OFDM系统的资源分配与有限反馈研究
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摘要
OFDM技术是下一代无线通信系统中最重要的候选技术之一,它能有效对抗频率选择性衰落,具有很强的链路可靠性。OFDM相关系统的自适应资源调度和分配有效地利用了时间、频率、空间等资源,进一步提高系统性能,已经得到了广泛的研究。但是,基站端进行资源分配时,都需要知道用户端每个子载波上的信道信息。对于FDD系统,下行链路信道信息必须通过专门的反馈信道,由用户估计后反馈给基站。当用户、子载波以及天线数目较大的时候,多用户OFDM系统的反馈信息量是非常大的,这就需要有限反馈技术在保证系统性能的前提下降低用户信道信息占用的反馈带宽。
本文考虑OFDM及其相关系统中的有限反馈问题,针对OFDM系统、MIMO-OFDM系统、以及非理想反馈的情况,提出若干降低系统反馈开销的算法。
文中分析了OFDM系统的信道模型特征和有限反馈算法的基础根源：信道的频域和时域相关性能,并对数字系统反馈不可避免的量化问题进行了简单介绍。在对瑞利信道、莱斯信道和Nakagami信道的分布函数进行分析后,提出了一种基于信道概率分布的CQI量化算法,在优化目标为CQI的MMSE值和系统BER的情况下,分别推导了概率量化的公式,通过迭代计算求解了优化的量化门限,提升了系统BER性能。并对这种概率量化算法的目标函数和其概率分布函数的几种实际情况进行了分析,指出了本文这种次优量化算法的使用环境和拓展的方向。压缩算法是一种广为研究的算法,近年来在无线通信系统的反馈中也得到了应用。在对现有的3种无损压缩算法和2种有损压缩算法及其在OFDM系统反馈压缩中的使用进行介绍后,文中提出了一种基于排序的DCT反馈压缩算法,利用排序算法增大了频率选择性信道的反馈CQI之间的相关性,计算分析了该算法合适的作用数据块大小,降低了系统的反馈开销。
在多天线环境下,本文分析了多用户MIMO-OFDM系统中天线间相关性以及天线间无相关性时MIMO矩阵特征值的分布情况。针对多用户MIMO-OFDM系统中反馈信息量大的问题,通过分析信道反馈矩阵的天线间相关性和子载波间相关性系数,并结合小波变换的特点,提出了自适应DWT-CQI压缩算法,它相对于二维DWT-CQI压缩算法、基于天线间相关性的一维DWT-CQI压缩算法和基于子载波间相关性的一维DWT-CQI压缩算法,在不同相关性条件下反馈开销最小。仿真结果表明,在V-BLAST+OFDM系统下,DWT-CQI压缩算法在相同的压缩率下BER性能优于DCT-CQI压缩算法,并且在降低大量的反馈信令开销的情况下系统BER下降较小,仍能有效地利用多用户分集增益,有效地实现了系统性能和反馈信令开销之间的折中。通过对多用户MIMO-OFDM系统的MIMO反馈特征值分布特性的分析和特征值期望的推导,文中设计了一种对CQI反馈压缩信息进行数据预处理的改进压缩算法。该算法增大了待压缩数据的相关性,提高了反馈压缩效果。仿真表明在多用户V-BLAST+OFDM系统下,DWT和DCT压缩方案使用基于数据预处理的算法都能明显提高反馈信息的压缩率和系统的吞吐量性能,大大地节省了反馈开销。
本文在最后一部分选取了4种影响信道信息的主要因素：接收端的信道估计误差、量化误差、反馈回路的时延和传输误差,讨论了在基站端使用Max-SNR子载波调度算法的情况下,这些非理想因素对基站端使用的SNR及系统整体BER性能的影响。并介绍了现有的对抗信道非理想因素的算法主要是信道预测算法的应用。
有限反馈算法能有效地节省系统的反馈信令开销,以增大上行数据传输带宽或者反馈更多的信令信息。本文所作的研究和贡献,对实际OFDM系统中的有限反馈问题具有一定参考意义,提出的部分有限反馈算法,也具有一定的实用价值。
OFDM is one of the most important candidates in the next generation wireless communication systems. It can effectively combat the frequency selective fading and provide good link reliability. In OFDM related systems the adaptive resource allocation which efficiently utilizes time, frequency and space, improves the system performance has been studied widely. But the base station needs to know the channel information of every subcarrier on the user side before it starts the resource allocation. To FDD systems, downlink channel information need to be estimated by users and fed back to the base station through dedicated feedback channel. When the user number, subcarrier number and the antenna number are big, the feedback information is numerous. So limited feedback is proposed to reduce the feedback information while guarantee the system performance.
Limited feedback problems for OFDM related systems are studied in this thesis, and a lot of algorithms are proposed to reduce system feedback overhead for OFDM and MIMO-OFDM systems.
