異構(gòu)網(wǎng)絡(luò)干擾信道估計(jì)研究
發(fā)布時(shí)間:2019-06-25 09:30
【摘要】:城市化發(fā)展帶來的整體環(huán)境的改變,使得無線信號(hào)的傳播信道愈加惡劣,與此同時(shí),室內(nèi)數(shù)據(jù)、語音等業(yè)務(wù)需求不斷增大,這使得高質(zhì)量的室內(nèi)覆蓋變得十分迫切。家庭基站作為一種室內(nèi)覆蓋技術(shù),有效提升了整體網(wǎng)絡(luò)的容量,不僅發(fā)射功率低,而且部署方便。家庭基站和宏基站構(gòu)成了雙層異構(gòu)網(wǎng)絡(luò),二者使用相同的頻譜資源,相較于傳統(tǒng)網(wǎng)絡(luò),異構(gòu)網(wǎng)絡(luò)的結(jié)構(gòu)復(fù)雜,干擾也更加嚴(yán)重。異構(gòu)網(wǎng)絡(luò)中得到干擾信道信息后,可以進(jìn)行干擾消除。協(xié)作網(wǎng)絡(luò)中利用導(dǎo)頻信息通過LS、MMSE算法進(jìn)行干擾信道估計(jì),但在非協(xié)作網(wǎng)絡(luò)中,當(dāng)期望信道的數(shù)據(jù)信息和干擾信道的導(dǎo)頻信息重疊時(shí),利用LS、MMSE算法得到的干擾信道估計(jì)性能較差。本文基于無線寬帶信道的稀疏性質(zhì),在非協(xié)作異構(gòu)網(wǎng)絡(luò)的干擾信道估計(jì)中,提出一種基于壓縮感知的迭代方法,通過迭代估計(jì)得到干擾信道信息和期望數(shù)據(jù)信息。文中建立了雙層異構(gòu)網(wǎng)絡(luò)的下行鏈路系統(tǒng)仿真模型,對(duì)比采用壓縮感知和采用LS的干擾信道估計(jì)性能。仿真結(jié)果表明,利用壓縮感知技術(shù)可準(zhǔn)確估計(jì)異構(gòu)網(wǎng)絡(luò)中的干擾信道,路徑數(shù)量發(fā)生變化時(shí),估計(jì)的性能受到部分影響,當(dāng)SNR高于19dB時(shí),基于壓縮感知的干擾信道估計(jì)性能明顯優(yōu)于LS算法。本文在異構(gòu)網(wǎng)絡(luò)中基于壓縮感知對(duì)干擾信道估計(jì)性能進(jìn)行優(yōu)化,提出了兩種優(yōu)化方法:(1)通過構(gòu)造確定性稀疏二值觀測(cè)矩陣,獲得相應(yīng)的感知矩陣,基于OMP優(yōu)化恢復(fù)算法;(2)給定稀疏基,通過求解最小Frobenius范數(shù),使觀測(cè)矩陣具有較小的互相關(guān)值,優(yōu)化觀測(cè)矩陣。仿真結(jié)果表明,利用優(yōu)化算法能夠有效降低干擾信道估計(jì)的均方誤差0.5-2dB。
[Abstract]:With the change of the overall environment brought by the development of urbanization, the propagation channel of wireless signal is becoming worse and worse. at the same time, the demand for indoor data, voice and other services is increasing, which makes high-quality indoor coverage very urgent. As an indoor coverage technology, home base station effectively improves the capacity of the whole network, which not only has low transmission power, but also is convenient to deploy. Home base station and macro base station constitute double-layer heterogeneous network, which use the same spectrum resources. Compared with the traditional network, the structure of heterogeneous network is more complex and the interference is more serious. Interference cancellation can be carried out after interference channel information is obtained in heterogeneous networks. In cooperative networks, pilot information is used to estimate interference channels by LS,MMSE algorithm, but in non-cooperative networks, when the data information of expected channels and pilot information of interference channels overlap, the performance of interference channel estimation obtained by LS,MMSE algorithm is poor. In this paper, based on the sparse nature of wireless broadband channel, an iterative method based on compressed sensing is proposed in the interference channel estimation of non-cooperative heterogeneous networks, and the interference channel information and expected data information are obtained by iterative estimation. In this paper, a downlink system simulation model for double-layer heterogeneous networks is established, and the interference channel estimation performance using compressed sensing and LS is compared. The simulation results show that the interference channel in heterogeneous networks can be accurately estimated by using compressed sensing technology. When the number of paths changes, the performance of the estimation is partly affected. When the SNR is higher than 19dB, the performance of interference channel estimation based on compression sensing is obviously better than that of LS algorithm. In this paper, the performance of interference channel estimation is optimized based on compressed sensing in heterogeneous networks, and two optimization methods are proposed: (1) the corresponding perception matrix is obtained by constructing deterministic sparse binary observation matrix, and the corresponding perceptual matrix is optimized based on OMP; (2) given sparse basis, the observation matrix has a small cross-correlation value and optimizes the observation matrix by solving the minimum Frobenius norm. The simulation results show that the mean square error of interference channel estimation can be effectively reduced by using the optimization algorithm.
