分布式MIMO-OFDM的功率分配与自适应调制技术

【作者】 张帆；

【导师】 唐友喜；

【作者基本信息】 电子科技大学 ， 通信与信息系统， 2007， 硕士

【摘要】 下一代移动通信要求大容量和高质量的数据传输,因此多输入多输出系统中的正交频分复用技术受到学术界及产业界的关注。现有的集中式MIMO-OFDM系统的多根收、发天线均分别集中于一处,而分布式MIMO-OFDM系统的多根收、发天线均分别分布于不同的地理位置。与集中式MIMO-OFDM相比,分布式MIMO-OFDM系统的各对收发天线间链路更加独立,具有大容量、低功耗、更好的覆盖、对人体的低电磁损害等优势,被认为是未来无线通信系统中的重要技术。分布式MIMO-OFDM系统比集中式MIMO-OFDM系统具有更大的优势,同时也具有其自身的特点。因此需要研究分布式MIMO-OFDM系统适用的自适应技术,以合理分配系统的开销,同时还要改善或者保证系统性能。考虑到分布式MIMO-OFDM系统的上述问题,目前在分布式MIMO-OFDM系统的自适应功率分配、自适应调制以及和自适应技术密切相关的信噪比估计技术方面的研究还比较少。本文拟在上述三个方面做一些工作:本文针对在总的发射功率恒定的情况下,如何对子载波的功率进行分配以提高分布式MIMO-OFDM系统性能的问题,在多径衰落信道下,研究了一种对子载波进行功率分配的算法及其优化算法。仿真结果表明,在考虑大尺度衰落的COST207 TU信道下,在误码率为10? 3和BPSK调制时,具有功率分配的分布式MIMO-OFDM系统与无功率分配的STBC分布式MIMO-OFDM系统相比,能够获得4 dB左右的性能增益。该算法在分布式MIMO-OFDM系统的性能要好于其在集中式MIMO-OFDM系统中的性能。同时,将两个子载波分为一组的优化自适应功率分配算法性能比未进行子载波分组前的性能有0.4 dB的损失。本文针对如何减小分布式MIMO-OFDM系统发射功率的问题,根据注水原理和贪婪算法,在多径衰落信道下,研究了一种对系统子载波进行比特和功率分配的自适应调制算法及其优化算法,使得在满足所要求的系统性能的同时,系统的发射功率最小。仿真结果表明,在考虑大尺度衰落的COST207 TU信道下,采用MQAM调制方式,在误码率为10? 3时,与最大似然检测的STBC分布式MIMO-OFDM系统相比,自适应调制的分布式MIMO-OFDM系统能够获得约2.3 dB的性能增益;和最大似然检测的VBLAST分布式MIMO-OFDM系统相比,获得的性能增益更明显。仿真结果还表明,该算法在分布式MIMO-OFDM系统中的性能要好于其在集中式MIMO-OFDM系统中的性能。同时,将两个子载波分为一组的优化自适应调制性能与未进行子载波分组前的性能近似。在本文研究的分布式MIMO-OFDM系统自适应功率分配和自适应调制算法中,考虑到自适应技术对信号功率的影响,现有的AWGN信道中的信噪比估计算法无法直接使用,因此需要根据两种不同自适应技术的特点重新设计,相应提出了基于均方误差的两种自适应技术的噪声功率估计方法。仿真结果表明,这种噪声功率估计方法在两种自适应技术下都有较好的估计性能。自适应功率分配的分布式MIMO-OFDM系统估计精度要稍好于自适应调制的分布式MIMO-OFDM系统的估计精度,并且在不同信噪比下其性能也比较稳定,而自适应调制的分布式MIMO-OFDM系统在中低信噪比时存在较大的估计误差。本文在分布式MIMO-OFDM系统自适应技术和信噪比估计技术方面的研究成果,可应用于下一代基于分布式MIMO-OFDM思想的分布式蜂窝移动通信网、分布式无线局域网、分布式数字无线电视/广播等无线通信系统的信号处理技术中,具有重要的理论及经济价值。更多还原

