本文關(guān)鍵詞：MIMO無線通信自適應(yīng)傳輸理論方法研究　出處：《東南大學(xué)》2016年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 多天線系統(tǒng) 迭代接收機(jī)性能建模 自適應(yīng)傳輸 大規(guī)模MIMO傳輸 可達(dá)和速率 導(dǎo)頻最優(yōu)長度 功率分配

【摘要】：多天線發(fā)送和多天線接收(MIMO, Multiple-Input Multiple-Output)無線傳輸技術(shù)能夠提升無線通信的系統(tǒng)容量、頻譜效率、功率效率及傳輸可靠性,在過去的近二十年得到了廣泛的研究與應(yīng)用,成為寬帶移動(dòng)通信系統(tǒng)的核心技術(shù)。未來移動(dòng)通信系統(tǒng)對(duì)系統(tǒng)容量、頻譜效率、功率效率及傳輸可靠性都提出了更高的要求,需要采用大規(guī)模天線的MIMO無線傳輸技術(shù)。在此背景下,本論文開展MIMO無線通信系統(tǒng)自適應(yīng)傳輸理論方法研究,著重研究與迭代接收相適應(yīng)的自適應(yīng)MIMO傳輸理論方法和大規(guī)模MIMO系統(tǒng)導(dǎo)頻和功率配置的自適應(yīng)理論方法。首先,研究了MIMO系統(tǒng)迭代接收機(jī)的性能建模方法。迭代接收技術(shù)是獲得逼近信道容量的接收技術(shù),其性能建模是實(shí)現(xiàn)迭代接收情況下鏈路自適應(yīng)的基礎(chǔ),為此,從等效模型、傳遞參數(shù)、性能提取及傳遞關(guān)系等四個(gè)方面著手,提出了MIMO系統(tǒng)迭代接收性能建模方法。該方法以服從高斯分布的對(duì)數(shù)似然比信息等效模型為基礎(chǔ),以互信息為傳遞參數(shù)并通過仿真獲得互信息傳遞關(guān)系圖,并利用誤比特率或保真度為傳遞參數(shù)的半公式化傳遞關(guān)系及以互信息為傳遞參數(shù)的半公式化傳遞關(guān)系,實(shí)現(xiàn)MIMO迭代接收的性能建模。進(jìn)而,提出了迭代接收機(jī)各軟輸入軟輸出單元的性能預(yù)測方法。仿真結(jié)果證實(shí)所提方法的有效性。然后,針對(duì)MIMO傳輸鏈路,研究了迭代接收情況下的高效鏈路自適應(yīng)方法。推導(dǎo)了迭代接收后驗(yàn)信干比以及等效信噪比,提出了迭代接收情況下MIMO鏈路自適應(yīng)方法。該方法利用經(jīng)典鏈路自適應(yīng)方法確定秩指示和信道質(zhì)量指示的取值范圍,僅在秩指示和信道質(zhì)量指示的取值范圍內(nèi)確定反饋參數(shù),減少了后驗(yàn)信干比及等效信噪比的計(jì)算次數(shù),從而降低了在線吞吐量預(yù)測的計(jì)算量。仿真結(jié)果表明：所提鏈路自適應(yīng)方法的吞吐量優(yōu)于經(jīng)典鏈路自適應(yīng)方法,滿足鏈路服務(wù)質(zhì)量要求,并且獲得了3.5dB吞吐量增益。接著,研究了角度域信道模型下大規(guī)模MIMO系統(tǒng)上行傳輸最小均方誤差(MMSE)接收機(jī)的可達(dá)和速率。可達(dá)速率分析是實(shí)現(xiàn)導(dǎo)頻和功率等自適應(yīng)優(yōu)化配置的基礎(chǔ),本論文將MMSE檢測器輸出端后驗(yàn)信干比分解為兩個(gè)獨(dú)立隨機(jī)變量之求和,通過引入卡方變量二次型的分布、隨機(jī)矩陣的經(jīng)驗(yàn)特征值分布等理論,得到了這兩個(gè)獨(dú)立隨機(jī)變量的矩統(tǒng)計(jì)量及概率分布、以及后驗(yàn)信干比的矩統(tǒng)計(jì)量。由兩個(gè)獨(dú)立隨機(jī)變量的概率分布,提出了后驗(yàn)信干比的一種歸一化形式,證明了后驗(yàn)信干比服從伽瑪分布,并由所得后驗(yàn)信干比矩統(tǒng)計(jì)量得到伽瑪分布函數(shù)的參數(shù)。進(jìn)而,利用后驗(yàn)信干比的分布函數(shù),得到了MMSE接收機(jī)后驗(yàn)信干比下界以及可達(dá)和速率的近似式。仿真結(jié)果證實(shí)了理論結(jié)果的準(zhǔn)確性。最后,研究了大規(guī)模MIMO系統(tǒng)上行導(dǎo)頻輔助傳輸方式下導(dǎo)頻和功率自適應(yīng)優(yōu)化配置方法。在可達(dá)和速率分析的基礎(chǔ)上,進(jìn)一步從理論上得到導(dǎo)頻輔助傳輸方式下線性MMSE接收機(jī)可達(dá)和速率,進(jìn)而得到其在基站天線單元數(shù)量大且用戶數(shù)目固定的情形下無需迭代數(shù)值運(yùn)算的近似式。針對(duì)導(dǎo)頻長度及功率聯(lián)合自適應(yīng)優(yōu)化配置,分別證明了固定導(dǎo)頻長度下可達(dá)和速率是功率的凹函數(shù),固定導(dǎo)頻功率下可達(dá)和速率是導(dǎo)頻長度的凹函數(shù),進(jìn)而提出針對(duì)聯(lián)合自適應(yīng)優(yōu)化配置問題的交替優(yōu)化算法,計(jì)算復(fù)雜度低。此外,研究了等功率分配傳輸情形下導(dǎo)頻最優(yōu)長度。證明了在中等及高信噪比條件下導(dǎo)頻長度接近單天線用戶數(shù),在低信噪比條件下導(dǎo)頻長度接近信道相干時(shí)間間隔數(shù)的一半。仿真結(jié)果證實(shí)了可達(dá)和速率近似式的準(zhǔn)確性及聯(lián)合優(yōu)化算法的有效性。
[Abstract]:The multi antenna transmit and multiple receive antennas (MIMO, Multiple-Input, Multiple-Output) wireless transmission technology can improve system capacity of wireless communications, spectrum efficiency, power efficiency and reliability, in the past twenty years has been extensive research and application, become the core technology of broadband mobile communication system. The spectral efficiency of future mobile communication system of system capacity, power, efficiency and reliability are put forward higher requirements to the MIMO wireless transmission technology using large scale antenna. Under this background, the theory research on adaptive transmission method of MIMO wireless communication system in this thesis, the theory focuses on the research and method of adaptive iterative receiver adaptive MIMO transmission theory and method to adapt and large-scale MIMO pilot system and power allocation. Firstly, the performance modeling method of MIMO system is studied. The iterative receiver Iterative Receiver Technology Is to get close to the channel capacity receiving technology, its performance is the basis of link adaptive modeling, realize the iterative receiver case to pass parameters from the equivalent model, the performance of extraction and transfer between the four aspects, proposed the iterative receiver modeling method of MIMO system performance. This method is to obey the Gauss distribution of the log likelihood ratio information the