has redefined eight key indexes which include user experience rate,mobility,end-to-end latency,connection density,traffic density,network spectral and energy efficiency and so on.In order to satisfy these require-ments by virtue of limited time and frequency resource,superhigh effective wireless transmission techniques are introduced to 5G which can further excavate the potential of improving spectral efficiency.Among these,the massive MIMO based wireless transmission technology has greatest chance to improve the spectral and power efficiency by order of magnitude without any extra cost of time and frequency overhead.By utilizing a large number of antennas,massive MIMO exploits the spatial resource deeply and brings many transmission and physical characteristics,which are different from conventional MIMO system.Thus,massive MIMO has been widely considered as one of the most sought-after and disruptive technologies for the 5G wireless com-munication systems.However,to facilitate the massive MIMO technology,there are still many open issues that need to be solved,such as,appropriate pilot overhead scheme and pilot design for FDD massive MIMO systems,high energy-efficiency based resource allocation for green massive MIMO,capacity analysis of the heterogeneous massive MIMO and distributed massive MIMO systems,the effects of channel time-varying characteristic on the massive MIMO systems with user mobility and so on.Based on these,we conduct the topic "Research on Key Technologies of Massive MIMO Wireless Communication System for B4G/5G",the main contributions are listed as follows:1.For a massive MIMO downlink frequency division duplex(FDD)system over general correlated Rayleigh fading channel,we investigate the impacts of the pilot sequence length on the ergodic achievable rate,which varies with the number of base station antennas at different speed,and then derive the analytical expression of achievable rate with respect to(w.r.t.)the training sequence length.It is discovered from the analytical results in two-fold that(1)the length of training sequence normalized by the antenna number approaches to zero yet the system capacity is guaranteed to be positive infinity as long as the antenna number is large enough;(2)the transmission capability saturates to a certain level if the antenna number grows to very large with any given training length.Furthermore,for a given training sequence length,we propose an optimal pilot design based on the achievable rate maximization,which combines the effect of channel estimation into the final performance of rate.Simulation results verify the theoretical derivations and the performance gain of our proposed optimal pilot structure.2.The energy efficient resource allocation problem is investigated for the downlink massive MIMO FDD system,which considers the channel estimation and data transmission simultaneously.Our objective is to maximize energy efficiency(EE)by adjusting the training duration,training power and data power,under the constraint of total transmit energy and spectral efficiency requirement of the user.Due to the complicated form of the established problem,the deterministic equivalent approximation methodology is introduced to obtain an analytical expression of the cost function.Based on this,the optimization problem in non-convex fractional form is transformed into an equivalent optimization problem with parametric subtractive form by using fractional programming.Then,with the lower bound of spectral efficiency,the transformed objective function is relaxed to a concave form and finally a 3-layer iterative resource allocation algorithm is proposed to solve it.Moreover,we obtain the closed-form solutions using the Lambert W function for some special channel cases.Numerical results validate the benefits of the proposed scheme and illustrate the tradeoff between training and data transmission.3.We investigate the spectral efficiency(SE)and power scaling laws for a massive MIMO relaying sys-tem with multi-pair users under different CSI conditions,when the relay node adopts different processing schemes.Firstly,we derive the closed-form expression of the SE,based on which,it is shown that(1)For perfect CSI,the SE per user increases with the number of relay antennas but decreases with the number of user pairs,both logarithmically,with MRT and ZF precoding.(2)For imperfect CSI,the SE performance w.r.t.the antenna number still holds as above,but it becomes more complicated w.r.t.the user-pair num-ber due to the inter-user interference caused by channel estimation error.For the fixed user-pair number,we deduce the asymptotic performance of SE,which indicates that for ideal and imperfect CSI cases,the transmit power at the senders and the relay can be simultaneously scaled down maximally by 1/N and(?)(N is the number of relay antennas)while the SE can maintain a constant value.Moreover,when the user-pair number increases with the antenna number.it is shown from the asymptotic performance that the user transmit power can be cut down maximally by(?)but the power saving is unavailable at relay.It also means that the number of served user pairs can grow proportionally over the number of relay antennas with arbitrary SE requirement and no extra power cost.All the analytical results are verified through the numerical simulations and the performance comparison between MRT and ZF precoding schemes is also conducted.4.We consider the EE-oriented resource allocation problem in multi-pair massive MIMO relaying systems.Although the transmit power at the users and relay can be scaled down as the number of relay antennas increases,the circuit power consumption of the radio frequency(RF)chains grows by times,which leads to serious influence on the system energy efficiency(EE).Thus,the relay antenna number and the transmit power at the users and the relay are jointly optimized to maximize the EE.When the MRT precoding is exploited at the relay,the quasi-concavity of the cost function w.r.t.each variable is demonstrated by ex-ploring the properties of objective function,and then we obtain two important results,namely,(1)With the antenna number fixed the mathematical relationship between the optimal transmit power at the users and the relay is given;(2)With fixed transmit power vector the closed-form solution of the optimal antenna number is derived.Accordingly,an one-dimensional exhaustive iterative algorithm is proposed,while the convergence rate and the performance are sensitive to initialization point and the value of step length.To improve the convergence speed,we further adopt fractional programming combining with the first results above to propose a more efficient iterative algorithm with superlinear convergence rate.When the ZF pre-coding is employed at the relay,we first transform the original EE function into an equivalent optimization problem in a parametric subtractive by using fractional programming.Then,we explore the partial con-vexity of the cost function w.r.t.the variables and finally,the closed-form solutions are derived by means of the standard convex theory,i.e.,KKT conditions.What's more,the proposed algorithms avoid the com-plicated matrix calculations and the requirement for instantaneous CSI of small-scale fading.Therefore,they are computationally efficient in the practical system.Numerical results verify the effectiveness and superiority of the proposed algorithms,which have fast convergence and achieve near-optimal EE.5.We study the SE performance and power scaling laws for a multiuser distributed massive MIMO system under the mobile scenario with the impact of general time-varying channel.Firstly,the first order Gauss-Markov process is introduced to model the time-varying channel,where temporal correlation coefficient was adopted to characterize time-varying degree.Secondly,using the deterministic equivalent principles and the properties of Gamma random variables,we derive the closed-form expression of the uplink and downlink SE including the temporal correlation coefficient in it,when the MRC detection and the MRT precoding are employed.Furthermore,considering the influences of both pilot contamination and channel time variance,we derive the closed-form expression of SE for a multi-cell distributed massive MIMO system with MRC receiver.Finally,the limiting performances of SE are given when the ratio of the total number of antennas to the number of users goes to infinity,which indicate that(1)In the single-cell scenario,the limiting SE decreases with temporal correlation coefficient without affecting the transmit power gain in comparison to the time-invariant channel.(2)In the multi-cell scenario,the limiting SE has no relation to the temporal correlation coefficient and the power scaling law is the same as that of time-invariant channel.Numerical simulations validate the accuracy of the proposed analytical expression of the SE even for small number of antennas,and show that distributed massive MIMO outperforms the centralized massive MIMO under the channel temporal correlation.
Keywords/Search Tags:Massive multiple-input multiple-output, Frequency division duplex, Precoding, Pilot overhead and design, Spectral efficiency, Energy efficiency, Transmit power, Relay, Distributed massive multipleinput multiple-output, Time-varying channel
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