Analysis Of Massive MIMO System And Interference Management Technologies

The techniques of massive Multi-Input Multi-Output (MIMO) system and interference management are of great importance in wireless communications nowadays. Among those, the massive MIMO system technique is able to reach a remarkable capacity and spectrum efficiency by employing a large number of antennas at the base station (BS) and serving many users. However, because an amount of data streams are supported in limited frequency resources at the same time, the interference in the massive MIMO system is tremendous. As a result, something must be done to suppress the interferences. Since the complexity of non-linear precoding is unacceptable, especially in massive MIMO system, linear precoding technique plays an important part.In wireless cellular system and multi-user interference (MUI) channel sys-tem, inter-cell interference and inter-user interference IUI become the main factors which limit the capacity, respectively. Interference management is able to suppress interference and improve system capacity. Through precoding, in-terference management techniques suppress the inter-cell interference and IUI into a smaller dimension space, which makes the desired signal transmit with-out interruption, thus effectively increasing degrees of freedom (DoF) of the system, and improving system capacity.The main contribution and contents of this paper are as follows:Firstly, the optimal served number of users is derived in the downlink mas-sive multiuser-MIMO (MU-MIMO) system through lenear precoding based on the actual channel model. On this basis, this paper analyzes the findings of the above results, puts forward the corresponding low-complexity data stream allo-cation methods. Specifically, the asymptotic expressions of downlink massive MU-MIMO system under regularized zero-forcing (RZF) precoding and sin-gular value decomposition (SVD) precoding are derived. And the asymptotic expression of downlink distributed antenna system (DAS) under zero-forcing (ZF) precoding is derived. Noting that in both system models, the sum rates decrease while the user numbers increase when the transmit power is limited. According to this, the low-complexity user selections are proposed and ana-lyzed.Secondly, this paper proposed a novel interference management tech-nique, which is applied in both the single-hop and multi-hop multi-user in-terference channel models. In the multi-user interference channel system, the receiver could receive the desired signal without interference, with the help of an instantaneous relay. Meanwhile, the whole signal space is occupied by the desired signal. In the multi-hop interference channel model, the receiver could also receive desired signal without jamming. At the same time, by utilizing energy harvesting (EH), the interference signals would be absorbed to enhance the energy efficiency. Both scenarios have shown that such technique can in-crease the user’s DoFs and the system’s sum rate.Finally, we summarize the massive MIMO system and interference man-agement techniques, and look forward to the next stage of work.