equivalent model based on mutual information and mutual information transmission parameters transfer diagram by simulation, and the bit error rate or fidelity as the half formula transfer parameters transfer relationship and mutual information formula semi transfer parameters transfer relationship, achieve the performance modeling of MIMO iterative receiver. Then, put forward the performance the soft input soft output iterative receiver unit prediction method. Simulation results confirm the effectiveness of the proposed method. Then, according to the MIMO transmission link, the iterative receiver Efficient link adaptation methods. Deduced the iterative receiver posteriori SNR and equivalent SNR, forward link adaptive method MIMO iterative receiver case. This method uses the classical method to determine the range of link adaptive rank indication and channel quality indication, only to determine the feedback parameters in the range rank indication and channel quality indicator in a letter to calculate ratio and equivalent signal-to-noise ratio of the number of test is reduced, thereby reducing the amount of online computation throughput prediction. The simulation results show that the throughput is better than the classical link adaptive method proposed link adaptive method, link to meet quality of service requirements, and obtained the 3.5dB throughput gain. Then, the research angle domain channel model of large-scale MIMO system uplink transmission minimum mean square error (MMSE) receiver is achievable rate and rate. Analysis is the implementation of pilot and power Adaptive optimization based, the SNR is decomposed into two independent random variables summation test MMSE detector output, by introducing a distribution chi square variable two type, experience the value distribution characteristics of random matrix theory, the moments and the probability distribution of the two independent random variables the signal ratio testing and the moments. By probability distribution of two independent random variables, proposes a posteriori signal-to-noise ratio of the normalized form, it proves that the posterior SNR obeys the gamma distribution, and by the posterior signal obtained parameter of gamma distribution function than the moment statistics. Then, the distribution function of the ratio of signal to interference test using, SNR bounds and approximations and the rate of inspection has been up to MMSE receiver. The simulation results confirm the accuracy of the theoretical results. Finally, the research on the large scale MIMO system uplink pilot aided The frequency allocation method and adaptive power optimization guide transmission mode. Based on the analysis of reachability and rate, further pilot assisted transmission under linear MMSE receiver and rate up to theoretically, and then get the number of base station antenna elements and the number of users under the condition of no fixed approximation requires an iterative numerical calculation. According to the pilot length and power joint adaptive optimization, it is shown that the fixed length of pilot and the rate is a concave function of power, fixed pilot power can reach and rate is a concave function of pilot length, then put forward alternating optimization algorithm which combines adaptive optimization and low computational complexity. In addition, study on the transmission power allocation under the condition of optimal pilot length. It is proved that in the medium and high SNR pilot single antenna length is close to the number of users, in the low SNR. The lower pilot length is close to half of the coherent time interval of the channel. The simulation results confirm the accuracy of the approximation of the reachable and rate and the effectiveness of the combined optimization algorithm.

【學(xué)位授予單位】：東南大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TN919.3

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