【學(xué)位授予單位】:南京郵電大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TN929.5
本文編號(hào):2505581
[Abstract]:With the change of the overall environment brought by the development of urbanization, the propagation channel of wireless signal is becoming worse and worse. at the same time, the demand for indoor data, voice and other services is increasing, which makes high-quality indoor coverage very urgent. As an indoor coverage technology, home base station effectively improves the capacity of the whole network, which not only has low transmission power, but also is convenient to deploy. Home base station and macro base station constitute double-layer heterogeneous network, which use the same spectrum resources. Compared with the traditional network, the structure of heterogeneous network is more complex and the interference is more serious. Interference cancellation can be carried out after interference channel information is obtained in heterogeneous networks. In cooperative networks, pilot information is used to estimate interference channels by LS,MMSE algorithm, but in non-cooperative networks, when the data information of expected channels and pilot information of interference channels overlap, the performance of interference channel estimation obtained by LS,MMSE algorithm is poor. In this paper, based on the sparse nature of wireless broadband channel, an iterative method based on compressed sensing is proposed in the interference channel estimation of non-cooperative heterogeneous networks, and the interference channel information and expected data information are obtained by iterative estimation. In this paper, a downlink system simulation model for double-layer heterogeneous networks is established, and the interference channel estimation performance using compressed sensing and LS is compared. The simulation results show that the interference channel in heterogeneous networks can be accurately estimated by using compressed sensing technology. When the number of paths changes, the performance of the estimation is partly affected. When the SNR is higher than 19dB, the performance of interference channel estimation based on compression sensing is obviously better than that of LS algorithm. In this paper, the performance of interference channel estimation is optimized based on compressed sensing in heterogeneous networks, and two optimization methods are proposed: (1) the corresponding perception matrix is obtained by constructing deterministic sparse binary observation matrix, and the corresponding perceptual matrix is optimized based on OMP; (2) given sparse basis, the observation matrix has a small cross-correlation value and optimizes the observation matrix by solving the minimum Frobenius norm. The simulation results show that the mean square error of interference channel estimation can be effectively reduced by using the optimization algorithm.
【學(xué)位授予單位】:南京郵電大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TN929.5
【參考文獻(xiàn)】
相關(guān)期刊論文 前2條
1 田香玲;席志紅;;壓縮感知觀測(cè)矩陣的優(yōu)化算法[J];電子科技;2015年08期
2 石光明;劉丹華;高大化;劉哲;林杰;王良君;;壓縮感知理論及其研究進(jìn)展[J];電子學(xué)報(bào);2009年05期
,本文編號(hào):2505581
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