# Joint Interference and Phase Alignment among Data Streams in Multicell MIMO Broadcasting
## 2 Related Work  
At present, most Interference Alignment (IA) algorithms rely on ideal Channel State Information (CSI) [1; 2]. However, in the actual wireless communication, the CSI obtained by the sender often has time delay and error, so that the ideal IA cannot be realized [3; 4]. In recent years, researchers have studied the IA of time delay CSI and error CSI separately, while less research has been conducted on the case of CSI with both time delay and error (time delay error CSI).  
Firstly, in terms of latency CSI, the literature [5; 6] discusses the influence of time delay on the degree of freedom of the K-user interference network and the three-user MIMO Gaussian network. It also considers the imperfect CSI case. Literature [7] gives the IA algorithm under time-varying channel and analyzes the degree of freedom. The literature [8; 9] gives the backtracking algorithm applicable to three-user interference channels and two-cell multiple access channels under time delay CSI. The literature [9] pointed out that the delay CSI can obtain better performance than that without CSI. When the number of users changes and the delay is unknown, in [10] the receiver uses the current CSI and delay CSI and previous precoding to update the current precoding step by step, providing a low-complexity adaptive beam design scheme. Under the classical time delay channel model, the literature [11] predicts the channel by the minimum mean square error (MMSE) and least square error (LSE) and gives a robust IA scheme.  
Second, in terms of error CSI, the literature [12] gives a robust IA based on the MMSE criterion and analyzes the bit error rate (BER). The literature [13] gives the upper and lower limits of the mutual information of the system when the base station knows the noisy CSI. The IA algorithm of weighted MMSE is given in [14]. In [15], based on the error CSI statistical model, a robust minimum interference leakage algorithm is given. The literature [16] carries on QR decomposition to the joint error channel, reduces the intensity of the interference, and improves the performance of the algorithm under error CSI. The literature [17] derives the Max-SINR with stochastic CSI Error Knowledge (Max-SINR-SCEK) algorithm from the error CSI statistical model. Under error CSI, the literature [18] aligns the phase of the sender signal and the receiver signal and gives a robust joint interference phase alignment algorithm under MIMO-MAC.  
It can be seen that in the time delay CSI, the literature [5; 6] analyzed the degree of freedom, and no concrete implementation was given. The literature [7; 8] needed the number of known users and the current delay CSI, so it is difficult to be applied in practice. The backtracking IA in [8; 9] required the channel to have interlaced block fading characteristics. The systems in [10; 11] had a large overhead.  
In the error CSI, the literature [12; 13; 14] did not consider the data flow correlation and power allocation. The literature [15] did not consider the effect on useful signals. Interference leakage in the literature [16] has become a major factor in limiting channel capacity, and there is no power allocation. Literature [17] required that the sender has more antennas and high sensitivity to error CSI. Literature [18] did not consider how to increase the power of useful signals.  
In summary, in the case of time delay error CSI, this paper gives the solution to the existing problem by proposing a joint interference and phase alignment algorithm based on Bayesian estimation and power allocation among data streams.