Research On Interference Alignment In Heterogeneous Networks

The co-channel interference (CCI) is believed as a major bottleneck to data rate improvement, while interference management technology is a difficult subject in the field of wireless communications. As an advanced beamforming technique, interference alignment (IA), not only achieving higher capacity than the previously believed but also reducing the system complexity, has been widely investigated as an effective interference management technique in wireless networks. In order to; meet the explosively increasing traffic demand, heterogeneous networks (HetNets) are the main tendency in wireless networks. By deploying a number of small cells, such as picocells and femtocells, overlaid with conventional macro networks, the coverage is extended and the spectral utilization is increased. Nevertheless, as the macro cell and small cells reuse the same spectrum resources, the user equipments (UEs) experience severe CCI, and then the research of IA technique becomes increasing complex. Consequently, improvements and some new designs of IA technique must be provided according to the characteristics of CCI in HetNets.The research work is sponsored by two business cooperation projects with China academy of telecommunications technology, named as "Nonlinear precoding and interference alignment technology in LTE-A system" and "The signal processing and resource scheduling of distributed joint processing systems". The main contents and achievements of the research are summarized as follows:(1) This dissertation gives the summary of IA technique. Firstly, the basic principles of IA in time domain, frequency domain and spatial domain are described, respectively. Then, the research status of IA in typical channels, cellular networks, cognitive radio networks and multi-hop networks are summarized and analyzed, respectively. Finally, the IA techniques for HetNets are analyzed in depth. In addition, the challenges and the issues need to be further addressed are also pointed out.(2) This dissertation researches the IA schemes for small cell tier. In multi-cell and multi-user small cell tier, the existing IA schemes are mainly focus on eliminating the interference and optimizing a single UE’s data rate, which do not consider the fairness among the UEs. If the fairness is not taken into account, the quality of service (QoS) of UEs in the outer regions of small cell and some areas with poor channel conditions can not be ensured. This paper proposes an IA scheme based on Nash bargaining solution (NBS), which can improve the data rate fairness among UEs without decrease of the total achievable rate. Firstly, the inter-cell interference (ICI) is eliminated and then the multi-cell network is equivalent to multiple single-cell networks; Secondly, an optimization problem on precoding matrices is modeled according to the cooperative game relationship among UEs, then the inter-user interference (IUI) is aligned onto a multi-dimensional subspace and the fairness of the UEs inside each cell is balanced. The simulations show that the proposed scheme can obtain higher data rate and fairness of UEs then the existing IA schemes.(3) This dissertation researches the IA schemes in the open subscriber group (OSG) mode of HetNets. To the best of our knowledge, the existing IA schemes in the OSG mode are only applied to some specific networks, such as the network with two or three picocells in a macrocell, and cannot be straightforwardly extended to general case with arbitrary number of picocells in a macrocell. This paper analyzes the interference distribution of the OSG mode. And in a general framework consisting of arbitrary number of picocells within a macro cell three IA schemes are proposed considering the lower computing complexity for eliminating the all interference, the higher rate performance and the lower requirement of receive antennas respectively. The first scheme, named as zero forcing IA (ZF-IA) scheme, aligns the inter picocell interference onto an arbitrary sub-space of the cross-tier interference. Considering the channel state information (CSI) of the desired channel of pico UEs, the second scheme, named as optimal desired sub-channel selected IA (ODC-IA) scheme, aligns the inter picocell interference onto a certain sub-space of the cross-tier interference, which guarantees the largest channel gain of the desired signal of pico UEs. The third IA scheme, named as maximum cross-tier interference selected IA (MI-IA) scheme, is designed for the system with less receive antennas. The inter picocell interference is aligned onto the space of the strongest cross-tier interference and only the interference on this space is nullified. The simulations show that the proposed IA schemes outperform the existing IA schemes on rate and BER performance.(4) This dissertation researches the IA schemes in the closed subscriber group (CSG) mode of HetNets. The CCI in the CSG mode of two-tier HetNets is severe and complicated, and the existing IA schemes are used to suppress CCI without effective utilization. If any technique can take advantage of CCI, the system performance can be further improved. This paper proposes an interference alignment-simultaneous wireless information and power transfer (IA-SWIPT) scheme, which jointly research IA and energy harvesting technique. The energy efficiency is maximized by collecting the power of aligned interference and regarding it as a source of energy. Firstly, the inter macro-user interference is removed and the inter picocell interference is aligned onto the space of the strongest cross-layer interference. Then, the utilization signal power in certain cross-layer interference subspaces is harvested and the energy efficiency per receive antenna of UE is maximized. The simulations show that the proposed IA-SWIPT scheme can obtain higher energy efficiency, guarantee the utilization of receive antennas and promote the total achievable rate in the case of lower and medium signal to noise ratio.