【作者】 高鹏；

【导师】 白智全；

【作者基本信息】 山东大学 ， 通信与信息系统， 2015， 硕士

【摘要】 大规模多输入多输出(Massive Multiple-Input Multiple-output, Massive MIMO)技术通过在宏小区基站安装大规模天线阵列而实现,并通常采用时分双工模式进行工作以利用信道互易性,其可以大幅提高系统的吞吐量和能量效率,且具有很好的鲁棒性,硬件实现成本低。然而宏小区能量的集中随之带来的是远离宏小区基站和用户的区域产生大片频谱空白区域。为有效利用这些区域,认知大规模MIMO技术被提出并广泛地加以研究。这项技术通过在大规模MIMO系统中布置大量小范围的认知家庭网络,并通过允许认知家庭网络对频谱的再利用,可以有效地提高系统总的吞吐量。认知家庭网络接入方案的研究是认知大规模MIMO中的重要问题,即认知家庭网络何时、以何种方式接入频谱。典型的认知家庭网络接入方案包括时分双工接入方案、反向时分双工接入方案、混分双工接入方案等,这些方案具有各自的优缺点。在此基础上,本文首先给出了一种认知家庭网络的混合时分双工接入方案,并在此基础上提出了一种基于置信因素的加权合作频谱感知方案来提高认知家庭网络的检测性能。论文对所提方案的性能进行了理论分析与仿真,并与其他方案作了比较。本文的主要工作如下：首先,提出了认知家庭网络的混合时分双工接入方案。传统的认知家庭网络接入方案中,家庭网络基站只要在检测到宏小区基站或用户存在活动情况时,就必须放弃频谱再利用机会,这降低了系统的频谱分享概率。考虑到实际环境中认知家庭网络的分布及环境差异造成通信状况不同的情况,本文提出了一种混合时分双工接入方案,依据家庭网络基站在宏小区上行与下行的能量检测结果,认知家庭网络充分利用其分布特点可灵活地采用对宏小区影响最小的方式接入网络。论文给出了该混合时分双工接入方案的具体实施过程,以及吞吐量分析,并通过实验仿真验证了所提方案对系统吞吐量的显著提升。其次,提出了综合置信因素的认知家庭网络加权合作频谱检测方案。考虑在实际环境中,单个认知家庭网络检测可靠性较差,以及多个认知家庭网络干扰叠加问题,本文针对性的提出了综合置信因素的认知家庭网络加权合作频谱检测方案。首先,各家庭网络基站根据基站间信道的信噪比进行动态分组并根据分组情况实施合作频谱感知以更新置信因子,然后使置信度高的家庭网络基站更相信自己的判断,而置信度低的家庭网络基站接受其它家庭网络基站的协助。论文给出了动态分组及加权检测的实施过程,以信息论与概率统计为数学工具给出了性能分析,并通过实验仿真验证了该方案的合理性,以及在对宏小区吞吐量造成较低影响的前提下,家庭网络层频谱分享概率与吞吐量的提高。最后,论文总结了认知大规模MIMO技术中门限值优化等方面需要进一步解决的问题和未来的可能研究点。更多还原

【Abstract】 Massive Multiple-Input Multiple-output (Massive MIMO) technology is achieved by mounting a large antenna array at the macrocell (MC) base station (MBS), and effectively exploits the channel reciprocity using time-division duplex (TDD) scheme. This technology can bring tremendous improvements in throughput and energy efficiency, and has a good robustness as well as low cost hardware implementation. Nevertheless, the concentration of the energy means a lot of blank areas of spectrum in the regions far away from MBS and MUs. In order to exploit these areas effectively, cognitive massive MIMO technology is proposed and widely studied, which deploys a large number of small range femtocells (FCs) in massive MIMO system, and enables significant increase in system capacity by spectrum reuse (SR) of the FCs.The research on the access scheme of FCs is an important problem in cognitive massive MIMO technology, i.e. when and how the FCs can access the spectrum. The typical access schemes of FCs include the time division duplex (TDD) access scheme, the reverse time division duplex (RTDD) access scheme and the hybrid division duplex (HDD) access scheme, these schemes have different advantages and disadvantages. Based on these schemes above, this thesis proposes a hybrid time division duplex (HTDD) access scheme for FCs, and then exploits a confidence factor based weighted cooperative spectrum sensing (CFWCSS) technology to improve the detection performance of FCs in this HTDD access scheme. Furthermore, this thesis presents the theoretical analysis and simulation on the performance of the proposed scheme, and compares it with other schemes. The main research work of the thesis is as follows.Firstly, an HTDD access scheme for FCs is proposed. In the traditional access schemes, the FCs, which detect the MBS or one of the MUs is active, must abandon the SR opportunity, this reduces the spectrum sharing probability of system. Considering the different communication conditions of FCs caused by the difference of distribution and environmental, we propose an HTDD access scheme for FCs in this thesis. This scheme makes full use of the distribution characteristics of FCs, i.e. FCs can flexibly adopt the access scheme, which causes the smallest effects on MC, according to the energy detection results in both the macro uplink (UL) and downlink (DL) time slots. This thesis presents the concrete implementation process of this HTDD access scheme, and analyzes the throughput. Simulation results show that the proposed scheme can significantly improve the system throughput.Secondly, a CFWCSS scheme is proposed. Considering the poor detection reliability of a single FC and the interference superposition problem of multiple FCs in realistic situations, this thesis proposes a CFWCSS scheme. At first, according to the signal-to-noise ratio (SNR) of all the inter-user channels for each FCs in the massive MIMO system, we can group all the FCs into clusters dynamically and make them perform cooperative spectrum sensing to update the confidence factors. Then, each FC will have more confidence to the detection result from itself or the other FCs according to the confidence factors. This thesis presents the concrete dynamical grouping process of this CFWCSS scheme, and analyzes the performance by utilizing information theory and probability statistics as mathematical tools. Simulation results show that the proposed scheme can significantly improve the spectrum sharing probability and throughput of FC-tier while only slightly sacrificing MC-tier throughput.Finally, the problems, e.g. the threshold optimization, to be solved in cognitive massive MIMO technology and future research topics are summarized.更多还原