We analyze the characteristics of OFDM channel model and the foundation of limited feedback algorithms:the frequency and time correlations of the channel. We also introduce the quantification problem which is unavoidable in digital systems. After analyzing the PDFs of Rayleigh channel, Rice channel and Nakagami channel, we propose a CQI quantification algorithm based on the channel PDF. When the optimization targets are the MMSE of the CQI and the system BER, we respectively derive the quantification formula, get the target threholds through iterative computation, and improve the system performance. Furthermore, we analyze the optimization targets and PDF functions of these quantification algorithms in many practical cases, and point out the usable cases of the algorithms and their directions to be further extended. Compression algorithms have been widely studied by now, and they have also been used in the feedback of wireless communication systems. We introduce a few popular lossless and lossy compression algorithms and their applications in the feedback compression of OFDM systems. A DCT feedback compression algorithm based on sorting is proposed. After the appropriate data block size of it is computed, the proposed algorithm improves the correlation of the feedback CQI in frequency selective channel and reduces the system feedback overhead.
In multi-antenna cases, we analyze the correlation among antennas. When there isn't antenna correlation, we analyze the distribution of MIMO matrix eigenvalues. To reduce the CQI feedback information in multiuser MIMO-OFDM systems, an adaptive scheme is proposed according to the correlation among antennas and that of subcarriers in the feedback information, and characteristics of the wavelet transform. Comparing to the two-dimensional DWT-CQI compression algorithm and other two one-dimensional DWT compression algorithms respectively based on antenna correlation and subcarrier correlation, our algorithm has the least feedback overhead. Simulation results show that our compression algorithm greatly reduces the feedback signaling with little BER performance degradation in a V-BLAST+OFDM system, and it can deal with the tradeoff between system performance and feedback overhead well. After analyzing the eigenvalues of the CQI in multiuser MIMO-OFDM systems and deriving their expectations, an improved CQI feedback compression algorithm is proposed which pretreats the feedback information before it is compressed and fed back. This algorithm improves the correlation between the information to be compressed and has good performance. Simulation results show that the proposed algorithm improves the compression ratio of the feedback information and the system throughput performance in a multiuser V-BLAST+OFDM system. It can be effectively used both in DWT and DCT compression algorithms.
At last we introduce four kinds of factors which affect the channel performance:channel estimation error, quantification error, delay in the feedback link and the feedback transmission error. We discuss the influence of unperfect channel to the assumed SNR in the base station and the system BER when Max-SNR subcarrier scheduling algorithm is used in the base station.
Limited feedback algorithms can effectively save the system feedback overhead, which can be used to transmit more uplink data or more feedback information. The research results and contributions in this thesis can be references for limited feedback in OFDM systems. Some of the proposed limited feedback algorithms are also very meaningful for practice.
本文考虑OFDM及其相关系统中的有限反馈问题,针对OFDM系统、MIMO-OFDM系统、以及非理想反馈的情况,提出若干降低系统反馈开销的算法。
文中分析了OFDM系统的信道模型特征和有限反馈算法的基础根源：信道的频域和时域相关性能,并对数字系统反馈不可避免的量化问题进行了简单介绍。在对瑞利信道、莱斯信道和Nakagami信道的分布函数进行分析后,提出了一种基于信道概率分布的CQI量化算法,在优化目标为CQI的MMSE值和系统BER的情况下,分别推导了概率量化的公式,通过迭代计算求解了优化的量化门限,提升了系统BER性能。并对这种概率量化算法的目标函数和其概率分布函数的几种实际情况进行了分析,指出了本文这种次优量化算法的使用环境和拓展的方向。压缩算法是一种广为研究的算法,近年来在无线通信系统的反馈中也得到了应用。在对现有的3种无损压缩算法和2种有损压缩算法及其在OFDM系统反馈压缩中的使用进行介绍后,文中提出了一种基于排序的DCT反馈压缩算法,利用排序算法增大了频率选择性信道的反馈CQI之间的相关性,计算分析了该算法合适的作用数据块大小,降低了系统的反馈开销。
在多天线环境下,本文分析了多用户MIMO-OFDM系统中天线间相关性以及天线间无相关性时MIMO矩阵特征值的分布情况。针对多用户MIMO-OFDM系统中反馈信息量大的问题,通过分析信道反馈矩阵的天线间相关性和子载波间相关性系数,并结合小波变换的特点,提出了自适应DWT-CQI压缩算法,它相对于二维DWT-CQI压缩算法、基于天线间相关性的一维DWT-CQI压缩算法和基于子载波间相关性的一维DWT-CQI压缩算法,在不同相关性条件下反馈开销最小。仿真结果表明,在V-BLAST+OFDM系统下,DWT-CQI压缩算法在相同的压缩率下BER性能优于DCT-CQI压缩算法,并且在降低大量的反馈信令开销的情况下系统BER下降较小,仍能有效地利用多用户分集增益,有效地实现了系统性能和反馈信令开销之间的折中。通过对多用户MIMO-OFDM系统的MIMO反馈特征值分布特性的分析和特征值期望的推导,文中设计了一种对CQI反馈压缩信息进行数据预处理的改进压缩算法。该算法增大了待压缩数据的相关性,提高了反馈压缩效果。仿真表明在多用户V-BLAST+OFDM系统下,DWT和DCT压缩方案使用基于数据预处理的算法都能明显提高反馈信息的压缩率和系统的吞吐量性能,大大地节省了反馈开销。
本文在最后一部分选取了4种影响信道信息的主要因素：接收端的信道估计误差、量化误差、反馈回路的时延和传输误差,讨论了在基站端使用Max-SNR子载波调度算法的情况下,这些非理想因素对基站端使用的SNR及系统整体BER性能的影响。并介绍了现有的对抗信道非理想因素的算法主要是信道预测算法的应用。