【Abstract】 The next generation of mobile communications requirements of large-capacity and high-quality data transmission, so multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system is drawing intensive attention both from academic and industry. In distributed MIMO-OFDM systems, the antennas at the side of base station are not co-located in the base station, but distributed in different locations. Distributed MIMO is promised as a key technology in future wireless communication systems due to its unique merits such as large system capacity, low transmit power, uniform and enhanced coverage and low radiation on the human body.Compared with centralized MIMO-OFDM system, distributed MIMO-OFDM system has more advantages, and also has its own characteristics. Therefore we need to study the adaptive technology of distributed MIMO-OFDM system to allocate the system cost while improving or guaranteeing system performance.To the above problems of distributed MIMO-OFDM system, the researches on distributed MIMO-OFDM adaptive power distribution, adaptive modulation and signal-to-noise ratio (SNR) estimation which closely related to the adaptive technologies is still limited. Hence, in this paper, we present some research work in the three topics mentioned above:How to improve the performance of distributed MIMO-OFDM system by power allocation of its subcarriers under the constant transmission power is studied in this paper. We propose a power allocation algorithm to the subcarriers of distributed MIMO-OFDM system and its improved algorithm over multipath fading channel. Simulation results show that over large scale fading and COST207 TU channel, the proposed algorithm can obtain about 4 dB performance improvement compared with the distributed MIMO-OFDM space-time block code (STBC) system without power allocation in cases of BPSK modulation, when the BER is 10? 3. The performance of power allocation algorithm in distributed MIMO-OFDM system is better than that of centralized MIMO-OFDM system. Meanwhile, the original algorithm outperforms the algorithm based on subcarrier grouping that makes two subcarriers in one group about 0.4dB.We also focus on reducing the transmission power of distributed MIMO-OFDM system. Based on the water-filling principle and the greedy algorithm, we study an adaptive bit and power allocation algorithm to the subcarriers of distributed MIMO-OFDM system and its improved algorithm over multipath fading channel. The algorithm can minimize the transmission power and meet the required performance at the same time. Simulation results show that over large scale fading and COST207 TU channel, the proposed algorithm can achieve about 2.3 dB performance improvement in the case of MQAM modulation when the BER is 10? 3, compared with the distributed MIMO-OFDM STBC system without adaptive modulation, and the performance gain is even more evident compared with distributed MIMO-OFDM VBLAST system with maximum likelihood detection. The performance of adaptive modulation in distributed MIMO-OFDM system is better than that of centralized MIMO-OFDM system. Meanwhile, the algorithm based on subcarrier grouping that makes two subcarriers in one group has the similar performance with the original algorithm.To the two adaptive systems in this paper, we take into account the impact of adaptive technology to signal power. The additive white gaussian noise (AWGN) channel estimation algorithm can not be used directly in the adaptive systems, so the SNR estimation should be redesigned according to the characteristics of two different adaptive technologies. We give the corresponding noise power estimation methods of two adaptive technologies based on the mean square error. Simulation results show that both the two adaptive technologies have good estimation performance. The estimation algorithm in adaptive power allocation distributed MIMO-OFDM system presents better slightly than that in adaptive modulation distributed MIMO-OFDM system, and its performance is relatively stable. The estimation algorithm in adaptive modulation distributed MIMO-OFDM system has greater estimation error in low and medium SNR.The research results of the distributed MIMO-OFDM adaptive power allocation, distributed MIMO-OFDM adaptive modulation and distributed MIMO-OFDM SNR estimation in this paper can be applied in the signal processing techniques of the next generation distributed MIMO-OFDM based distributed cellular mobile communication networks, distributed wireless local area networks, distributed digital TV/Radio wireless communication networks, which are of great theoretical importance and economic value.更多还原