The Key Technique Of Interference Alignment For MIMO Downlink Heterogeneous Networks

With the rapid development of wireless communication technology, how to meet the relentless traffic demand to support higher transmission rate and system capacity becomes an important issue. Multiple input multiple output(MIMO) networks develop rapidly because it can increase the system capacity. In future, we will deploy the heterogeneous networks which consists of one macro BS and several pico BSs to support more users to communicate. In recent years, researchers have studying deeply on MIMO heterogeneous networks. Since the scarcity of the available frequency spectrum, macro cells and pico cells share the same frequency spectrum. Therefore, the interference management became a promising issue to mitigate the inter-cell interference(ICI) and the inter-user interference(IUI), which induced by the simultaneous transmission from the BSs to their corresponding users. Hence, as a key technology, interference alignment(IA) has been highlighted to mitigate interference and improve system capacity efficiently. The main idea of IA is to align multiple interferences into a smaller subspace so that the dimension allocated for signal transmission will increase as much as possible.Firstly, we introduce the MIMO technology and heterogeneous networks, and study the basic principles and core ideas of interference alignment. Meanwhile, we use degree of freedom to measure the system capacity.Secondly, an interference alignment scheme based on null space for homogeneous networks is detailed analyzed. However, the scheme do not applied to MIMO heterogeneous networks. In addition, we study a non-iterative interference alignment scheme for MIMO heterogeneous networks. But this method can be only applied to the scenario which all the BSs transmit the same data streams to users.For the shortcomings of the existing schemes, a novel interference management scheme based on two-stage null space and interference subspace location for MIMO heterogeneous networks is proposed and in what follows, antenna configuration to ensure the proposed design will be discussed.. We use the two-stage null space algorithm to mitigate the inter-cell interference efficiently. Specifically, the first-stage null space algorithm is applied to mitigate the inter-cell interference from macro BS to all the pico users and the second-stage null space algorithm is used to eliminate the inter-cell interference between pico cells. At the same time, the algorithm based on interference subspace allocation will be used to eliminate the interference from pico BSs to all the macro users. The proposed scheme based on two-stage null space and interference subspace allocation can effectively eliminate the inter-cell interference and inter-user interference.Finally, we compare the degree of freedom between the proposed method and the existing scheme in the same system configuration. According to the simulation results, we can see that the achievable degree of freedom of the interference alignment based on two-stage null space and interference subspace allocation is higher than the existing scheme.