有限反馈算法能有效地节省系统的反馈信令开销,以增大上行数据传输带宽或者反馈更多的信令信息。本文所作的研究和贡献,对实际OFDM系统中的有限反馈问题具有一定参考意义,提出的部分有限反馈算法,也具有一定的实用价值。
OFDM is one of the most important candidates in the next generation wireless communication systems. It can effectively combat the frequency selective fading and provide good link reliability. In OFDM related systems the adaptive resource allocation which efficiently utilizes time, frequency and space, improves the system performance has been studied widely. But the base station needs to know the channel information of every subcarrier on the user side before it starts the resource allocation. To FDD systems, downlink channel information need to be estimated by users and fed back to the base station through dedicated feedback channel. When the user number, subcarrier number and the antenna number are big, the feedback information is numerous. So limited feedback is proposed to reduce the feedback information while guarantee the system performance.
Limited feedback problems for OFDM related systems are studied in this thesis, and a lot of algorithms are proposed to reduce system feedback overhead for OFDM and MIMO-OFDM systems.
We analyze the characteristics of OFDM channel model and the foundation of limited feedback algorithms:the frequency and time correlations of the channel. We also introduce the quantification problem which is unavoidable in digital systems. After analyzing the PDFs of Rayleigh channel, Rice channel and Nakagami channel, we propose a CQI quantification algorithm based on the channel PDF. When the optimization targets are the MMSE of the CQI and the system BER, we respectively derive the quantification formula, get the target threholds through iterative computation, and improve the system performance. Furthermore, we analyze the optimization targets and PDF functions of these quantification algorithms in many practical cases, and point out the usable cases of the algorithms and their directions to be further extended. Compression algorithms have been widely studied by now, and they have also been used in the feedback of wireless communication systems. We introduce a few popular lossless and lossy compression algorithms and their applications in the feedback compression of OFDM systems. A DCT feedback compression algorithm based on sorting is proposed. After the appropriate data block size of it is computed, the proposed algorithm improves the correlation of the feedback CQI in frequency selective channel and reduces the system feedback overhead.
In multi-antenna cases, we analyze the correlation among antennas. When there isn't antenna correlation, we analyze the distribution of MIMO matrix eigenvalues. To reduce the CQI feedback information in multiuser MIMO-OFDM systems, an adaptive scheme is proposed according to the correlation among antennas and that of subcarriers in the feedback information, and characteristics of the wavelet transform. Comparing to the two-dimensional DWT-CQI compression algorithm and other two one-dimensional DWT compression algorithms respectively based on antenna correlation and subcarrier correlation, our algorithm has the least feedback overhead. Simulation results show that our compression algorithm greatly reduces the feedback signaling with little BER performance degradation in a V-BLAST+OFDM system, and it can deal with the tradeoff between system performance and feedback overhead well. After analyzing the eigenvalues of the CQI in multiuser MIMO-OFDM systems and deriving their expectations, an improved CQI feedback compression algorithm is proposed which pretreats the feedback information before it is compressed and fed back. This algorithm improves the correlation between the information to be compressed and has good performance. Simulation results show that the proposed algorithm improves the compression ratio of the feedback information and the system throughput performance in a multiuser V-BLAST+OFDM system. It can be effectively used both in DWT and DCT compression algorithms.
At last we introduce four kinds of factors which affect the channel performance:channel estimation error, quantification error, delay in the feedback link and the feedback transmission error. We discuss the influence of unperfect channel to the assumed SNR in the base station and the system BER when Max-SNR subcarrier scheduling algorithm is used in the base station.
Limited feedback algorithms can effectively save the system feedback overhead, which can be used to transmit more uplink data or more feedback information. The research results and contributions in this thesis can be references for limited feedback in OFDM systems. Some of the proposed limited feedback algorithms are also very meaningful for practice.
引文
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