本文關(guān)鍵詞： 非線性失真 低位寬ADC 大規(guī)模多天線技術(shù) 加性噪聲模型 線性接收機(jī) 廣義互信息　出處：《中國科學(xué)技術(shù)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：近些年移動(dòng)互聯(lián)網(wǎng)用戶數(shù)和移動(dòng)終端數(shù)量正快速增長,移動(dòng)互聯(lián)網(wǎng)用戶對高清視頻等高質(zhì)量的服務(wù)的需求逐漸提高,這給現(xiàn)有的無線通信系統(tǒng)和技術(shù)帶來了巨大的壓力。為了緩解壓力,下一代無線通信系統(tǒng)中使用的頻率帶寬和天線數(shù)量都會(huì)大幅增長,Massive MIMO、毫米波等技術(shù)大幅提高了能量的效率和頻譜的效率,但這給通信系統(tǒng)的硬件設(shè)計(jì)引入了一些新的挑戰(zhàn)。這些挑戰(zhàn)中,有關(guān)于ADC的功率消耗就是一個(gè)急需解決的重要問題。低位寬的,特別是1-bit位寬的ADC徹底改變了通信的理論和應(yīng)用。在本論文中,我們采用廣義互信息來衡量信道輸出端經(jīng)過低位寬量化的Massive MIMO系統(tǒng)的性能。廣義互信息的物理意義是系統(tǒng)在給定了輸入的碼元分布和解碼方式下的速率:如果發(fā)送信號速率低于這個(gè)速率,全體碼本統(tǒng)計(jì)意義上的平均解碼錯(cuò)誤概率隨著碼長趨于無窮變?yōu)?;相反地,如果發(fā)送信號速率高于這個(gè)速率,解碼錯(cuò)誤概率隨著碼長趨于無窮變?yōu)?。基于高斯碼本和最近鄰解碼,我們得出了一個(gè)有關(guān)于通信系統(tǒng)收發(fā)端的失真的等效關(guān)系,這個(gè)等效關(guān)系驗(yàn)證了基于GMI的有效信噪比和基于Bussgang理論推導(dǎo)出的啟發(fā)式的信噪比形式上相等。物理上,量化過程使用ADC來實(shí)現(xiàn),但是ADC的非線性特性給分析帶來了困難。加性量化噪聲模型(AQNM)是一個(gè)廣泛使用的近似描述量化過程的強(qiáng)分析性模型。所以我們采用加性量化噪聲模型來近似分析系統(tǒng)速率,并與實(shí)際量化系統(tǒng)的可達(dá)速率進(jìn)行對比。仿真結(jié)果顯示,基于加性量化噪聲模型的近似速率和量化系統(tǒng)的可達(dá)速率在單用戶場景中差異較大,但是這個(gè)區(qū)別可以通過在加性量化噪聲模型中考慮量化噪聲矢量之間的相關(guān)性最終取得一致性。廣義互信息的一般解析式涉及到接收機(jī),量化輸出矢量的協(xié)方差矩陣,量化輸出矢量和發(fā)送信號的相關(guān)矢量。我們在量化系統(tǒng)中采用一種低復(fù)雜度的接收機(jī),以降低系統(tǒng)開銷。仿真結(jié)果表明這個(gè)低復(fù)雜度的次優(yōu)接收機(jī)帶來的性能增益在BER和系統(tǒng)速率角度均接近最優(yōu)的接收機(jī)。
[Abstract]:In recent years, the number of mobile Internet users and the number of mobile terminals are growing rapidly, and the demand of mobile Internet users for high-quality services such as high-definition video is gradually increasing. This puts tremendous pressure on existing wireless communication systems and technologies. The frequency bandwidth and the number of antennas used in the next generation wireless communication systems will increase greatly, such as massive MIMOs, millimeter-wave and other technologies that greatly improve the energy efficiency and spectral efficiency. But this introduces some new challenges to the hardware design of the communication system. Among these challenges, the power consumption of ADC is an important problem that needs to be solved. In particular, 1-bit bit wide ADC has completely changed the theory and application of communication. We use generalized mutual information to measure the performance of Massive MIMO systems with low bandwidth quantization at the output end of the channel. The physical meaning of generalized mutual information is the rate of the system under the given input symbol distribution and decoding mode: if the transmitter is transmitted. The signal rate is lower than this rate. The average decoding error probability in the statistical sense of all codebooks tends to zero with the code length; conversely, if the transmission signal rate is higher than this rate, Based on Gao Si codebook and nearest neighbor decoding, we obtain an equivalent relation of distortion on the transceiver of communication system. The equivalent relation verifies that the effective SNR based on GMI is equivalent to the heuristic SNR derived from Bussgang theory. Physically, the quantization process is realized by ADC. But the nonlinear characteristics of ADC make it difficult to analyze. The additive quantization noise model is a strong analytical model which is widely used to describe the quantization process. So we use the additive quantization noise model to approximate the system rate. The simulation results show that the approximate rate based on additive quantization noise model and the reachable rate of quantization system differ greatly in single user scenario. But this difference can be achieved by considering the correlation between quantization noise vectors in the additive quantization noise model. The general analytic formula of generalized mutual information relates to the receiver, the covariance matrix of quantization output vector, Quantization output vectors and correlation vectors of transmitted signals. We use a low complexity receiver in the quantization system. The simulation results show that the performance gain of this low-complexity sub-optimal receiver is close to the optimal one in both the BER and system rate angles.
【學(xué)位授予單位】：中國科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN92

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