本文選題：無(wú)線(xiàn)通信　切入點(diǎn)：信噪比估計(jì)　出處：《電子科技大學(xué)》2014年碩士論文

【摘要】：信噪比是無(wú)線(xiàn)通信信道環(huán)境和通信質(zhì)量的有效評(píng)估指標(biāo),并可作為指導(dǎo)編解碼以及數(shù)字解調(diào)算法選擇和優(yōu)化的重要依據(jù)。在衡量信道質(zhì)量的參數(shù)中,信噪比實(shí)時(shí)測(cè)量性好,并且與信道的誤碼率、誤幀率直接相關(guān)。本文首先基于高斯信道研究了最大似然估計(jì)、二階四階矩估計(jì)、高階累積量估計(jì)以及最小均方誤差估計(jì)信噪比估計(jì)算法在不同頻偏、數(shù)據(jù)長(zhǎng)度、采樣倍數(shù)以及有無(wú)定時(shí)的情況下的估計(jì)性能,并分析總結(jié)出影響算法性能的影響因子。仿真時(shí)最大似然估計(jì)可以工作于多倍采樣的情況下,在有頻偏時(shí)性能下降;二階四階矩和高階累積量估計(jì)法在信號(hào)定時(shí)理想的情況下具有良好的估計(jì)性能,增大數(shù)據(jù)量可以提高算法估計(jì)性能的穩(wěn)定性;最小均方誤差法在理想高斯白噪聲下對(duì)理想定時(shí)后的信號(hào)才具有良好的估計(jì)性能,并且以上信噪比估計(jì)算法主要針對(duì)PSK調(diào)制信號(hào)具有較好的估計(jì)性能。針對(duì)以上分析結(jié)果,本文提出了基于信號(hào)頻譜自身歸一化的改進(jìn)頻偏估計(jì)算法,信號(hào)帶寬、符號(hào)率估計(jì)算法以及信噪比估計(jì)算法。改進(jìn)的頻偏估計(jì)、信號(hào)帶寬、符號(hào)率估計(jì)算法能很好的消除頻偏、采樣倍數(shù)對(duì)信噪比估計(jì)性能的影響,改進(jìn)的信噪比估計(jì)算法適用于QAM和PSK調(diào)制,估計(jì)性能幾乎不受頻偏和采樣倍數(shù)的影響,能很好的估計(jì)1-30d B范圍的信噪比值。然后,基于DSP平臺(tái)在不同實(shí)現(xiàn)條件下進(jìn)行了以上算法的全數(shù)字實(shí)現(xiàn)。最大似然估計(jì)實(shí)際實(shí)現(xiàn)的過(guò)程中由于噪聲的非完全高斯性,估計(jì)性能較差;二階四階矩和高階累積量估計(jì)法在在信號(hào)定時(shí)恢復(fù)后能較好的估計(jì)信噪比值;最小均方誤差法實(shí)際實(shí)現(xiàn)時(shí)性能不佳;改進(jìn)的信噪比估計(jì)算法實(shí)現(xiàn)時(shí)具有良好的估計(jì)性能。改進(jìn)的頻偏估計(jì)算法,信號(hào)帶寬、符號(hào)率估計(jì)算法能很好的估計(jì)發(fā)送端調(diào)制信號(hào)的頻偏、帶寬及符號(hào)率。最后,將信噪比估計(jì)算法應(yīng)用于64QAM的自適應(yīng)選擇載波恢復(fù)算法中,使得解調(diào)性能得到了優(yōu)化,穩(wěn)定性提高,解調(diào)星座點(diǎn)更集中。
[Abstract]:Signal-to-noise ratio (SNR) is an effective evaluation index for wireless communication channel environment and communication quality, and can be used as an important basis for the selection and optimization of codec and digital demodulation algorithms.Among the parameters used to measure the channel quality, the SNR can be measured in real time, and it is directly related to the bit error rate (BER) and frame error rate (FER) of the channel.In this paper, the maximum likelihood estimation, the second order fourth moment estimation, the high order cumulant estimation and the minimum mean square error estimation SNR estimation algorithm are studied based on Gao Si channel at different frequency offset and data length.The performance of the algorithm is estimated by sampling multiple and with or without timing, and the factors that affect the performance of the algorithm are analyzed and summarized.In simulation, the maximum likelihood estimation can work in the case of multiple sampling, and the performance of the second order fourth moment and high order cumulant estimation method can be reduced when the frequency offset is high, and the second order fourth moment and the high order cumulant estimation method have good estimation performance in the case of ideal signal timing.Increasing the amount of data can improve the stability of the estimation performance of the algorithm, and the minimum mean square error method has good estimation performance for the signal after ideal timing under ideal Gao Si white noise.And the above SNR estimation algorithms have better estimation performance for PSK modulation signals.Based on the above analysis results, an improved frequency offset estimation algorithm, a signal bandwidth estimation algorithm, a symbol rate estimation algorithm and a signal-to-noise ratio estimation algorithm are proposed based on the normalization of the signal spectrum itself.The improved frequency offset estimation, signal bandwidth and symbol rate estimation algorithm can eliminate the frequency offset and the influence of sampling multiple on the SNR estimation performance. The improved SNR estimation algorithm is suitable for QAM and PSK modulation.The estimation performance is almost independent of the frequency offset and sampling multiple, and can estimate the SNR in the range of 1-30 dB.Then, the full digital implementation of the above algorithm is carried out based on the DSP platform under different implementation conditions.In the process of maximum likelihood estimation, the estimation performance is poor due to the incomplete Gao Si of noise, and the second order fourth moment and high order cumulant estimation method can estimate the signal-to-noise ratio better after the signal timing recovery.The minimum mean square error method has poor performance in practice and the improved SNR estimation algorithm has good estimation performance.The improved frequency offset estimation algorithm, signal bandwidth, symbol rate estimation algorithm can well estimate the frequency offset, bandwidth and symbol rate of the modulation signal at the transmitter.Finally, the SNR estimation algorithm is applied to the adaptive selective carrier recovery algorithm of 64QAM. The demodulation performance is optimized, the stability is improved, and the demodulation constellation is more concentrated.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN92

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 陳大夫;張爾揚(yáng);朱江;;快速傅里葉變換載波頻偏估計(jì)算法[J];電路與系統(tǒng)學(xué)報(bào);2006年02期

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本文編號(hào)：1701270